WorldWideScience

Sample records for learning ml approaches

  1. OpenML : An R package to connect to the machine learning platform OpenML

    NARCIS (Netherlands)

    Casalicchio, G.; Bossek, J.; Lang, M.; Kirchhoff, D.; Kerschke, P.; Hofner, B.; Seibold, H.; Vanschoren, J.; Bischl, B.

    2017-01-01

    OpenML is an online machine learning platform where researchers can easily share data, machine learning tasks and experiments as well as organize them online to work and collaborate more efficiently. In this paper, we present an R package to interface with the OpenML platform and illustrate its

  2. ML Confidential : machine learning on encrypted data

    NARCIS (Netherlands)

    Graepel, T.; Lauter, K.; Naehrig, M.

    2012-01-01

    We demonstrate that by using a recently proposed somewhat homomorphic encryption (SHE) scheme it is possible to delegate the execution of a machine learning (ML) algorithm to a compute service while retaining confidentiality of the training and test data. Since the computational complexity of the

  3. AstroML: "better, faster, cheaper" towards state-of-the-art data mining and machine learning

    Science.gov (United States)

    Ivezic, Zeljko; Connolly, Andrew J.; Vanderplas, Jacob

    2015-01-01

    We present AstroML, a Python module for machine learning and data mining built on numpy, scipy, scikit-learn, matplotlib, and astropy, and distributed under an open license. AstroML contains a growing library of statistical and machine learning routines for analyzing astronomical data in Python, loaders for several open astronomical datasets (such as SDSS and other recent major surveys), and a large suite of examples of analyzing and visualizing astronomical datasets. AstroML is especially suitable for introducing undergraduate students to numerical research projects and for graduate students to rapidly undertake cutting-edge research. The long-term goal of astroML is to provide a community repository for fast Python implementations of common tools and routines used for statistical data analysis in astronomy and astrophysics (see http://www.astroml.org).

  4. Machine learning (ML)-guided OPC using basis functions of polar Fourier transform

    Science.gov (United States)

    Choi, Suhyeong; Shim, Seongbo; Shin, Youngsoo

    2016-03-01

    With shrinking feature size, runtime has become a limitation of model-based OPC (MB-OPC). A few machine learning-guided OPC (ML-OPC) have been studied as candidates for next-generation OPC, but they all employ too many parameters (e.g. local densities), which set their own limitations. We propose to use basis functions of polar Fourier transform (PFT) as parameters of ML-OPC. Since PFT functions are orthogonal each other and well reflect light phenomena, the number of parameters can significantly be reduced without loss of OPC accuracy. Experiments demonstrate that our new ML-OPC achieves 80% reduction in OPC time and 35% reduction in the error of predicted mask bias when compared to conventional ML-OPC.

  5. RED-ML

    DEFF Research Database (Denmark)

    Xiong, Heng; Liu, Dongbing; Li, Qiye

    2017-01-01

    using diverse RNA-seq datasets, we have developed a software tool, RED-ML: RNA Editing Detection based on Machine learning (pronounced as "red ML"). The input to RED-ML can be as simple as a single BAM file, while it can also take advantage of matched genomic variant information when available...... accurately detect novel RNA editing sites without relying on curated RNA editing databases. We have also made this tool freely available via GitHub . We have developed a highly accurate, speedy and general-purpose tool for RNA editing detection using RNA-seq data....... With the availability of RED-ML, it is now possible to conveniently make RNA editing a routine analysis of RNA-seq. We believe this can greatly benefit the RNA editing research community and has profound impact to accelerate our understanding of this intriguing posttranscriptional modification process....

  6. International Conference ML4CPS 2016

    CERN Document Server

    Niggemann, Oliver; Kühnert, Christian

    2017-01-01

    The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, September 29th, 2016. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments. The Editors Prof. Dr.-Ing. Jürgen Beyerer is Professor at the Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. Prof. Dr. Oliver Niggemann is Professor for Embedded Software Engineering. His research interests are in the field of Di...

  7. A best-first tree-searching approach for ML decoding in MIMO system

    KAUST Repository

    Shen, Chung-An; Eltawil, Ahmed M.; Mondal, Sudip; Salama, Khaled N.

    2012-01-01

    In MIMO communication systems maximum-likelihood (ML) decoding can be formulated as a tree-searching problem. This paper presents a tree-searching approach that combines the features of classical depth-first and breadth-first approaches to achieve

  8. A best-first tree-searching approach for ML decoding in MIMO system

    KAUST Repository

    Shen, Chung-An

    2012-07-28

    In MIMO communication systems maximum-likelihood (ML) decoding can be formulated as a tree-searching problem. This paper presents a tree-searching approach that combines the features of classical depth-first and breadth-first approaches to achieve close to ML performance while minimizing the number of visited nodes. A detailed outline of the algorithm is given, including the required storage. The effects of storage size on BER performance and complexity in terms of search space are also studied. Our result demonstrates that with a proper choice of storage size the proposed method visits 40% fewer nodes than a sphere decoding algorithm at signal to noise ratio (SNR) = 20dB and by an order of magnitude at 0 dB SNR.

  9. An Event-Triggered Machine Learning Approach for Accelerometer-Based Fall Detection.

    Science.gov (United States)

    Putra, I Putu Edy Suardiyana; Brusey, James; Gaura, Elena; Vesilo, Rein

    2017-12-22

    The fixed-size non-overlapping sliding window (FNSW) and fixed-size overlapping sliding window (FOSW) approaches are the most commonly used data-segmentation techniques in machine learning-based fall detection using accelerometer sensors. However, these techniques do not segment by fall stages (pre-impact, impact, and post-impact) and thus useful information is lost, which may reduce the detection rate of the classifier. Aligning the segment with the fall stage is difficult, as the segment size varies. We propose an event-triggered machine learning (EvenT-ML) approach that aligns each fall stage so that the characteristic features of the fall stages are more easily recognized. To evaluate our approach, two publicly accessible datasets were used. Classification and regression tree (CART), k -nearest neighbor ( k -NN), logistic regression (LR), and the support vector machine (SVM) were used to train the classifiers. EvenT-ML gives classifier F-scores of 98% for a chest-worn sensor and 92% for a waist-worn sensor, and significantly reduces the computational cost compared with the FNSW- and FOSW-based approaches, with reductions of up to 8-fold and 78-fold, respectively. EvenT-ML achieves a significantly better F-score than existing fall detection approaches. These results indicate that aligning feature segments with fall stages significantly increases the detection rate and reduces the computational cost.

  10. Use of machine learning approaches for novel drug discovery.

    Science.gov (United States)

    Lima, Angélica Nakagawa; Philot, Eric Allison; Trossini, Gustavo Henrique Goulart; Scott, Luis Paulo Barbour; Maltarollo, Vinícius Gonçalves; Honorio, Kathia Maria

    2016-01-01

    The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery methodology, such as prediction of target structure, prediction of biological activity of new ligands through model construction, discovery or optimization of hits, and construction of models that predict the pharmacokinetic and toxicological (ADMET) profile of compounds. This article presents an overview on some applications of ML techniques in drug design. These techniques can be employed in ligand-based drug design (LBDD) and structure-based drug design (SBDD) studies, such as similarity searches, construction of classification and/or prediction models of biological activity, prediction of secondary structures and binding sites docking and virtual screening. Successful cases have been reported in the literature, demonstrating the efficiency of ML techniques combined with traditional approaches to study medicinal chemistry problems. Some ML techniques used in drug design are: support vector machine, random forest, decision trees and artificial neural networks. Currently, an important application of ML techniques is related to the calculation of scoring functions used in docking and virtual screening assays from a consensus, combining traditional and ML techniques in order to improve the prediction of binding sites and docking solutions.

  11. HLS4ML: deploying deep learning on FPGAs for L1 trigger and Data Acquisition

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Machine learning is becoming ubiquitous across HEP. There is great potential to improve trigger and DAQ performances with it. However, the exploration of such techniques within the field in low latency/power FPGAs has just begun. We present HLS4ML, a user-friendly software, based on High-Level Synthesis (HLS), designed to deploy network architectures on FPGAs. As a case study, we use HLS4ML for boosted-jet tagging with deep networks at the LHC. We show how neural networks can be made fit the resources available on modern FPGAs, thanks to network pruning and quantization. We map out resource usage and latency versus network architectures, to identify the typical problem complexity that HLS4ML could deal with. We discuss possible applications in current and future HEP experiments.

  12. Geminivirus data warehouse: a database enriched with machine learning approaches.

    Science.gov (United States)

    Silva, Jose Cleydson F; Carvalho, Thales F M; Basso, Marcos F; Deguchi, Michihito; Pereira, Welison A; Sobrinho, Roberto R; Vidigal, Pedro M P; Brustolini, Otávio J B; Silva, Fabyano F; Dal-Bianco, Maximiller; Fontes, Renildes L F; Santos, Anésia A; Zerbini, Francisco Murilo; Cerqueira, Fabio R; Fontes, Elizabeth P B

    2017-05-05

    The Geminiviridae family encompasses a group of single-stranded DNA viruses with twinned and quasi-isometric virions, which infect a wide range of dicotyledonous and monocotyledonous plants and are responsible for significant economic losses worldwide. Geminiviruses are divided into nine genera, according to their insect vector, host range, genome organization, and phylogeny reconstruction. Using rolling-circle amplification approaches along with high-throughput sequencing technologies, thousands of full-length geminivirus and satellite genome sequences were amplified and have become available in public databases. As a consequence, many important challenges have emerged, namely, how to classify, store, and analyze massive datasets as well as how to extract information or new knowledge. Data mining approaches, mainly supported by machine learning (ML) techniques, are a natural means for high-throughput data analysis in the context of genomics, transcriptomics, proteomics, and metabolomics. Here, we describe the development of a data warehouse enriched with ML approaches, designated geminivirus.org. We implemented search modules, bioinformatics tools, and ML methods to retrieve high precision information, demarcate species, and create classifiers for genera and open reading frames (ORFs) of geminivirus genomes. The use of data mining techniques such as ETL (Extract, Transform, Load) to feed our database, as well as algorithms based on machine learning for knowledge extraction, allowed us to obtain a database with quality data and suitable tools for bioinformatics analysis. The Geminivirus Data Warehouse (geminivirus.org) offers a simple and user-friendly environment for information retrieval and knowledge discovery related to geminiviruses.

  13. RuleML-Based Learning Object Interoperability on the Semantic Web

    Science.gov (United States)

    Biletskiy, Yevgen; Boley, Harold; Ranganathan, Girish R.

    2008-01-01

    Purpose: The present paper aims to describe an approach for building the Semantic Web rules for interoperation between heterogeneous learning objects, namely course outlines from different universities, and one of the rule uses: identifying (in)compatibilities between course descriptions. Design/methodology/approach: As proof of concept, a rule…

  14. Advanced methods in NDE using machine learning approaches

    Science.gov (United States)

    Wunderlich, Christian; Tschöpe, Constanze; Duckhorn, Frank

    2018-04-01

    Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predictions, or to find patterns, particularly with new and unseen similar data, fits perfectly to Non-Destructive Evaluation. The advantages of ML in NDE are obvious in such tasks as pattern recognition in acoustic signals or automated processing of images from X-ray, Ultrasonics or optical methods. Fraunhofer IKTS is using machine learning algorithms in acoustic signal analysis. The approach had been applied to such a variety of tasks in quality assessment. The principal approach is based on acoustic signal processing with a primary and secondary analysis step followed by a cognitive system to create model data. Already in the second analysis steps unsupervised learning algorithms as principal component analysis are used to simplify data structures. In the cognitive part of the software further unsupervised and supervised learning algorithms will be trained. Later the sensor signals from unknown samples can be recognized and classified automatically by the algorithms trained before. Recently the IKTS team was able to transfer the software for signal processing and pattern recognition to a small printed circuit board (PCB). Still, algorithms will be trained on an ordinary PC; however, trained algorithms run on the Digital Signal Processor and the FPGA chip. The identical approach will be used for pattern recognition in image analysis of OCT pictures. Some key requirements have to be fulfilled, however. A sufficiently large set of training data, a high signal-to-noise ratio, and an optimized and exact fixation of components are required. The automated testing can be done subsequently by the machine. By integrating the test data of many components along the value chain further optimization including lifetime and durability

  15. SysML for systems engineering a model-based approach

    CERN Document Server

    Holt, Jon

    2013-01-01

    This new edition of this popular text has been fully updated to reflect SysML 1.3, the latest version of the standard, and the discussion has been extended to show the power of SysML as a tool for systems engineering in an MBSE context.

  16. Machine learning for epigenetics and future medical applications.

    Science.gov (United States)

    Holder, Lawrence B; Haque, M Muksitul; Skinner, Michael K

    2017-07-03

    Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems with ML to develop a more efficient feature selection process and address the imbalance problem in all genomic data sets. The power of this novel ML approach and our ability to predict epigenetic phenomena and associated disease is suggested. The current approach requires extensive computation of features over the genome. A promising new approach is to introduce Deep Learning (DL) for the generation and simultaneous computation of novel genomic features tuned to the classification task. This approach can be used with any genomic or biological data set applied to medicine. The application of molecular epigenetic data in advanced machine learning analysis to medicine is the focus of this review.

  17. Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

    Science.gov (United States)

    Wallace, Byron C; Noel-Storr, Anna; Marshall, Iain J; Cohen, Aaron M; Smalheiser, Neil R; Thomas, James

    2017-11-01

    Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML. We trained a classifier to discriminate between citations that describe RCTs and those that do not. We then adopted a simple strategy of automatically excluding citations deemed very unlikely to be RCTs by the classifier and deferring to crowdworkers otherwise. Combining ML and crowdsourcing provides a highly sensitive RCT identification strategy (our estimates suggest 95%-99% recall) with substantially less effort (we observed a reduction of around 60%-80%) than relying on manual screening alone. Hybrid crowd-ML strategies warrant further exploration for biomedical curation/annotation tasks. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  18. Promises of Machine Learning Approaches in Prediction of Absorption of Compounds.

    Science.gov (United States)

    Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

    2018-01-01

    The Machine Learning (ML) is one of the fastest developing techniques in the prediction and evaluation of important pharmacokinetic properties such as absorption, distribution, metabolism and excretion. The availability of a large number of robust validation techniques for prediction models devoted to pharmacokinetics has significantly enhanced the trust and authenticity in ML approaches. There is a series of prediction models generated and used for rapid screening of compounds on the basis of absorption in last one decade. Prediction of absorption of compounds using ML models has great potential across the pharmaceutical industry as a non-animal alternative to predict absorption. However, these prediction models still have to go far ahead to develop the confidence similar to conventional experimental methods for estimation of drug absorption. Some of the general concerns are selection of appropriate ML methods and validation techniques in addition to selecting relevant descriptors and authentic data sets for the generation of prediction models. The current review explores published models of ML for the prediction of absorption using physicochemical properties as descriptors and their important conclusions. In addition, some critical challenges in acceptance of ML models for absorption are also discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  19. Machine learning in geosciences and remote sensing

    Directory of Open Access Journals (Sweden)

    David J. Lary

    2016-01-01

    Full Text Available Learning incorporates a broad range of complex procedures. Machine learning (ML is a subdivision of artificial intelligence based on the biological learning process. The ML approach deals with the design of algorithms to learn from machine readable data. ML covers main domains such as data mining, difficult-to-program applications, and software applications. It is a collection of a variety of algorithms (e.g. neural networks, support vector machines, self-organizing map, decision trees, random forests, case-based reasoning, genetic programming, etc. that can provide multivariate, nonlinear, nonparametric regression or classification. The modeling capabilities of the ML-based methods have resulted in their extensive applications in science and engineering. Herein, the role of ML as an effective approach for solving problems in geosciences and remote sensing will be highlighted. The unique features of some of the ML techniques will be outlined with a specific attention to genetic programming paradigm. Furthermore, nonparametric regression and classification illustrative examples are presented to demonstrate the efficiency of ML for tackling the geosciences and remote sensing problems.

  20. Discovery learning with SAVI approach in geometry learning

    Science.gov (United States)

    Sahara, R.; Mardiyana; Saputro, D. R. S.

    2018-05-01

    Geometry is one branch of mathematics that an important role in learning mathematics in the schools. This research aims to find out about Discovery Learning with SAVI approach to achievement of learning geometry. This research was conducted at Junior High School in Surakarta city. Research data were obtained through test and questionnaire. Furthermore, the data was analyzed by using two-way Anova. The results showed that Discovery Learning with SAVI approach gives a positive influence on mathematics learning achievement. Discovery Learning with SAVI approach provides better mathematics learning outcomes than direct learning. In addition, students with high self-efficacy categories have better mathematics learning achievement than those with moderate and low self-efficacy categories, while student with moderate self-efficacy categories are better mathematics learning achievers than students with low self-efficacy categories. There is an interaction between Discovery Learning with SAVI approach and self-efficacy toward student's mathematics learning achievement. Therefore, Discovery Learning with SAVI approach can improve mathematics learning achievement.

  1. libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.

    Science.gov (United States)

    Vella, Michael; Cannon, Robert C; Crook, Sharon; Davison, Andrew P; Ganapathy, Gautham; Robinson, Hugh P C; Silver, R Angus; Gleeson, Padraig

    2014-01-01

    NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment.

  2. libNeuroML and PyLEMS: using Python to combine imperative and declarative modelling approaches in computational neuroscience

    Directory of Open Access Journals (Sweden)

    Michael eVella

    2014-04-01

    Full Text Available NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell,and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two APIs (Application Programming Interfaces written in Python (http://www.python.org, which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment.

  3. Introducing the Collaborative Learning Modeling Language (ColeML)

    DEFF Research Database (Denmark)

    Bundsgaard, Jeppe

    2014-01-01

    in this area, represented by, for example, the Workflow Management Coalition (Hollingsworth, 1995) and the very widespread standard Business Process Modeling and Notation (BPMN), has been criticized on the basis of research in knowledge work processes. Inspiration for ColeML is found in this research area...

  4. CellML, SED-ML, and the Physiome Model Repository

    OpenAIRE

    Nickerson, David

    2016-01-01

    Invited presentation delivered at COMBINE 2016.CellML, SED-ML, and the Physiome Model Repository.David Nickerson, Auckland Bioengineering Institute, University of Auckland, New Zealand.CellML is an XML-based protocol for storing and exchanging computer-based mathematical models in an unambiguous, modular, and reusable manner. In addition to introducing CellML, in this presentation I will provide some of physiological examples that have help drive the development and adoption of CellML. I will...

  5. GeoSciML and EarthResourceML Update, 2012

    Science.gov (United States)

    Richard, S. M.; Commissionthe Management; Application Inte, I.

    2012-12-01

    CGI Interoperability Working Group activities during 2012 include deployment of services using the GeoSciML-Portrayal schema, addition of new vocabularies to support properties added in version 3.0, improvements to server software for deploying services, introduction of EarthResourceML v.2 for mineral resources, and collaboration with the IUSS on a markup language for soils information. GeoSciML and EarthResourceML have been used as the basis for the INSPIRE Geology and Mineral Resources specifications respectively. GeoSciML-Portrayal is an OGC GML simple-feature application schema for presentation of geologic map unit, contact, and shear displacement structure (fault and ductile shear zone) descriptions in web map services. Use of standard vocabularies for geologic age and lithology enables map services using shared legends to achieve visual harmonization of maps provided by different services. New vocabularies have been added to the collection of CGI vocabularies provided to support interoperable GeoSciML services, and can be accessed through http://resource.geosciml.org. Concept URIs can be dereferenced to obtain SKOS rdf or html representations using the SISSVoc vocabulary service. New releases of the FOSS GeoServer application greatly improve support for complex XML feature schemas like GeoSciML, and the ArcGIS for INSPIRE extension implements similar complex feature support for ArcGIS Server. These improved server implementations greatly facilitate deploying GeoSciML services. EarthResourceML v2 adds features for information related to mining activities. SoilML provides an interchange format for soil material, soil profile, and terrain information. Work is underway to add GeoSciML to the portfolio of Open Geospatial Consortium (OGC) specifications.

  6. Using VS30 to Estimate Station ML Adjustments (dML)

    Science.gov (United States)

    Yong, A.; Herrick, J.; Cochran, E. S.; Andrews, J. R.; Yu, E.

    2017-12-01

    Currently, new seismic stations added to a regional seismic network cannot be used to calculate local or Richter magnitude (ML) until a revised region-wide amplitude decay function is developed. The new station must record a minimum number of local and regional events that meet specific amplitude requirements prior to re-calibration of the amplitude decay function. Therefore, there can be significant delay between when a new station starts contributing real-time waveform packets and when the data can be included in magnitude estimation. The station component adjustments (dML; Uhrhammer et al., 2011) are calculated after first inverting for a new regional amplitude decay function, constrained by the sum of dML for long-running stations. Here, we propose a method to calculate an initial dML using known or proxy values of seismic site conditions. For site conditions, we use the time-averaged shear-wave velocity (VS) of the upper 30 m (VS30). We solve for dML as described in Equation (1) by Uhrhammer et al. (2011): ML = log (A) - log A0 (r) + dML, where A is the maximum Wood and Anderson (1925) trace amplitude (mm), r is the distance (km), and dML is the station adjustment. Measured VS30 and estimated dML data are comprised of records from 887 horizontal components (east-west and north-south orientations) from 93 seismic monitoring stations in the California Integrated Seismic Network. VS30 values range from 202 m/s to 1464 m/s and dML range from -1.10 to 0.39. VS30 and dML exhibit a positive correlation coefficient (R = 0.72), indicating that as VS30 increases, dML increases. This implies that greater site amplification (i.e., lower VS30) results in smaller ML. When we restrict VS30 regional network ML estimates immediately without the need to wait until a minimum set of earthquake data has been recorded.

  7. Approaches toward learning in physiotherapy

    Directory of Open Access Journals (Sweden)

    L. Keiller

    2013-11-01

    Full Text Available The aim of this study was to investigate the approaches toward learning of undergraduate Physiotherapy students in a PBl module to enhance facilitation of learning at the Stellenbosch University, Division of Physiotherapy in South Africa. This quantitative, descriptive study utilized the revised Two-factor Study Process Questionnaire (r-SPQ-2f to evaluate the study cohorts’ approaches toward learning in the module. results of the data instruments were analysed statistically and discussed in a descriptive manner. There were a statistically significant greater number of students who adopted a deep approach toward learning at the commencement of the academic year. Students showed a trend toward an increase in their intrinsic interest in the learning material as the module progressed. Students in the Applied Physiotherapy module (ATP started to shift their focus from a surface learning approach to a deep learning approach. further research is needed to determine the long-term changes in approach toward learning and the possible determinants of these changes. This can be done in conjunction with the implementation of quality assurance mechanisms for learning material and earlier preparation of students for the change in the learning environment.

  8. Using Machine Learning in Adversarial Environments.

    Energy Technology Data Exchange (ETDEWEB)

    Davis, Warren Leon [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2016-02-01

    Intrusion/anomaly detection systems are among the first lines of cyber defense. Commonly, they either use signatures or machine learning (ML) to identify threats, but fail to account for sophisticated attackers trying to circumvent them. We propose to embed machine learning within a game theoretic framework that performs adversarial modeling, develops methods for optimizing operational response based on ML, and integrates the resulting optimization codebase into the existing ML infrastructure developed by the Hybrid LDRD. Our approach addresses three key shortcomings of ML in adversarial settings: 1) resulting classifiers are typically deterministic and, therefore, easy to reverse engineer; 2) ML approaches only address the prediction problem, but do not prescribe how one should operationalize predictions, nor account for operational costs and constraints; and 3) ML approaches do not model attackers’ response and can be circumvented by sophisticated adversaries. The principal novelty of our approach is to construct an optimization framework that blends ML, operational considerations, and a model predicting attackers reaction, with the goal of computing optimal moving target defense. One important challenge is to construct a realistic model of an adversary that is tractable, yet realistic. We aim to advance the science of attacker modeling by considering game-theoretic methods, and by engaging experimental subjects with red teaming experience in trying to actively circumvent an intrusion detection system, and learning a predictive model of such circumvention activities. In addition, we will generate metrics to test that a particular model of an adversary is consistent with available data.

  9. Improving orbit prediction accuracy through supervised machine learning

    Science.gov (United States)

    Peng, Hao; Bai, Xiaoli

    2018-05-01

    Due to the lack of information such as the space environment condition and resident space objects' (RSOs') body characteristics, current orbit predictions that are solely grounded on physics-based models may fail to achieve required accuracy for collision avoidance and have led to satellite collisions already. This paper presents a methodology to predict RSOs' trajectories with higher accuracy than that of the current methods. Inspired by the machine learning (ML) theory through which the models are learned based on large amounts of observed data and the prediction is conducted without explicitly modeling space objects and space environment, the proposed ML approach integrates physics-based orbit prediction algorithms with a learning-based process that focuses on reducing the prediction errors. Using a simulation-based space catalog environment as the test bed, the paper demonstrates three types of generalization capability for the proposed ML approach: (1) the ML model can be used to improve the same RSO's orbit information that is not available during the learning process but shares the same time interval as the training data; (2) the ML model can be used to improve predictions of the same RSO at future epochs; and (3) the ML model based on a RSO can be applied to other RSOs that share some common features.

  10. Machine learning for epigenetics and future medical applications

    OpenAIRE

    Holder, Lawrence B.; Haque, M. Muksitul; Skinner, Michael K.

    2017-01-01

    ABSTRACT Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems w...

  11. Interactive machine learning for health informatics: when do we need the human-in-the-loop?

    Science.gov (United States)

    Holzinger, Andreas

    2016-06-01

    Machine learning (ML) is the fastest growing field in computer science, and health informatics is among the greatest challenges. The goal of ML is to develop algorithms which can learn and improve over time and can be used for predictions. Most ML researchers concentrate on automatic machine learning (aML), where great advances have been made, for example, in speech recognition, recommender systems, or autonomous vehicles. Automatic approaches greatly benefit from big data with many training sets. However, in the health domain, sometimes we are confronted with a small number of data sets or rare events, where aML-approaches suffer of insufficient training samples. Here interactive machine learning (iML) may be of help, having its roots in reinforcement learning, preference learning, and active learning. The term iML is not yet well used, so we define it as "algorithms that can interact with agents and can optimize their learning behavior through these interactions, where the agents can also be human." This "human-in-the-loop" can be beneficial in solving computationally hard problems, e.g., subspace clustering, protein folding, or k-anonymization of health data, where human expertise can help to reduce an exponential search space through heuristic selection of samples. Therefore, what would otherwise be an NP-hard problem, reduces greatly in complexity through the input and the assistance of a human agent involved in the learning phase.

  12. Overview of deep learning in medical imaging.

    Science.gov (United States)

    Suzuki, Kenji

    2017-09-01

    The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification. Since then, researchers in virtually all fields, including medical imaging, have started actively participating in the explosively growing field of deep learning. In this paper, the area of deep learning in medical imaging is overviewed, including (1) what was changed in machine learning before and after the introduction of deep learning, (2) what is the source of the power of deep learning, (3) two major deep-learning models: a massive-training artificial neural network (MTANN) and a convolutional neural network (CNN), (4) similarities and differences between the two models, and (5) their applications to medical imaging. This review shows that ML with feature input (or feature-based ML) was dominant before the introduction of deep learning, and that the major and essential difference between ML before and after deep learning is the learning of image data directly without object segmentation or feature extraction; thus, it is the source of the power of deep learning, although the depth of the model is an important attribute. The class of ML with image input (or image-based ML) including deep learning has a long history, but recently gained popularity due to the use of the new terminology, deep learning. There are two major models in this class of ML in medical imaging, MTANN and CNN, which have similarities as well as several differences. In our experience, MTANNs were substantially more efficient in their development, had a higher performance, and required a

  13. Challenges in the Verification of Reinforcement Learning Algorithms

    Science.gov (United States)

    Van Wesel, Perry; Goodloe, Alwyn E.

    2017-01-01

    Machine learning (ML) is increasingly being applied to a wide array of domains from search engines to autonomous vehicles. These algorithms, however, are notoriously complex and hard to verify. This work looks at the assumptions underlying machine learning algorithms as well as some of the challenges in trying to verify ML algorithms. Furthermore, we focus on the specific challenges of verifying reinforcement learning algorithms. These are highlighted using a specific example. Ultimately, we do not offer a solution to the complex problem of ML verification, but point out possible approaches for verification and interesting research opportunities.

  14. In the business of learning : approaches to learning of undergraduate students in business

    NARCIS (Netherlands)

    Hooijer, J.G.

    2010-01-01

    Three approaches to learning are distinguished in the learning literature: a surface, deep and strategic approach to learning. The surface approach to learning is characterized as undirected rote learning, motivated by a fear of failure. The deep approach to learning is characterized as interested

  15. Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective

    International Nuclear Information System (INIS)

    Kang, John; Schwartz, Russell; Flickinger, John; Beriwal, Sushil

    2015-01-01

    Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both prognostic and therapeutic purposes has exploded thanks to increasing availability of electronic data and genomics. One promising direction that medical modeling is moving toward is adopting the same machine learning methods used by companies such as Google and Facebook to combat disease. Broadly defined, machine learning is a branch of computer science that deals with making predictions from complex data through statistical models. These methods serve to uncover patterns in data and are actively used in areas such as speech recognition, handwriting recognition, face recognition, “spam” filtering (junk email), and targeted advertising. Although multiple radiation oncology research groups have shown the value of applied machine learning (ML), clinical adoption has been slow due to the high barrier to understanding these complex models by clinicians. Here, we present a review of the use of ML to predict radiation therapy outcomes from the clinician's point of view with the hope that it lowers the “barrier to entry” for those without formal training in ML. We begin by describing 7 principles that one should consider when evaluating (or creating) an ML model in radiation oncology. We next introduce 3 popular ML methods—logistic regression (LR), support vector machine (SVM), and artificial neural network (ANN)—and critique 3 seminal papers in the context of these principles. Although current studies are in exploratory stages, the overall methodology has progressively matured, and the field is ready for larger-scale further investigation.

  16. qcML

    DEFF Research Database (Denmark)

    Walzer, Mathias; Pernas, Lucia Espona; Nasso, Sara

    2014-01-01

    provide tools for the calculation of a wide range of quality metrics as well as a database format and interconversion tools, so that existing LIMS systems can easily add relational storage of the quality control data to their existing schema. We here describe the qcML specification, along with possible...... use cases and an illustrative example of the subsequent analysis possibilities. All information about qcML is available at http://code.google.com/p/qcml....

  17. ML Confidential : machine learning on encrypted data

    NARCIS (Netherlands)

    Graepel, T.; Lauter, K.; Naehrig, M.; Kwon, T.; Lee, M.-K.; Kwon, D.

    2013-01-01

    We demonstrate that, by using a recently proposed leveled homomorphic encryption scheme, it is possible to delegate the execution of a machine learning algorithm to a computing service while retaining con¿dentiality of the training and test data. Since the computational complexity of the homomorphic

  18. Less is more: Sampling chemical space with active learning

    Science.gov (United States)

    Smith, Justin S.; Nebgen, Ben; Lubbers, Nicholas; Isayev, Olexandr; Roitberg, Adrian E.

    2018-06-01

    The development of accurate and transferable machine learning (ML) potentials for predicting molecular energetics is a challenging task. The process of data generation to train such ML potentials is a task neither well understood nor researched in detail. In this work, we present a fully automated approach for the generation of datasets with the intent of training universal ML potentials. It is based on the concept of active learning (AL) via Query by Committee (QBC), which uses the disagreement between an ensemble of ML potentials to infer the reliability of the ensemble's prediction. QBC allows the presented AL algorithm to automatically sample regions of chemical space where the ML potential fails to accurately predict the potential energy. AL improves the overall fitness of ANAKIN-ME (ANI) deep learning potentials in rigorous test cases by mitigating human biases in deciding what new training data to use. AL also reduces the training set size to a fraction of the data required when using naive random sampling techniques. To provide validation of our AL approach, we develop the COmprehensive Machine-learning Potential (COMP6) benchmark (publicly available on GitHub) which contains a diverse set of organic molecules. Active learning-based ANI potentials outperform the original random sampled ANI-1 potential with only 10% of the data, while the final active learning-based model vastly outperforms ANI-1 on the COMP6 benchmark after training to only 25% of the data. Finally, we show that our proposed AL technique develops a universal ANI potential (ANI-1x) that provides accurate energy and force predictions on the entire COMP6 benchmark. This universal ML potential achieves a level of accuracy on par with the best ML potentials for single molecules or materials, while remaining applicable to the general class of organic molecules composed of the elements CHNO.

  19. Exploration of Machine Learning Approaches to Predict Pavement Performance

    Science.gov (United States)

    2018-03-23

    Machine learning (ML) techniques were used to model and predict pavement condition index (PCI) for various pavement types using a variety of input variables. The primary objective of this research was to develop and assess PCI predictive models for t...

  20. Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective.

    Science.gov (United States)

    Kang, John; Schwartz, Russell; Flickinger, John; Beriwal, Sushil

    2015-12-01

    Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both prognostic and therapeutic purposes has exploded thanks to increasing availability of electronic data and genomics. One promising direction that medical modeling is moving toward is adopting the same machine learning methods used by companies such as Google and Facebook to combat disease. Broadly defined, machine learning is a branch of computer science that deals with making predictions from complex data through statistical models. These methods serve to uncover patterns in data and are actively used in areas such as speech recognition, handwriting recognition, face recognition, "spam" filtering (junk email), and targeted advertising. Although multiple radiation oncology research groups have shown the value of applied machine learning (ML), clinical adoption has been slow due to the high barrier to understanding these complex models by clinicians. Here, we present a review of the use of ML to predict radiation therapy outcomes from the clinician's point of view with the hope that it lowers the "barrier to entry" for those without formal training in ML. We begin by describing 7 principles that one should consider when evaluating (or creating) an ML model in radiation oncology. We next introduce 3 popular ML methods--logistic regression (LR), support vector machine (SVM), and artificial neural network (ANN)--and critique 3 seminal papers in the context of these principles. Although current studies are in exploratory stages, the overall methodology has progressively matured, and the field is ready for larger-scale further investigation. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Study strategies and approaches to learning

    DEFF Research Database (Denmark)

    Christensen, Hans Peter

    Process Questionnaire to identify their approach to learning. It was hypothesised that the students’ learning approach would depend more on the quality of the study work than on the quantity; that an active and reflective study strategy was required to obtain deep conceptual understanding. The result...... showed a weak correlation between the student’s main learning approach as defined by the ratio of the deep approach score to the surface approach score and the student’s study intensity as identified by the ratio of non-scheduled independent activities to scheduled teacher-controlled activities....... There was however a much stronger linear correlation (significant at the 0.01 level) between the deep-surface ratio and the total study load. The same result was observed when measuring other students’ study strategy and learning approach for a single course. The empirical basis is still too limited to draw...

  2. Does the acceptance of hybrid learning affect learning approaches in France?

    Science.gov (United States)

    Marco, Lionel Di; Venot, Alain; Gillois, Pierre

    2017-01-01

    Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (Paffected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.

  3. Linking Action Learning and Inter-Organisational Learning: The Learning Journey Approach

    Science.gov (United States)

    Schumacher, Thomas

    2015-01-01

    The article presents and illustrates the learning journey (LJ)--a new management development approach to inter-organisational learning based on observation, reflection and problem-solving. The LJ involves managers from different organisations and applies key concepts of action learning and systemic organisational development. Made up of…

  4. Contextual Approach with Guided Discovery Learning and Brain Based Learning in Geometry Learning

    Science.gov (United States)

    Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi

    2017-09-01

    The aim of this study was to combine the contextual approach with Guided Discovery Learning (GDL) and Brain Based Learning (BBL) in geometry learning of junior high school. Furthermore, this study analysed the effect of contextual approach with GDL and BBL in geometry learning. GDL-contextual and BBL-contextual was built from the steps of GDL and BBL that combined with the principles of contextual approach. To validate the models, it uses quasi experiment which used two experiment groups. The sample had been chosen by stratified cluster random sampling. The sample was 150 students of grade 8th in junior high school. The data were collected through the student’s mathematics achievement test that given after the treatment of each group. The data analysed by using one way ANOVA with different cell. The result shows that GDL-contextual has not different effect than BBL-contextual on mathematics achievement in geometry learning. It means both the two models could be used in mathematics learning as the innovative way in geometry learning.

  5. Learning styles and approaches to learning among medical undergraduates and postgraduates.

    Science.gov (United States)

    Samarakoon, Lasitha; Fernando, Tharanga; Rodrigo, Chaturaka

    2013-03-25

    The challenge of imparting a large amount of knowledge within a limited time period in a way it is retained, remembered and effectively interpreted by a student is considerable. This has resulted in crucial changes in the field of medical education, with a shift from didactic teacher centered and subject based teaching to the use of interactive, problem based, student centered learning. This study tested the hypothesis that learning styles (visual, auditory, read/write and kinesthetic) and approaches to learning (deep, strategic and superficial) differ among first and final year undergraduate medical students, and postgraduates medical trainees. We used self administered VARK and ASSIST questionnaires to assess the differences in learning styles and approaches to learning among medical undergraduates of the University of Colombo and postgraduate trainees of the Postgraduate Institute of Medicine, Colombo. A total of 147 participated: 73 (49.7%) first year students, 40 (27.2%) final year students and 34(23.1%) postgraduate students. The majority (69.9%) of first year students had multimodal learning styles. Among final year students, the majority (67.5%) had multimodal learning styles, and among postgraduates, the majority were unimodal (52.9%) learners.Among all three groups, the predominant approach to learning was strategic. Postgraduates had significant higher mean scores for deep and strategic approaches than first years or final years (p learning approaches suggest a positive shift towards deep and strategic learning in postgraduate students. However a similar difference was not observed in undergraduate students from first year to final year, suggesting that their curriculum may not have influenced learning methodology over a five year period.

  6. Toward a Social Approach to Learning in Community Service Learning

    Science.gov (United States)

    Cooks, Leda; Scharrer, Erica; Paredes, Mari Castaneda

    2004-01-01

    The authors describe a social approach to learning in community service learning that extends the contributions of three theoretical bodies of scholarship on learning: social constructionism, critical pedagogy, and community service learning. Building on the assumptions about learning described in each of these areas, engagement, identity, and…

  7. Approaches to Learning and Kolb's Learning Styles of Undergraduates with Better Grades

    Science.gov (United States)

    Almeida, Patrícia; Teixeira-Dias, José Joaquim; Martinho, Mariana; Balasooriya, Chinthaka

    The purpose of this study is to investigate if the teaching, learning and assessment strategies conceived and implemented in a higher education chemistry course promote the development of conceptual understanding, as intended. Thus, our aim is to analyse the learning styles and the approaches to learning of chemistry undergraduates with better grades. The overall results show that the students with better grades possess the assimilator learning style, that is usually associated to the archetypal chemist. Moreover, the students with the highest grades revealed a conception of learning emphasising understanding. However, these students diverged both in their learning approaches and in their preferences for teaching strategies. The majority of students adopted a deep approach or a combination of a deep and a strategic approach, but half of them revealed their preference for teaching-centred strategies.

  8. Implementation of a Goal-Based Systems Engineering Process Using the Systems Modeling Language (SysML)

    Science.gov (United States)

    Breckenridge, Jonathan T.; Johnson, Stephen B.

    2013-01-01

    Building upon the purpose, theoretical approach, and use of a Goal-Function Tree (GFT) being presented by Dr. Stephen B. Johnson, described in a related Infotech 2013 ISHM abstract titled "Goal-Function Tree Modeling for Systems Engineering and Fault Management", this paper will describe the core framework used to implement the GFTbased systems engineering process using the Systems Modeling Language (SysML). These two papers are ideally accepted and presented together in the same Infotech session. Statement of problem: SysML, as a tool, is currently not capable of implementing the theoretical approach described within the "Goal-Function Tree Modeling for Systems Engineering and Fault Management" paper cited above. More generally, SysML's current capabilities to model functional decompositions in the rigorous manner required in the GFT approach are limited. The GFT is a new Model-Based Systems Engineering (MBSE) approach to the development of goals and requirements, functions, and its linkage to design. As a growing standard for systems engineering, it is important to develop methods to implement GFT in SysML. Proposed Method of Solution: Many of the central concepts of the SysML language are needed to implement a GFT for large complex systems. In the implementation of those central concepts, the following will be described in detail: changes to the nominal SysML process, model view definitions and examples, diagram definitions and examples, and detailed SysML construct and stereotype definitions.

  9. White cell labeling: 20 ML VS 4 ML of blood volume-case reports

    International Nuclear Information System (INIS)

    Imam, S.K.

    1998-01-01

    Full text: Some times, it becomes difficult to draw 20 mL blood from a patient with bad veins. On two occasions, we could collect only about 4 mL of blood, that too with a great deal of struggle, and then we carried out the routine labelling procedure. A labelling efficiency of 98.2% and 95.6% was achieved. The white cell scan was negative in one patient, but positive in the next one. In a third patient, a comparison of labelling efficiency was done between 5 and 20 mLs of blood volumes separately and the results were found to be identical, 98.5% and 98.4%, respectively. As we have achieved the usual pattern of white cell scan with as low as 4-5 mL of blood, it appears that enough number of white cells is present even in the 4-5 mL of blood that is capable of generating a white cell scan and so, it seems rational to reduce the blood volume from 20 mL to 4 or 5 mL. However, further studies are warranted before adopting this modification. The procedure appears to carry the following advantages: ease of blood collection, handling and re-injection and less risk to the patient

  10. Assessing Approaches to Learning in School Readiness

    Directory of Open Access Journals (Sweden)

    Otilia C. Barbu

    2015-07-01

    Full Text Available This study examines the psychometric properties of two assessments of children’s approaches to learning: the Devereux Early Childhood Assessment (DECA and a 13-item approaches to learning rating scale (AtL derived from the Arizona Early Learning Standards (AELS. First, we administered questionnaires to 1,145 randomly selected parents/guardians of first-time kindergarteners. Second, we employed confirmatory factor analysis (CFA with parceling for DECA to reduce errors due to item specificity and prevent convergence difficulties when simultaneously estimating DECA and AtL models. Results indicated an overlap of 55% to 72% variance between the domains of the two instruments and suggested that the new AtL instrument is an easily administered alternative to the DECA for measuring children’s approaches to learning. This is one of the first studies that investigated DECA’s approaches to learning dimension and explored the measurement properties of an instrument purposely derived from a state’s early learning guidelines.

  11. Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective

    Energy Technology Data Exchange (ETDEWEB)

    Kang, John [Medical Scientist Training Program, University of Pittsburgh-Carnegie Mellon University, Pittsburgh, Pennsylvania (United States); Schwartz, Russell [Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania (United States); Flickinger, John [Departments of Radiation Oncology and Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (United States); Beriwal, Sushil, E-mail: beriwals@upmc.edu [Department of Radiation Oncology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (United States)

    2015-12-01

    Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both prognostic and therapeutic purposes has exploded thanks to increasing availability of electronic data and genomics. One promising direction that medical modeling is moving toward is adopting the same machine learning methods used by companies such as Google and Facebook to combat disease. Broadly defined, machine learning is a branch of computer science that deals with making predictions from complex data through statistical models. These methods serve to uncover patterns in data and are actively used in areas such as speech recognition, handwriting recognition, face recognition, “spam” filtering (junk email), and targeted advertising. Although multiple radiation oncology research groups have shown the value of applied machine learning (ML), clinical adoption has been slow due to the high barrier to understanding these complex models by clinicians. Here, we present a review of the use of ML to predict radiation therapy outcomes from the clinician's point of view with the hope that it lowers the “barrier to entry” for those without formal training in ML. We begin by describing 7 principles that one should consider when evaluating (or creating) an ML model in radiation oncology. We next introduce 3 popular ML methods—logistic regression (LR), support vector machine (SVM), and artificial neural network (ANN)—and critique 3 seminal papers in the context of these principles. Although current studies are in exploratory stages, the overall methodology has progressively matured, and the field is ready for larger-scale further investigation.

  12. Learners for life : student approaches to learning

    NARCIS (Netherlands)

    Artelt, Cordula; Baumert, Jürgen; Julius-McElvany, Nele; Peschar, Jules

    2003-01-01

    What are students like as learners as they approach the end of compulsory education? The answer matters greatly, not only because those with stronger approaches to learning get better results at school but also because young adults able to set learning goals and manage their own learning are much

  13. Cooperative learning as an approach to pedagogy.

    Science.gov (United States)

    Nolinske, T; Millis, B

    1999-01-01

    Lecture-based pedagogical approaches cannot adequately prepare students in professional and technical occupational therapy programs. Faculty members in other disciplines are turning to a well-known and well-researched teaching approach called cooperative learning, which is more carefully structured and defined than most other forms of small group learning. Cooperative learning includes several key principles: positive interdependence, individual responsibility, appropriate grouping, group maintenance, cooperative skills, and promotive (interaction) time. This article provides ideas for managing the classroom with cooperative learning activities and describes eight of them: Three-Step Interview, Roundtable, Think-Pair-Share, Structured Problem Solving, Send/Pass-a-Problem, Generic Question Stems, Double Entry Journal, and Dyadic Essay Confrontation. Each activity is applied to content embedded in professional and technical occupational therapy curricula. A cooperative learning approach to evaluating learning is also presented.

  14. The High Scope Approach To Early Learning

    OpenAIRE

    French, Geraldine

    2012-01-01

    Learning Objectives: After studying this chapter the reader should be able to: • Describe the historical origins, the longitudinal research, and the theoretical underpinnings of the HighScope approach. • Identify the teaching strategies adopted by HighScope educators. • Appreciate the curriculum content. • Understand the HighScope approach to the assessment of children’s learning. • Consider some criticisms of the HighScope research and approach to early learning. This ...

  15. The jmzQuantML programming interface and validator for the mzQuantML data standard.

    Science.gov (United States)

    Qi, Da; Krishna, Ritesh; Jones, Andrew R

    2014-03-01

    The mzQuantML standard from the HUPO Proteomics Standards Initiative has recently been released, capturing quantitative data about peptides and proteins, following analysis of MS data. We present a Java application programming interface (API) for mzQuantML called jmzQuantML. The API provides robust bridges between Java classes and elements in mzQuantML files and allows random access to any part of the file. The API provides read and write capabilities, and is designed to be embedded in other software packages, enabling mzQuantML support to be added to proteomics software tools (http://code.google.com/p/jmzquantml/). The mzQuantML standard is designed around a multilevel validation system to ensure that files are structurally and semantically correct for different proteomics quantitative techniques. In this article, we also describe a Java software tool (http://code.google.com/p/mzquantml-validator/) for validating mzQuantML files, which is a formal part of the data standard. © 2014 The Authors. Proteomics published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Accounting Student's Learning Approaches And Impact On Academic Performance

    OpenAIRE

    Ismail, Suhaiza

    2009-01-01

    The objective of the study is threefold. Firstly, the study explores the learning approaches adopted by students in completing their Business Finance. Secondly, it examines the impact that learning approaches has on the student's academic performance. Finally, the study considers gender differences in the learning approaches adopted by students and in the relationship between learning approaches and academic performance. The Approaches and Study Skills Inventory for Students (ASSIST) was used...

  17. WaterML: an XML Language for Communicating Water Observations Data

    Science.gov (United States)

    Maidment, D. R.; Zaslavsky, I.; Valentine, D.

    2007-12-01

    One of the great impediments to the synthesis of water information is the plethora of formats used to publish such data. Each water agency uses its own approach. XML (eXtended Markup Languages) are generalizations of Hypertext Markup Language to communicate specific kinds of information via the internet. WaterML is an XML language for water observations data - streamflow, water quality, groundwater levels, climate, precipitation and aquatic biology data, recorded at fixed, point locations as a function of time. The Hydrologic Information System project of the Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI) has defined WaterML and prepared a set of web service functions called WaterOneFLow that use WaterML to provide information about observation sites, the variables measured there and the values of those measurments. WaterML has been submitted to the Open GIS Consortium for harmonization with its standards for XML languages. Academic investigators at a number of testbed locations in the WATERS network are providing data in WaterML format using WaterOneFlow web services. The USGS and other federal agencies are also working with CUAHSI to similarly provide access to their data in WaterML through WaterOneFlow services.

  18. Machine learning for adaptive many-core machines a practical approach

    CERN Document Server

    Lopes, Noel

    2015-01-01

    The overwhelming data produced everyday and the increasing performance and cost requirements of applications?are transversal to a wide range of activities in society, from science to industry. In particular, the magnitude and complexity of the tasks that Machine Learning (ML) algorithms have to solve are driving the need to devise adaptive many-core machines that scale well with the volume of data, or in other words, can handle Big Data.This book gives a concise view on how to extend the applicability of well-known ML algorithms in Graphics Processing Unit (GPU) with data scalability in mind.

  19. jmzML, an open-source Java API for mzML, the PSI standard for MS data.

    Science.gov (United States)

    Côté, Richard G; Reisinger, Florian; Martens, Lennart

    2010-04-01

    We here present jmzML, a Java API for the Proteomics Standards Initiative mzML data standard. Based on the Java Architecture for XML Binding and XPath-based XML indexer random-access XML parser, jmzML can handle arbitrarily large files in minimal memory, allowing easy and efficient processing of mzML files using the Java programming language. jmzML also automatically resolves internal XML references on-the-fly. The library (which includes a viewer) can be downloaded from http://jmzml.googlecode.com.

  20. Relations between blended learning possibilities and teachers' approaches to blended learning

    DEFF Research Database (Denmark)

    Stenalt, Maria Hvid; Nielsen, Tobias Alsted; Bager-Elsborg, Anna

    Higher Education has embraced blended learning as a way of enhancing quality in teaching and helping students to learn. This presentation addresses relations between blended learning possiblities presented to teachers in a teacher training project and teachers’ approaches to blended learning. We...... suggest that in order to identify the level of impact of integrating technologies in teaching and learning, we need to understand the factors influencing approaches to design of courses for blended contexts. Participants in the teacher training project come from the Department of Law at Aarhus University......: • Optain locally-embedded knowledge about blended learning • Develop opportunities for law students to receive (more) feedback • Comply with strategic aims The results so far suggest that teachers provide a disciplinary perspective on the key dimensions of blended learning, which influences...

  1. Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.

    Science.gov (United States)

    Li, Xin; Bai, Yanqin; Peng, Yaxin; Du, Shaoyi; Ying, Shihui

    2018-03-01

    Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best nonlinear metric for the data. First, we describe the nonlinear metric by the multiple kernel representation. By this approach, we project the data into a high dimensional space, where the data can be well represented by linear ML. Then, we reformulate the linear ML by a minimization problem on the positive definite matrix group. Finally, we develop a two-step algorithm for solving this model and design an intrinsic steepest descent algorithm to learn the positive definite metric matrix. Experimental results validate that our proposed method is effective and outperforms several state-of-the-art ML methods.

  2. Learning Process Questionnaire Manual. Student Approaches to Learning and Studying.

    Science.gov (United States)

    Biggs, John B.

    This manual describes the theory behind the Learning Process Questionnaire (LPQ) used in Australia and defines what the subscale and scale scores mean. The LPQ is a 36-item self-report questionnaire that yields scores on three basic motives for learning and three learning strategies, and on the approaches to learning that are formed by these…

  3. ENVIRONMENTAL LEARNING APPROACHES IN IMPROVING LEARNING OUTCOMES IN ACID-BASE SUBJECT

    Directory of Open Access Journals (Sweden)

    Rachmat Sahputra

    2016-03-01

    Full Text Available Learning in the understanding of acid-base chemistry in schools needs to be improved so research to determine differences in learning outcomes between students taught using environmental approaches and methods lectures in class XI SMA on acid-base subject needs to be done. In this study, using a quasi-experimental method using a data collection tool achievement test essay form. The test statistic results of the post-test learning has been obtained Asymp value. Sig (2-tailed 0,026 that showed the differences between students' learning outcomes with a control experimental class with effect size of 0.63 or much influence difference with the percentage 23.57% which indicated that the learning environment approach can improve learning outcomes of high school students.

  4. Evoked prior learning experience and approach to learning as predictors of academic achievement.

    Science.gov (United States)

    Trigwell, Keith; Ashwin, Paul; Millan, Elena S

    2013-09-01

    In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students' perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. To investigate how students' evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. A 77-item questionnaire was used to gather students' self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was

  5. ML-o-Scope: A Diagnostic Visualization System for Deep Machine Learning Pipelines

    Science.gov (United States)

    2014-05-16

    Huawei , Intel, Microsoft, NetApp, Pivotal, Splunk, Virdata, VMware, WANdisco and Yahoo!. ML-o-scope: a diagnostic visualization system for deep machine...Facebook, GameOnTalis, Guavus, HP, Huawei , Intel, Microsoft, NetApp, Pivotal, Splunk, Virdata, VMware, WANdisco and Yahoo!. References [1] Bruna, J., and

  6. Validation by theoretical approach to the experimental estimation of efficiency for gamma spectrometry of gas in 100 ml standard flask

    International Nuclear Information System (INIS)

    Mohan, V.; Chudalayandi, K.; Sundaram, M.; Krishnamony, S.

    1996-01-01

    Estimation of gaseous activity forms an important component of air monitoring at Madras Atomic Power Station (MAPS). The gases of importance are argon 41 an air activation product and fission product noble gas xenon 133. For estimating the concentration, the experimental method is used in which a grab sample is collected in a 100 ml volumetric standard flask. The activity of gas is then computed by gamma spectrometry using a predetermined efficiency estimated experimentally. An attempt is made using theoretical approach to validate the experimental method of efficiency estimation. Two analytical models named relative flux model and absolute activity model were developed independently of each other. Attention is focussed on the efficiencies for 41 Ar and 133 Xe. Results show that the present method of sampling and analysis using 100 ml volumetric flask is adequate and acceptable. (author). 5 refs., 2 tabs

  7. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach

    Directory of Open Access Journals (Sweden)

    Niu AQ

    2016-07-01

    Full Text Available Ai-qin Niu,1 Liang-jun Xie,2 Hui Wang,1 Bing Zhu,1 Sheng-qi Wang3 1Department of Gynecology, the First People’s Hospital of Shangqiu, Shangqiu, Henan, People’s Republic of China; 2Department of Image Diagnoses, the Third Hospital of Jinan, Jinan, Shandong, People’s Republic of China; 3Department of Mammary Disease, Guangdong Provincial Hospital of Chinese Medicine, the Second Clinical College of Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China Background: Estrogen receptors (ERs are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Methods: Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML methods. Results: The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior

  8. Machine learning an artificial intelligence approach

    CERN Document Server

    Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer

    1983-01-01

    Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a

  9. A Janus-Faced Approach to Learning. A Critical Discussion of Habermas' Pragmatic Approach

    Science.gov (United States)

    Italia, Salvatore

    2017-01-01

    A realist approach to learning is what I propose here. This is based on a non-epistemic dimension whose presence is a necessary assumption for a concept of learning of a life-world as complementary to learning within a life-world. I develop my approach in opposition to Jürgen Habermas' pragmatic approach, which seems to lack of something from a…

  10. Dialogical, Enquiry and Participatory Approaches to Learning

    DEFF Research Database (Denmark)

    Hurford, Donna; Rowley, Chris

    2018-01-01

    Dialogical enquiry and participatory approaches This chapter is concerned with approaches to leading children into active participation and enquiry, through involvement in their own learning, both at Key Stages 1 and 2. The terms ‘enquiry’, ‘learning’ and ‘active participation’ are closely related....... We link these approaches to dialogue and discussion because these aspects of learning are often dealt with separately in the literature and yet clearly they are a form of enquiry and participatory learning. We draw upon a range of literature and research in order to justify these approaches and we...... Years (REPEY) Project (Siraj-Blatchford et al. 2002). This project found that the most effective strategies and techniques for promoting learning in the early years involved adult–child interactions in which the adult responds to the child’s understanding of a subject or activity, the child responds...

  11. Heutagogy: An alternative practice based learning approach.

    Science.gov (United States)

    Bhoyrub, John; Hurley, John; Neilson, Gavin R; Ramsay, Mike; Smith, Margaret

    2010-11-01

    Education has explored and utilised multiple approaches in attempts to enhance the learning and teaching opportunities available to adult learners. Traditional pedagogy has been both directly and indirectly affected by andragogy and transformational learning, consequently widening our understandings and approaches toward view teaching and learning. Within the context of nurse education, a major challenge has been to effectively apply these educational approaches to the complex, unpredictable and challenging environment of practice based learning. While not offered as a panacea to such challenges, heutagogy is offered in this discussion paper as an emerging and potentially highly congruent educational framework to place around practice based learning. Being an emergent theory its known conceptual underpinnings and possible applications to nurse education need to be explored and theoretically applied. Through placing the adult learner at the foreground of grasping learning opportunities as they unpredictability emerge from a sometimes chaotic environment, heutagogy can be argued as offering the potential to minimise many of the well published difficulties of coordinating practice with faculty teaching and learning. Copyright © 2010 Elsevier Ltd. All rights reserved.

  12. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach.

    Science.gov (United States)

    Niu, Ai-Qin; Xie, Liang-Jun; Wang, Hui; Zhu, Bing; Wang, Sheng-Qi

    2016-01-01

    Estrogen receptors (ERs) are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML) methods. The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic) curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior for the classification of selective ER-β agonists. Chemistry Development Kit extended fingerprints and MACCS fingerprint performed better in structural representation between active and inactive agonists. These results demonstrate that combining the fingerprint and ML approaches leads to robust ER-β agonist prediction models, which are potentially applicable to the identification of selective ER-β agonists.

  13. E-Learning Systems, Environments and Approaches

    OpenAIRE

    Isaias, P.; Spector, J.M.; Ifenthaler, D.; Sampson, D.G.

    2015-01-01

    The volume consists of twenty-five chapters selected from among peer-reviewed papers presented at the CELDA (Cognition and Exploratory Learning in the Digital Age) 2013 Conference held in Fort Worth, Texas, USA, in October 2013 and also from world class scholars in e-learning systems, environments and approaches. The following sub-topics are included: Exploratory Learning Technologies (Part I), e-Learning social web design (Part II), Learner communities through e-Learning implementations (Par...

  14. Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning.

    Directory of Open Access Journals (Sweden)

    Kristoffer Carl Aberg

    Full Text Available Learning how to gain rewards (approach learning and avoid punishments (avoidance learning is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance learning scored higher on measures of approach (vs. avoidance trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits.

  15. Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning

    Science.gov (United States)

    Carl Aberg, Kristoffer; Doell, Kimberly C.; Schwartz, Sophie

    2016-01-01

    Learning how to gain rewards (approach learning) and avoid punishments (avoidance learning) is fundamental for everyday life. While individual differences in approach and avoidance learning styles have been related to genetics and aging, the contribution of personality factors, such as traits, remains undetermined. Moreover, little is known about the computational mechanisms mediating differences in learning styles. Here, we used a probabilistic selection task with positive and negative feedbacks, in combination with computational modelling, to show that individuals displaying better approach (vs. avoidance) learning scored higher on measures of approach (vs. avoidance) trait motivation, but, paradoxically, also displayed reduced learning speed following positive (vs. negative) outcomes. These data suggest that learning different types of information depend on associated reward values and internal motivational drives, possibly determined by personality traits. PMID:27851807

  16. Investigative Primary Science: A Problem-Based Learning Approach

    Science.gov (United States)

    Etherington, Matthew B.

    2011-01-01

    This study reports on the success of using a problem-based learning approach (PBL) as a pedagogical mode of learning open inquiry science within a traditional four-year undergraduate elementary teacher education program. In 2010, a problem-based learning approach to teaching primary science replaced the traditional content driven syllabus. During…

  17. ACCOUNTING STUDENT’S LEARNING APPROACHES AND IMPACT ON ACADEMIC PERFORMANCE

    Directory of Open Access Journals (Sweden)

    Suhaiza Ismail

    2009-12-01

    Full Text Available The objective of the study is threefold. Firstly, the study explores the learning approaches adopted by students in completing their Business Finance. Secondly, it examines the impact that learning approaches has on the student’s academic performance. Finally, the study considers gender differences in the learning approaches adopted by students and in the relationship between learning approaches and academic performance. The Approaches and Study Skills Inventory for Students (ASSIST was used to assess the approaches to learning adopted by students whilst the students final examination result was considered in examining the performance of the students. The results indicate that majority of the accounting students, both male andfemale groups prefer to use the deep approach in studying Business Finance. The findings also reveal that there were significant relationships between learning approaches and academic performance with positive direction appears for deep and strategic approaches whilst negative relationship reveals for surface approach.

  18. ACCOUNTING STUDENT’S LEARNING APPROACHES AND IMPACT ON ACADEMIC PERFORMANCE

    OpenAIRE

    Suhaiza Ismail

    2009-01-01

    The objective of the study is threefold. Firstly, the study explores the learning approaches adopted by students in completing their Business Finance. Secondly, it examines the impact that learning approaches has on the student’s academic performance. Finally, the study considers gender differences in the learning approaches adopted by students and in the relationship between learning approaches and academic performance. The Approaches and Study Skills Inventory for Students (ASSIST) was used...

  19. The scientific learning approach using multimedia-based maze game to improve learning outcomes

    Science.gov (United States)

    Setiawan, Wawan; Hafitriani, Sarah; Prabawa, Harsa Wara

    2016-02-01

    The objective of curriculum 2013 is to improve the quality of education in Indonesia, which leads to improving the quality of learning. The scientific approach and supported empowerment media is one approach as massaged of curriculum 2013. This research aims to design a labyrinth game based multimedia and apply in the scientific learning approach. This study was conducted in one of the Vocational School in Subjects of Computer Network on 2 (two) classes of experimental and control. The method used Mix Method Research (MMR) which combines qualitative in multimedia design, and quantitative in the study of learning impact. The results of a survey showed that the general of vocational students like of network topology material (68%), like multimedia (74%), and in particular, like interactive multimedia games and flash (84%). Multimediabased maze game developed good eligibility based on media and material aspects of each value 840% and 82%. Student learning outcomes as a result of using a scientific approach to learning with a multimediabased labyrinth game increase with an average of gain index about (58%) and higher than conventional multimedia with index average gain of 0.41 (41%). Based on these results the scientific approach to learning by using multimediabased labyrinth game can improve the quality of learning and increase understanding of students. Multimedia of learning based labyrinth game, which developed, got a positive response from the students with a good qualification level (75%).

  20. An Ontology for State Analysis: Formalizing the Mapping to SysML

    Science.gov (United States)

    Wagner, David A.; Bennett, Matthew B.; Karban, Robert; Rouquette, Nicolas; Jenkins, Steven; Ingham, Michel

    2012-01-01

    State Analysis is a methodology developed over the last decade for architecting, designing and documenting complex control systems. Although it was originally conceived for designing robotic spacecraft, recent applications include the design of control systems for large ground-based telescopes. The European Southern Observatory (ESO) began a project to design the European Extremely Large Telescope (E-ELT), which will require coordinated control of over a thousand articulated mirror segments. The designers are using State Analysis as a methodology and the Systems Modeling Language (SysML) as a modeling and documentation language in this task. To effectively apply the State Analysis methodology in this context it became necessary to provide ontological definitions of the concepts and relations in State Analysis and greater flexibility through a mapping of State Analysis into a practical extension of SysML. The ontology provides the formal basis for verifying compliance with State Analysis semantics including architectural constraints. The SysML extension provides the practical basis for applying the State Analysis methodology with SysML tools. This paper will discuss the method used to develop these formalisms (the ontology), the formalisms themselves, the mapping to SysML and approach to using these formalisms to specify a control system and enforce architectural constraints in a SysML model.

  1. A Learning Object Approach To Evidence based learning

    Directory of Open Access Journals (Sweden)

    Zabin Visram

    2005-06-01

    Full Text Available This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has meant increasingly, there is a desperate need to adopt wireless schemes, whereby bespoke courses can be developed to help practitioners keep up with expanding knowledge base. Evidently, without current best evidence, practice risks becoming rapidly out of date, to the detriment of the patient. There is a need to provide a tactical, operational and effective environment, which allows professional to update their education, and complete specialised training, just-in-time, in their own time and location. Following this demand in the marketplace the information engineering group, in combination with several medical and dental schools, set out to develop and design a conceptual framework which form the basis of pioneering research, which at last, enables practitioner's to adopt a philosophy of life long learning. The body and structure of this framework is subsumed under the term Object oriented approach to Evidence Based learning, Just-in-time, via Internet sustained by Reusable Learning Objects (The OEBJIRLO Progression. The technical pillars which permit this concept of life long learning are pivoted by the foundations of object oriented technology, Learning objects, Just-in-time education, Data Mining, intelligent Agent technology, Flash interconnectivity and remote wireless technology, which allow practitioners to update their professional skills, complete specialised training which leads to accredited qualifications. This paper sets out to develop and

  2. Economic Gardening through Entrepreneurship Education: A Service-Learning Approach

    Science.gov (United States)

    Desplaces, David E.; Wergeles, Fred; McGuigan, Patrick

    2009-01-01

    This article outlines the implementation of a service-learning approach in an entrepreneurship programme using an "economic gardening" strategy. Economic Gardening through Service-Learning (EGS-L) is an approach to economic development that helps local businesses and students grow through a facilitated learning process. Learning is made possible…

  3. Learning Approaches - Final Report Sub-Project 4

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone; Rodríguez Illera, José Luis; Escofet, Anna

    2007-01-01

    The overall aim of Subproject 4 is to apply learning approaches that are appropriate and applicable using ICT. The task is made up of two components 4.1 dealing with learning approaches (see deliverable 4.1), and component 4.2 application of ICT (see deliverable 4.2, deliverable 4.3 & deliverable...

  4. E-Learning Approach in Teacher Training

    Science.gov (United States)

    Yucel, Seda A.

    2006-01-01

    There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational…

  5. Statistical and machine learning approaches for network analysis

    CERN Document Server

    Dehmer, Matthias

    2012-01-01

    Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation

  6. jqcML: an open-source java API for mass spectrometry quality control data in the qcML format.

    Science.gov (United States)

    Bittremieux, Wout; Kelchtermans, Pieter; Valkenborg, Dirk; Martens, Lennart; Laukens, Kris

    2014-07-03

    The awareness that systematic quality control is an essential factor to enable the growth of proteomics into a mature analytical discipline has increased over the past few years. To this aim, a controlled vocabulary and document structure have recently been proposed by Walzer et al. to store and disseminate quality-control metrics for mass-spectrometry-based proteomics experiments, called qcML. To facilitate the adoption of this standardized quality control routine, we introduce jqcML, a Java application programming interface (API) for the qcML data format. First, jqcML provides a complete object model to represent qcML data. Second, jqcML provides the ability to read, write, and work in a uniform manner with qcML data from different sources, including the XML-based qcML file format and the relational database qcDB. Interaction with the XML-based file format is obtained through the Java Architecture for XML Binding (JAXB), while generic database functionality is obtained by the Java Persistence API (JPA). jqcML is released as open-source software under the permissive Apache 2.0 license and can be downloaded from https://bitbucket.org/proteinspector/jqcml .

  7. A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces

    NARCIS (Netherlands)

    Melo, Rita; Fieldhouse, Robert; Melo, André; Correia, João D G; Cordeiro, Maria Natália D S; Gümüş, Zeynep H; Costa, Joaquim; Bonvin, Alexandre M J J; de Sousa Moreira, Irina

    2016-01-01

    Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model

  8. Understanding Fatty Acid Metabolism through an Active Learning Approach

    Science.gov (United States)

    Fardilha, M.; Schrader, M.; da Cruz e Silva, O. A. B.; da Cruz e Silva, E. F.

    2010-01-01

    A multi-method active learning approach (MALA) was implemented in the Medical Biochemistry teaching unit of the Biomedical Sciences degree at the University of Aveiro, using problem-based learning as the main learning approach. In this type of learning strategy, students are involved beyond the mere exercise of being taught by listening. Less…

  9. Development of Scientific Approach Based on Discovery Learning Module

    Science.gov (United States)

    Ellizar, E.; Hardeli, H.; Beltris, S.; Suharni, R.

    2018-04-01

    Scientific Approach is a learning process, designed to make the students actively construct their own knowledge through stages of scientific method. The scientific approach in learning process can be done by using learning modules. One of the learning model is discovery based learning. Discovery learning is a learning model for the valuable things in learning through various activities, such as observation, experience, and reasoning. In fact, the students’ activity to construct their own knowledge were not optimal. It’s because the available learning modules were not in line with the scientific approach. The purpose of this study was to develop a scientific approach discovery based learning module on Acid Based, also on electrolyte and non-electrolyte solution. The developing process of this chemistry modules use the Plomp Model with three main stages. The stages are preliminary research, prototyping stage, and the assessment stage. The subject of this research was the 10th and 11th Grade of Senior High School students (SMAN 2 Padang). Validation were tested by the experts of Chemistry lecturers and teachers. Practicality of these modules had been tested through questionnaire. The effectiveness had been tested through experimental procedure by comparing student achievement between experiment and control groups. Based on the findings, it can be concluded that the developed scientific approach discovery based learning module significantly improve the students’ learning in Acid-based and Electrolyte solution. The result of the data analysis indicated that the chemistry module was valid in content, construct, and presentation. Chemistry module also has a good practicality level and also accordance with the available time. This chemistry module was also effective, because it can help the students to understand the content of the learning material. That’s proved by the result of learning student. Based on the result can conclude that chemistry module based on

  10. The abstract geometry modeling language (AgML): experience and road map toward eRHIC

    International Nuclear Information System (INIS)

    Webb, Jason; Lauret, Jerome; Perevoztchikov, Victor

    2014-01-01

    The STAR experiment has adopted an Abstract Geometry Modeling Language (AgML) as the primary description of our geometry model. AgML establishes a level of abstraction, decoupling the definition of the detector from the software libraries used to create the concrete geometry model. Thus, AgML allows us to support both our legacy GEANT 3 simulation application and our ROOT/TGeo based reconstruction software from a single source, which is demonstrably self- consistent. While AgML was developed primarily as a tool to migrate away from our legacy FORTRAN-era geometry codes, it also provides a rich syntax geared towards the rapid development of detector models. AgML has been successfully employed by users to quickly develop and integrate the descriptions of several new detectors in the RHIC/STAR experiment including the Forward GEM Tracker (FGT) and Heavy Flavor Tracker (HFT) upgrades installed in STAR for the 2012 and 2013 runs. AgML has furthermore been heavily utilized to study future upgrades to the STAR detector as it prepares for the eRHIC era. With its track record of practical use in a live experiment in mind, we present the status, lessons learned and future of the AgML language as well as our experience in bringing the code into our production and development environments. We will discuss the path toward eRHIC and pushing the current model to accommodate for detector miss-alignment and high precision physics.

  11. QuakeML: XML for Seismological Data Exchange and Resource Metadata Description

    Science.gov (United States)

    Euchner, F.; Schorlemmer, D.; Becker, J.; Heinloo, A.; Kästli, P.; Saul, J.; Weber, B.; QuakeML Working Group

    2007-12-01

    QuakeML is an XML-based data exchange format for seismology that is under development. Current collaborators are from ETH, GFZ, USC, USGS, IRIS DMC, EMSC, ORFEUS, and ISTI. QuakeML development was motivated by the lack of a widely accepted and well-documented data format that is applicable to a broad range of fields in seismology. The development team brings together expertise from communities dealing with analysis and creation of earthquake catalogs, distribution of seismic bulletins, and real-time processing of seismic data. Efforts to merge QuakeML with existing XML dialects are under way. The first release of QuakeML will cover a basic description of seismic events including picks, arrivals, amplitudes, magnitudes, origins, focal mechanisms, and moment tensors. Further extensions are in progress or planned, e.g., for macroseismic information, location probability density functions, slip distributions, and ground motion information. The QuakeML language definition is supplemented by a concept to provide resource metadata and facilitate metadata exchange between distributed data providers. For that purpose, we introduce unique, location-independent identifiers of seismological resources. As an application of QuakeML, ETH Zurich currently develops a Python-based seismicity analysis toolkit as a contribution to CSEP (Collaboratory for the Study of Earthquake Predictability). We follow a collaborative and transparent development approach along the lines of the procedures of the World Wide Web Consortium (W3C). QuakeML currently is in working draft status. The standard description will be subjected to a public Request for Comments (RFC) process and eventually reach the status of a recommendation. QuakeML can be found at http://www.quakeml.org.

  12. E-Learning Approach in Teacher Training

    OpenAIRE

    YUCEL, A. Seda

    2015-01-01

    There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational system on platform with Internet, Intranet or computer access. The concept of e-learning has two main subtitles as synchronized (where a group of stu...

  13. Machine Learning Approaches for Clinical Psychology and Psychiatry.

    Science.gov (United States)

    Dwyer, Dominic B; Falkai, Peter; Koutsouleris, Nikolaos

    2018-05-07

    Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an accessible understanding of why this approach is important for future practice given its potential to augment decisions associated with the diagnosis, prognosis, and treatment of people suffering from mental illness using clinical and biological data. To this end, the limitations of current statistical paradigms in mental health research are critiqued, and an introduction is provided to critical machine learning methods used in clinical studies. A selective literature review is then presented aiming to reinforce the usefulness of machine learning methods and provide evidence of their potential. In the context of promising initial results, the current limitations of machine learning approaches are addressed, and considerations for future clinical translation are outlined.

  14. A deep learning approach to estimate chemically-treated collagenous tissue nonlinear anisotropic stress-strain responses from microscopy images.

    Science.gov (United States)

    Liang, Liang; Liu, Minliang; Sun, Wei

    2017-11-01

    Biological collagenous tissues comprised of networks of collagen fibers are suitable for a broad spectrum of medical applications owing to their attractive mechanical properties. In this study, we developed a noninvasive approach to estimate collagenous tissue elastic properties directly from microscopy images using Machine Learning (ML) techniques. Glutaraldehyde-treated bovine pericardium (GLBP) tissue, widely used in the fabrication of bioprosthetic heart valves and vascular patches, was chosen to develop a representative application. A Deep Learning model was designed and trained to process second harmonic generation (SHG) images of collagen networks in GLBP tissue samples, and directly predict the tissue elastic mechanical properties. The trained model is capable of identifying the overall tissue stiffness with a classification accuracy of 84%, and predicting the nonlinear anisotropic stress-strain curves with average regression errors of 0.021 and 0.031. Thus, this study demonstrates the feasibility and great potential of using the Deep Learning approach for fast and noninvasive assessment of collagenous tissue elastic properties from microstructural images. In this study, we developed, to our best knowledge, the first Deep Learning-based approach to estimate the elastic properties of collagenous tissues directly from noninvasive second harmonic generation images. The success of this study holds promise for the use of Machine Learning techniques to noninvasively and efficiently estimate the mechanical properties of many structure-based biological materials, and it also enables many potential applications such as serving as a quality control tool to select tissue for the manufacturing of medical devices (e.g. bioprosthetic heart valves). Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  15. A Learning Object Approach To Evidence based learning

    OpenAIRE

    Zabin Visram; Bruce Elson; Patricia Reynolds

    2005-01-01

    This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has mea...

  16. ML 3.1 developer's guide.

    Energy Technology Data Exchange (ETDEWEB)

    Sala, Marzio; Hu, Jonathan Joseph (Sandia National Laboratories, Livermore, CA); Tuminaro, Raymond Stephen (Sandia National Laboratories, Livermore, CA)

    2004-05-01

    ML development was started in 1997 by Ray Tuminaro and Charles Tong. Currently, there are several full- and part-time developers. The kernel of ML is written in ANSI C, and there is a rich C++ interface for Trilinos users and developers. ML can be customized to run geometric and algebraic multigrid; it can solve a scalar or a vector equation (with constant number of equations per grid node), and it can solve a form of Maxwell's equations. For a general introduction to ML and its applications, we refer to the Users Guide [SHT04], and to the ML web site, http://software.sandia.gov/ml.

  17. Mathematics Literacy on Problem Based Learning with Indonesian Realistic Mathematics Education Approach Assisted E-Learning Edmodo

    Science.gov (United States)

    Wardono; Waluya, S. B.; Mariani, Scolastika; Candra D, S.

    2016-02-01

    This study aims to find out that there are differences in mathematical literacy ability in content Change and Relationship class VII Junior High School 19, Semarang by Problem Based Learning (PBL) model with an Indonesian Realistic Mathematics Education (called Pendidikan Matematika Realistik Indonesia or PMRI in Indonesia) approach assisted Elearning Edmodo, PBL with a PMRI approach, and expository; to know whether the group of students with learning PBL models with PMRI approach and assisted E-learning Edmodo can improve mathematics literacy; to know that the quality of learning PBL models with a PMRI approach assisted E-learning Edmodo has a good category; to describe the difficulties of students in working the problems of mathematical literacy ability oriented PISA. This research is a mixed methods study. The population was seventh grade students of Junior High School 19, Semarang Indonesia. Sample selection is done by random sampling so that the selected experimental class 1, class 2 and the control experiment. Data collected by the methods of documentation, tests and interviews. From the results of this study showed average mathematics literacy ability of students in the group PBL models with a PMRI approach assisted E-learning Edmodo better than average mathematics literacy ability of students in the group PBL models with a PMRI approach and better than average mathematics literacy ability of students in the expository models; Mathematics literacy ability in the class using the PBL model with a PMRI approach assisted E-learning Edmodo have increased and the improvement of mathematics literacy ability is higher than the improvement of mathematics literacy ability of class that uses the model of PBL learning with PMRI approach and is higher than the improvement of mathematics literacy ability of class that uses the expository models; The quality of learning using PBL models with a PMRI approach assisted E-learning Edmodo have very good category.

  18. mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data.

    Science.gov (United States)

    Larralde, Martin; Lawson, Thomas N; Weber, Ralf J M; Moreno, Pablo; Haug, Kenneth; Rocca-Serra, Philippe; Viant, Mark R; Steinbeck, Christoph; Salek, Reza M

    2017-08-15

    Submission to the MetaboLights repository for metabolomics data currently places the burden of reporting instrument and acquisition parameters in ISA-Tab format on users, who have to do it manually, a process that is time consuming and prone to user input error. Since the large majority of these parameters are embedded in instrument raw data files, an opportunity exists to capture this metadata more accurately. Here we report a set of Python packages that can automatically generate ISA-Tab metadata file stubs from raw XML metabolomics data files. The parsing packages are separated into mzML2ISA (encompassing mzML and imzML formats) and nmrML2ISA (nmrML format only). Overall, the use of mzML2ISA & nmrML2ISA reduces the time needed to capture metadata substantially (capturing 90% of metadata on assay and sample levels), is much less prone to user input errors, improves compliance with minimum information reporting guidelines and facilitates more finely grained data exploration and querying of datasets. mzML2ISA & nmrML2ISA are available under version 3 of the GNU General Public Licence at https://github.com/ISA-tools. Documentation is available from http://2isa.readthedocs.io/en/latest/. reza.salek@ebi.ac.uk or isatools@googlegroups.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

  19. Project Management Approaches for Online Learning Design

    Science.gov (United States)

    Eby, Gulsun; Yuzer, T. Volkan

    2013-01-01

    Developments in online learning and its design are areas that continue to grow in order to enhance students' learning environments and experiences. However, in the implementation of new technologies, the importance of properly and fairly overseeing these courses is often undervalued. "Project Management Approaches for Online Learning Design"…

  20. Machine learning approaches in medical image analysis

    DEFF Research Database (Denmark)

    de Bruijne, Marleen

    2016-01-01

    Machine learning approaches are increasingly successful in image-based diagnosis, disease prognosis, and risk assessment. This paper highlights new research directions and discusses three main challenges related to machine learning in medical imaging: coping with variation in imaging protocols......, learning from weak labels, and interpretation and evaluation of results....

  1. Teaching of anatomical sciences: A blended learning approach.

    Science.gov (United States)

    Khalil, Mohammed K; Abdel Meguid, Eiman M; Elkhider, Ihsan A

    2018-04-01

    Blended learning is the integration of different learning approaches, new technologies, and activities that combine traditional face-to-face teaching methods with authentic online methodologies. Although advances in educational technology have helped to expand the selection of different pedagogies, the teaching of anatomical sciences has been challenged by implementation difficulties and other limitations. These challenges are reported to include lack of time, costs, and lack of qualified teachers. Easy access to online information and advances in technology make it possible to resolve these limitations by adopting blended learning approaches. Blended learning strategies have been shown to improve students' academic performance, motivation, attitude, and satisfaction, and to provide convenient and flexible learning. Implementation of blended learning strategies has also proved cost effective. This article provides a theoretical foundation for blended learning and proposes a validated framework for the design of blended learning activities in the teaching and learning of anatomical sciences. Clin. Anat. 31:323-329, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

  2. Machine Learning Approaches in Cardiovascular Imaging.

    Science.gov (United States)

    Henglin, Mir; Stein, Gillian; Hushcha, Pavel V; Snoek, Jasper; Wiltschko, Alexander B; Cheng, Susan

    2017-10-01

    Cardiovascular imaging technologies continue to increase in their capacity to capture and store large quantities of data. Modern computational methods, developed in the field of machine learning, offer new approaches to leveraging the growing volume of imaging data available for analyses. Machine learning methods can now address data-related problems ranging from simple analytic queries of existing measurement data to the more complex challenges involved in analyzing raw images. To date, machine learning has been used in 2 broad and highly interconnected areas: automation of tasks that might otherwise be performed by a human and generation of clinically important new knowledge. Most cardiovascular imaging studies have focused on task-oriented problems, but more studies involving algorithms aimed at generating new clinical insights are emerging. Continued expansion in the size and dimensionality of cardiovascular imaging databases is driving strong interest in applying powerful deep learning methods, in particular, to analyze these data. Overall, the most effective approaches will require an investment in the resources needed to appropriately prepare such large data sets for analyses. Notwithstanding current technical and logistical challenges, machine learning and especially deep learning methods have much to offer and will substantially impact the future practice and science of cardiovascular imaging. © 2017 American Heart Association, Inc.

  3. Learning approaches of Indonesian EFL Gen Z students in a Flipped Learning context

    Directory of Open Access Journals (Sweden)

    Made Hery Santosa

    2017-09-01

    Full Text Available The 21st-century learning has eventually transformed today’s classroom. With more digital natives in the class, both educators and students face a changing classroom that should accommodate different learning paces, styles and needs. This study aimed at helping students in becoming English as Foreign Language (EFL competent in-service teachers. Using Flipped Learning, the study utilizes four FLIP pillars into EFL learning, namely Flexible environment, Learning culture, Intentional content, Professional educators. The study employed three instruments, namely survey, tests, and interview. The result of tests showed a promising students’ progress from low to high achievement. The survey showed that students tended to perform deep approaches to learning while findings from the interview provided more interesting phenomena underlying students’ motives in their learning approaches, involving dynamic power distance relationship between lecturer and students. Heavier task loads and learning model familiarity have been highlighted. Effective socialization of the model using technology and sustainability of use of the model are suggested.

  4. Self-regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison Between Professional Training and English Learning.

    Science.gov (United States)

    Tseng, Min-Chen; Chen, Chia-Cheng

    2017-06-01

    This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between students' professional training and English learning. The participants consisted of 344 arts majors. The Academic Self-Regulation Questionnaire and the Revised Learning Process Questionnaire were adopted to examine students' self-regulatory behaviors and their approaches to learning. The results show that a positive and significant correlation was found in students' self-regulatory behaviors between professional training and English learning. The results indicated that increases in using self-regulatory behaviors in professional training were associated with increases in applying self-regulatory behaviors in learning English. Seeking assistance, self-evaluation, and planning and organizing were significant predictors for learning English. In addition, arts students used the deep approach more often than the surface approach in both their professional training and English learning. A positive correlation was found in DA, whereas a negative correlation was shown in SA between students' self-regulatory behaviors and their approaches to learning. Students with high self-regulation adopted a deep approach, and they applied the surface approach less in professional training and English learning. In addition, a SEM model confirmed that DA had a positive influence; however, SA had a negative influence on self-regulatory behaviors.

  5. Allelism of Genes in the Ml-a locus

    DEFF Research Database (Denmark)

    Giese, Nanna Henriette; Jensen, Hans Peter; Jørgensen, Jørgen Helms

    1980-01-01

    Seven barley lines or varieties, each with a different gene at the Ml-a locus for resistance to Erysiphe graminis were intercrossed. Progeny testing of the F2s using two different fungal isolates per cross provided evidence that there are two or more loci in the Ml-a region. Apparent recombinants...... were also screened for recombination between the Hor1 and Hor2 loci which are situated either side of the Ml-a locus. The cross between Ricardo and Iso42R (Rupee) yielded one possible recombinant, with Ml-a3 and Ml-a(Rul) in the coupling phase; other recombinants had wild-type genes in the coupling...... phase. Iso20R, derived from Hordeum spontaneum 'H204', carrying Ml-a6, had an additional gene, in close coupling with Ml-a6, tentatively named Ml-aSp2 or Reglv, causing an intermediate infection type with isolate EmA30. It is suggested that Ml-a(Ar) in Emir and Ml-a(Rul), shown to differ from other Ml...

  6. Component-Based Approach in Learning Management System Development

    Science.gov (United States)

    Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

    2013-01-01

    The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…

  7. (CBTP) on knowledge, problem-solving and learning approach

    African Journals Online (AJOL)

    In the first instance attention is paid to the effect of a computer-based teaching programme (CBTP) on the knowledge, problem-solving skills and learning approach of student ... In the practice group (oncology wards) no statistically significant change in the learning approach of respondents was found after using the CBTP.

  8. Spectra, chromatograms, Metadata: mzML-the standard data format for mass spectrometer output.

    Science.gov (United States)

    Turewicz, Michael; Deutsch, Eric W

    2011-01-01

    This chapter describes Mass Spectrometry Markup Language (mzML), an XML-based and vendor-neutral standard data format for storage and exchange of mass spectrometer output like raw spectra and peak lists. It is intended to replace its two precursor data formats (mzData and mzXML), which had been developed independently a few years earlier. Hence, with the release of mzML, the problem of having two different formats for the same purposes is solved, and with it the duplicated effort of maintaining and supporting two data formats. The new format has been developed by a broad-based consortium of major instrument vendors, software vendors, and academic researchers under the aegis of the Human Proteome Organisation (HUPO), Proteomics Standards Initiative (PSI), with full participation of the main developers of the precursor formats. This comprehensive approach helped mzML to become a generally accepted standard. Furthermore, the collaborative development insured that mzML has adopted the best features of its precursor formats. In this chapter, we discuss mzML's development history, its design principles and use cases, as well as its main building components. We also present the available documentation, an example file, and validation software for mzML.

  9. Integrated approaches to perceptual learning.

    Science.gov (United States)

    Jacobs, Robert A

    2010-04-01

    New technologies and new ways of thinking have recently led to rapid expansions in the study of perceptual learning. We describe three themes shared by many of the nine articles included in this topic on Integrated Approaches to Perceptual Learning. First, perceptual learning cannot be studied on its own because it is closely linked to other aspects of cognition, such as attention, working memory, decision making, and conceptual knowledge. Second, perceptual learning is sensitive to both the stimulus properties of the environment in which an observer exists and to the properties of the tasks that the observer needs to perform. Moreover, the environmental and task properties can be characterized through their statistical regularities. Finally, the study of perceptual learning has important implications for society, including implications for science education and medical rehabilitation. Contributed articles relevant to each theme are summarized. Copyright © 2010 Cognitive Science Society, Inc.

  10. Group investigation with scientific approach in mathematics learning

    Science.gov (United States)

    Indarti, D.; Mardiyana; Pramudya, I.

    2018-03-01

    The aim of this research is to find out the effect of learning model toward mathematics achievement. This research is quasi-experimental research. The population of research is all VII grade students of Karanganyar regency in the academic year of 2016/2017. The sample of this research was taken using stratified cluster random sampling technique. Data collection was done based on mathematics achievement test. The data analysis technique used one-way ANOVA following the normality test with liliefors method and homogeneity test with Bartlett method. The results of this research is the mathematics learning using Group Investigation learning model with scientific approach produces the better mathematics learning achievement than learning with conventional model on material of quadrilateral. Group Investigation learning model with scientific approach can be used by the teachers in mathematics learning, especially in the material of quadrilateral, which is can improve the mathematics achievement.

  11. Numbered head together with scientific approach in geometry learning

    Science.gov (United States)

    Indarti, Dwi; Mardiyana; Pramudya, Ikrar

    2017-12-01

    The aim of this research was to find out the influence of learning model implementation toward student’s achievement in mathematics. This research was using quasi-experimental research. The population of the research was all of 7th grade students in Karanganyar. Sample was taken using stratified cluster random sampling technique. The data collection has been conducted based on students’ mathematics achievement test. The results from the data analysis showed that the learning mathematics by using Numbered Head Together (NHT) learning model with scientific approach improved student’s achievement in mathematics rather than direct learning model particularly in learning object of quadrilateral. Implementation of NHT learning model with scientific approach could be used by the teachers in teaching and learning, particularly in learning object of quadrilateral.

  12. Learning from tutorials: a qualitative study of approaches to learning and perceptions of tutorial interaction

    DEFF Research Database (Denmark)

    Herrmann, Kim Jesper

    2014-01-01

    This study examines differences in university students’ approaches to learning when attending tutorials as well as variation in students’ perceptions of tutorials as an educational arena. In-depth qualitative analysis of semi-structured interviews with undergraduates showed how surface and deep...... approaches to learning were revealed in the students’ note-taking, listening, and engaging in dialogue. It was also shown how variation in the students’ approaches to learning were coherent with variation in the students’ perceptions of the tutors’ pedagogical role, the value of peer interaction......, and the overall purpose of tutorials. The results are discussed regarding the paradox that students relying on surface approaches to learning seemingly are the ones least likely to respond to tutorials in the way they were intended....

  13. Intra-articular sodium hyaluronate 2 mL versus physiological saline 20 mL versus physiological saline 2 mL for painful knee osteoarthritis: a randomized clinical trial

    DEFF Research Database (Denmark)

    Lundsgaard, C.; Dufour, N.; Fallentin, E.

    2008-01-01

    , Knee Injury and Osteoarthritis Outcome Score (KOOS), Osteoarthritis Research Society International (OARSI) criteria, and global assessment of the patient's condition. Results: The mean age of the patients was 69.4 years; 55% were women. The effects of hyaluronate 2 mL, physiological saline 20 m......Objective: Methodological constraints weaken previous evidence on intra-articular viscosupplementation and physiological saline distention for osteoarthritis. We conducted a randomized, patient- and observer-blind trial to evaluate these interventions in patients with painful knee osteoarthritis....... Methods: We centrally randomized 251 patients with knee ostcoarthritis to four weekly intra-articular injections of sodium hyaluronate 2 mL (Hyalgan(R) 10.3 mg/mL) versus physiological saline 20 mL (distention) versus physiological saline 2 mL (placebo) and followed patients for 26 weeks. Inclusion...

  14. The relationship between learning preferences (styles and approaches) and learning outcomes among pre-clinical undergraduate medical students.

    Science.gov (United States)

    Liew, Siaw-Cheok; Sidhu, Jagmohni; Barua, Ankur

    2015-03-11

    Learning styles and approaches of individual undergraduate medical students vary considerably and as a consequence, their learning needs also differ from one student to another. This study was conducted to identify different learning styles and approaches of pre-clinical, undergraduate medical students and also to determine the relationships of learning preferences with performances in the summative examinations. A cross-sectional study was conducted among randomly selected 419 pre-clinical, undergraduate medical students of the International Medical University (IMU) in Kuala Lumpur. The number of students from Year 2 was 217 while that from Year 3 was 202. The Visual, Auditory, Read/Write, Kinesthetic (VARK) and the Approaches and Study Skills Inventory for Students (ASSIST) questionnaires were used for data collection. This study revealed that 343 students (81.9%) had unimodal learning style, while the remaining 76 (18.1%) used a multimodal learning style. Among the unimodal learners, a majority (30.1%) were of Kinesthetic (K) type. Among the middle and high achievers in summative examinations, a majority had unimodal (Kinaesthetic) learning style (30.5%) and were also strategic/deep learners (79.4%). However, the learning styles and approaches did not contribute significantly towards the learning outcomes in summative examinations. A majority of the students in this study had Unimodal (Kinesthetic) learning style. The learning preferences (styles and approaches) did not contribute significantly to the learning outcomes. Future work to re-assess the viability of these learning preferences (styles and approaches) after the incorporation of teaching-learning instructions tailored specifically to the students will be beneficial to help medical teachers in facilitating students to become more capable learners.

  15. The Implementation of Discovery Learning Model with Scientific Learning Approach to Improve Students’ Critical Thinking in Learning History

    Directory of Open Access Journals (Sweden)

    Edi Nurcahyo

    2018-03-01

    Full Text Available Historical learning has not reached optimal in the learning process. It is caused by the history teachers’ learning model has not used the innovative learning models. Furthermore, it supported by the perception of students to the history subject because it does not become final exam (UN subject so it makes less improvement and builds less critical thinking in students’ daily learning. This is due to the lack of awareness of historical events and the availability of history books for students and teachers in the library are still lacking. Discovery learning with scientific approach encourages students to solve problems actively and able to improve students' critical thinking skills with scientific approach so student can build scientific thinking include observing, asking, reasoning, trying, and networking   Keywords: discovery learning, scientific, critical thinking

  16. Design of Learning Objects for Concept Learning: Effects of Multimedia Learning Principles and an Instructional Approach

    Science.gov (United States)

    Chiu, Thomas K. F.; Churchill, Daniel

    2016-01-01

    Literature suggests using multimedia learning principles in the design of instructional material. However, these principles may not be sufficient for the design of learning objects for concept learning in mathematics. This paper reports on an experimental study that investigated the effects of an instructional approach, which includes two teaching…

  17. MPS and ML

    Science.gov (United States)

    ... individuals about MPS and ML, the National MPS Society has created a central location for more information on MPS. Click here to go to the MPS Library. Share Tweet Our Mission The National MPS Society exists to cure, support and advocate for MPS ...

  18. Exam Success at Undergraduate and Graduate-Entry Medical Schools: Is Learning Style or Learning Approach More Important? A Critical Review Exploring Links Between Academic Success, Learning Styles, and Learning Approaches Among School-Leaver Entry ("Traditional") and Graduate-Entry ("Nontraditional") Medical Students.

    Science.gov (United States)

    Feeley, Anne-Marie; Biggerstaff, Deborah L

    2015-01-01

    PHENOMENON: The literature on learning styles over many years has been replete with debate and disagreement. Researchers have yet to elucidate exactly which underlying constructs are measured by the many learning styles questionnaires available. Some academics question whether learning styles exist at all. When it comes to establishing the value of learning styles for medical students, a further issue emerges. The demographics of medical students in the United Kingdom have changed in recent years, so past studies may not be applicable to students today. We wanted to answer a very simple, practical question: what can the literature on learning styles tell us that we can use to help today's medical students succeed academically at medical school? We conducted a literature review to synthesise the available evidence on how two different aspects of learning-the way in which students like to receive information in a learning environment (termed learning "styles") and the motivations that drive their learning (termed learning "approaches")-can impact on medical students' academic achievement. Our review confirms that although learning "styles" do not correlate with exam performance, learning "approaches" do: those with "strategic" and "deep" approaches to learning (i.e., motivated to do well and motivated to learn deeply respectively) perform consistently better in medical school examinations. Changes in medical school entrant demographics in the past decade have not altered these correlations. Optimistically, our review reveals that students' learning approaches can change and more adaptive approaches may be learned. Insights: For educators wishing to help medical students succeed academically, current evidence demonstrates that helping students develop their own positive learning approach using "growth mind-set" is a more effective (and more feasible) than attempting to alter students' learning styles. This conclusion holds true for both "traditional" and graduate

  19. Multi-dimensional technology-enabled social learning approach

    DEFF Research Database (Denmark)

    Petreski, Hristijan; Tsekeridou, Sofia; Prasad, Neeli R.

    2013-01-01

    ’t respond to this systemic and structural changes and/or challenges and retains its status quo than it is jeopardizing its own existence or the existence of the education, as we know it. This paper aims to precede one step further by proposing a multi-dimensional approach for technology-enabled social...... in learning while socializing within their learning communities. However, their “educational” usage is still limited to facilitation of online learning communities and to collaborative authoring of learning material complementary to existing formal (e-) learning services. If the educational system doesn...

  20. Machine learning approaches to diagnosis and laterality effects in semantic dementia discourse.

    Science.gov (United States)

    Garrard, Peter; Rentoumi, Vassiliki; Gesierich, Benno; Miller, Bruce; Gorno-Tempini, Maria Luisa

    2014-06-01

    Advances in automatic text classification have been necessitated by the rapid increase in the availability of digital documents. Machine learning (ML) algorithms can 'learn' from data: for instance a ML system can be trained on a set of features derived from written texts belonging to known categories, and learn to distinguish between them. Such a trained system can then be used to classify unseen texts. In this paper, we explore the potential of the technique to classify transcribed speech samples along clinical dimensions, using vocabulary data alone. We report the accuracy with which two related ML algorithms [naive Bayes Gaussian (NBG) and naive Bayes multinomial (NBM)] categorized picture descriptions produced by: 32 semantic dementia (SD) patients versus 10 healthy, age-matched controls; and SD patients with left- (n = 21) versus right-predominant (n = 11) patterns of temporal lobe atrophy. We used information gain (IG) to identify the vocabulary features that were most informative to each of these two distinctions. In the SD versus control classification task, both algorithms achieved accuracies of greater than 90%. In the right- versus left-temporal lobe predominant classification, NBM achieved a high level of accuracy (88%), but this was achieved by both NBM and NBG when the features used in the training set were restricted to those with high values of IG. The most informative features for the patient versus control task were low frequency content words, generic terms and components of metanarrative statements. For the right versus left task the number of informative lexical features was too small to support any specific inferences. An enriched feature set, including values derived from Quantitative Production Analysis (QPA) may shed further light on this little understood distinction. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. The XBabelPhish MAGE-ML and XML translator.

    Science.gov (United States)

    Maier, Don; Wymore, Farrell; Sherlock, Gavin; Ball, Catherine A

    2008-01-18

    MAGE-ML has been promoted as a standard format for describing microarray experiments and the data they produce. Two characteristics of the MAGE-ML format compromise its use as a universal standard: First, MAGE-ML files are exceptionally large - too large to be easily read by most people, and often too large to be read by most software programs. Second, the MAGE-ML standard permits many ways of representing the same information. As a result, different producers of MAGE-ML create different documents describing the same experiment and its data. Recognizing all the variants is an unwieldy software engineering task, resulting in software packages that can read and process MAGE-ML from some, but not all producers. This Tower of MAGE-ML Babel bars the unencumbered exchange of microarray experiment descriptions couched in MAGE-ML. We have developed XBabelPhish - an XQuery-based technology for translating one MAGE-ML variant into another. XBabelPhish's use is not restricted to translating MAGE-ML documents. It can transform XML files independent of their DTD, XML schema, or semantic content. Moreover, it is designed to work on very large (> 200 Mb.) files, which are common in the world of MAGE-ML. XBabelPhish provides a way to inter-translate MAGE-ML variants for improved interchange of microarray experiment information. More generally, it can be used to transform most XML files, including very large ones that exceed the capacity of most XML tools.

  2. Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches

    Science.gov (United States)

    Wang, Victor C. X.

    2010-01-01

    As adult learners and educators pioneer the use of technology in the new century, attention has been focused on developing strategic approaches to effectively integrate adult learning and technology in different learning environments. "Integrating Adult Learning and Technologies for Effective Education: Strategic Approaches" provides innovative…

  3. The difference of contrast effects of myelography in normal dogs: Comparison of iohexol (180 mgI/ml), iohexol (240 mgI/ml) and iotrolan (240 mgI/ml)

    International Nuclear Information System (INIS)

    Shimizu, J.; Yamada, K.; Kishimoto, M.; Iwasaki, T.; Miyake, Y.

    2008-01-01

    The contrast effects of three different contrast media preparations (iohexol 180 mgI/ml, iohexol 240 mgI/ml and iotrolan 240 mgI/ml) in conventional and CT myelography were compared. Three beagle dogs were used and the study employed a cross-over method (total of 9) for each contrast media. The result of CT myelography showed that the contrast effect of iohexol (180 mgI/ml), which had low viscosity, was highest in cranial sites, and the contrast effect of high-viscosity iotrolan (240 mgI/ml) was highest in caudal sites 5 min after injection of the contrast media preparations. This shows that the diffusion of contrast media preparations in the subarachnoid space is influenced by viscosity. The results of conventional myelography also showed that the diffusion of contrast media preparations is influenced by viscosity. Therefore, it is important to identify the location of spinal lesions in veterinary practice, and low viscosity contrast medium preparation with wide spread contrast effects is considered suitable for myelography

  4. Implementation of Reseptive Esteemy Approach Model in Learning Reading Literature

    Directory of Open Access Journals (Sweden)

    Titin Nurhayatin

    2017-03-01

    Full Text Available Research on the implementation of aesthetic model of receptive aesthetic approach in learning to read the literature on the background of the low quality of results and learning process of Indonesian language, especially the study of literature. Students as prospective teachers of Indonesian language are expected to have the ability to speak, have literature, and their learning in a balanced manner in accordance with the curriculum demands. This study examines the effectiveness, quality, acceptability, and sustainability of the aesthetic approach of receptions in improving students' literary skills. Based on these problems, this study is expected to produce a learning model that contributes high in improving the quality of results and the process of learning literature. This research was conducted on the students of Language Education Program, Indonesian Literature and Regional FKIP Pasundan University. The research method used is experiment with randomized type pretest-posttest control group design. Based on preliminary and final test data obtained in the experimental class the average preliminary test was 55.86 and the average final test was 76.75. From the preliminary test data in the control class the average score was 55.07 and the average final test was 68.76. These data suggest that there is a greater increase in grades in the experimental class using the aesthetic approach of the reception compared with the increase in values in the control class using a conventional approach. The results show that the aesthetic approach of receptions is more effective than the conventional approach in literary reading. Based on observations, acceptance, and views of sustainability, the aesthetic approach of receptions in literary learning is expected to be an alternative and solution in overcoming the problems of literary learning and improving the quality of Indonesian learning outcomes and learning process.

  5. Problem Posing with Realistic Mathematics Education Approach in Geometry Learning

    Science.gov (United States)

    Mahendra, R.; Slamet, I.; Budiyono

    2017-09-01

    One of the difficulties of students in the learning of geometry is on the subject of plane that requires students to understand the abstract matter. The aim of this research is to determine the effect of Problem Posing learning model with Realistic Mathematics Education Approach in geometry learning. This quasi experimental research was conducted in one of the junior high schools in Karanganyar, Indonesia. The sample was taken using stratified cluster random sampling technique. The results of this research indicate that the model of Problem Posing learning with Realistic Mathematics Education Approach can improve students’ conceptual understanding significantly in geometry learning especially on plane topics. It is because students on the application of Problem Posing with Realistic Mathematics Education Approach are become to be active in constructing their knowledge, proposing, and problem solving in realistic, so it easier for students to understand concepts and solve the problems. Therefore, the model of Problem Posing learning with Realistic Mathematics Education Approach is appropriately applied in mathematics learning especially on geometry material. Furthermore, the impact can improve student achievement.

  6. Looking at Learning Approaches from the Angle of Student Profiles

    Science.gov (United States)

    Kyndt, Eva; Dochy, Filip; Struyven, Katrien; Cascallar, Eduardo

    2012-01-01

    This study starts with investigating the relation of perceived workload, motivation for learning and working memory capacity (WMC) with students' approaches to learning. Secondly, this study investigates if differences exist between different student profiles concerning their approach to the learning and the influence of workloads thereon. Results…

  7. QuakeML 2.0: Recent developments

    Science.gov (United States)

    Euchner, Fabian; Kästli, Philipp; Heiniger, Lukas; Saul, Joachim; Schorlemmer, Danijel; Clinton, John

    2016-04-01

    QuakeML is a community-backed data model for seismic event parameter description. Its current version 1.2, released in 2013, has become the gold standard for parametric data dissemination at seismological data centers, and has been adopted as an FDSN standard. It is supported by several popular software products and data services, such as FDSN event web services, QuakePy, and SeisComP3. Work on the successor version 2.0 is under way since 2015. The scope of QuakeML has been expanded beyond event parameter description. Thanks to a modular architecture, many thematic packages have been added, which cover peak ground motion, site and station characterization, hydraulic parameters of borehole injection processes, and macroseismics. The first three packages can be considered near final and implementations of program codes and SQL databases are in productive use at various institutions. A public community review process has been initiated in order to turn them into community-approved standards. The most recent addition is a package for single station quake location, which allows a detailed probabilistic description of event parameters recorded at a single station. This package adds some information elements such as angle of incidence, frequency-dependent phase picks, and dispersion relations. The package containing common data types has been extended with a generic type for probability density functions. While on Earth, single station methods are niche applications, they are of prominent interest in planetary seismology, e.g., the NASA InSight mission to Mars. So far, QuakeML is lacking a description of seismic instrumentation (inventory). There are two existing standards of younger age (FDSN StationXML and SeisComP3 Inventory XML). We discuss their respective strengths, differences, and how they could be combined into an inventory package for QuakeML, thus allowing full interoperability with other QuakeML data types. QuakeML is accompanied by QuakePy, a Python package

  8. Investigating the Efficiency of Scenario Based Learning and Reflective Learning Approaches in Teacher Education

    Science.gov (United States)

    Hursen, Cigdem; Fasli, Funda Gezer

    2017-01-01

    The main purpose of this research is to investigate the efficiency of scenario based learning and reflective learning approaches in teacher education. The impact of applications of scenario based learning and reflective learning on prospective teachers' academic achievement and views regarding application and professional self-competence…

  9. E-learning and blended learning in textile engineering education: a closed feedback loop approach

    Science.gov (United States)

    Charitopoulos, A.; Vassiliadis, S.; Rangoussi, M.; Koulouriotis, D.

    2017-10-01

    E-learning has gained a significant role in typical education and in professional training, thanks to the flexibility it offers to the time and location parameters of the education event framework. Purely e-learning scenarios are mostly limited either to Open University-type higher education institutions or to graduate level or professional degrees; blended learning scenarios are progressively becoming popular thanks to their balanced approach. The aim of the present work is to propose approaches that exploit the e-learning and the blended-learning scenarios for Textile Engineering education programmes, especially for multi-institutional ones. The “E-Team” European MSc degree programme organized by AUTEX is used as a case study. The proposed solution is based on (i) a free and open-source e-learning platform (moodle) and (ii) blended learning educational scenarios. Educational challenges addressed include student engagement, student error / failure handling, as well as collaborative learning promotion and support.

  10. Science of learning is learning of science: why we need a dialectical approach to science education research

    Science.gov (United States)

    Roth, Wolff-Michael

    2012-06-01

    Research on learning science in informal settings and the formal (sometimes experimental) study of learning in classrooms or psychological laboratories tend to be separate domains, even drawing on different theories and methods. These differences make it difficult to compare knowing and learning observed in one paradigm/context with those observed in the other. Even more interestingly, the scientists studying science learning rarely consider their own learning in relation to the phenomena they study. A dialectical, reflexive approach to learning, however, would theorize the movement of an educational science (its learning and development) as a special and general case—subject matter and method—of the phenomenon of learning (in/of) science. In the dialectical approach to the study of science learning, therefore, subject matter, method, and theory fall together. This allows for a perspective in which not only disparate fields of study—school science learning and learning in everyday life—are integrated but also where the progress in the science of science learning coincides with its topic. Following the articulation of a contradictory situation on comparing learning in different settings, I describe the dialectical approach. As a way of providing a concrete example, I then trace the historical movement of my own research group as it simultaneously and alternately studied science learning in formal and informal settings. I conclude by recommending cultural-historical, dialectical approaches to learning and interaction analysis as a context for fruitful interdisciplinary research on science learning within and across different settings.

  11. Learning environment, approaches to learning and learning preferences: medical students versus general education students.

    Science.gov (United States)

    Ullah, Raza

    2016-05-01

    The main objective of the study was to see whether medical students use more desirable approaches to studying than general education students. Survey method was used to collect data from both the medical students and the general education students. The survey of the medical students was carried out between January and March, 2012. The survey was administered to all the medical students present in lecture halls on day of data collection, while general education students were randomly selected from four subject areas at two universities. In total, 976 medical students and 912 general students participated in the study. Of the general students, 494(54%) were boys and 418(46%)were girls with an overall mean age of 20.53±1.77 years (range: 17-27 years). The medical students' perceptions of their learning environment and their learning preferences were broadly similar to that of general education students with the exception of workload. The medical students perceived the workload to be less appropriate (Mean = 2.06±0.72) than the students in general education (Mean = 2.84±0.90). The medical students were more likely to use the deep approach to studying (Mean = 3.66±0.59) than the students in general education (Mean = 3.16±0.91). The students in general education were slightly more likely to use the organized studying (Mean = 3.44±0.90) than the medical students (Mean =3.23±0.90). Both medical students and the students in general education tended to use the surface approaches along with other approaches to studying. There was not a great difference between the medical students and the students pursuing general education with regard to perceptions of the learning environment and approaches to learning.

  12. CLAS App ML

    NARCIS (Netherlands)

    Maher, Bridget; Hartkopf, Kathleen; Stieger, Lina; Schroeder, Hanna; Sopka, Sasa; Orrego, Carola; Drachsler, Hendrik

    2014-01-01

    This is a multi-language (ML) update of the CLAS App original design by Bridget Maher from the School of Medicine at University College Cork, Ireland. The current version has an improve counting mechanism and has been translated from English to Spanish, Catalan and German languages within the

  13. Towards a Standards-Based Approach to E-Learning Personalization Using Reusable Learning Objects.

    Science.gov (United States)

    Conlan, Owen; Dagger, Declan; Wade, Vincent

    E-Learning systems that produce personalized course offerings for the learner are often expensive, both from a time and financial perspective, to develop and maintain. Learning content personalized to a learners' cognitive preferences has been shown to produce more effective learning, however many approaches to realizing this form of…

  14. Content-Based Instruction Approach In Instructional Multimedia For English Learning

    OpenAIRE

    Farani, Rizki

    2016-01-01

    Content-based Instruction (CBI) is an approach in English learning that integrates certain topic and English learning objectives. This approach focuses on using English competencies as a “bridge” to comprehend certain topic or theme in English. Nowadays, this approach can be used in instructional multimedia to support English learning by using computer. Instructional multimedia with computer system refers to the sequential or simultaneous use of variety of media formats in a given presentatio...

  15. Absorption kinetics of two highly concentrated preparations of growth hormone: 12 IU/ml compared to 56 IU/ml

    DEFF Research Database (Denmark)

    Laursen, Torben; Susgaard, Søren; Jensen, Flemming Steen

    1994-01-01

    was to compare the relative bioavailability of two highly concentrated (12 IU/ml versus 56 IU/ml) formulations of biosynthetic human growth hormone administered subcutaneously. After pretreatment with growth hormone for at least four weeks, nine growth hormone deficient patients with a mean age of 26.2 years......AbstractSend to: Pharmacol Toxicol. 1994 Jan;74(1):54-7. Absorption kinetics of two highly concentrated preparations of growth hormone: 12 IU/ml compared to 56 IU/ml. Laursen T1, Susgaard S, Jensen FS, Jørgensen JO, Christiansen JS. Author information Abstract The purpose of this study...... (range 17-43) were studied two times in a randomized design, the two studies being separated by at least one week. At the start of each study period (7 p.m.), growth hormone was injected subcutaneously in a dosage of 3 IU/m2. The 12 IU/ml preparation of growth hormone was administered on one occasion...

  16. Comparative study of induction of labour with Foley’s catheter inflated to 30 mL versus 60 mL

    OpenAIRE

    Indira I; Latha G; Lakshmi Narayanamma V

    2016-01-01

    Background: The ripeness of the cervix is an important determinant of the success of induction of labour. One of the mechanical methods of cervical ripening is the use of a transcervical Foley catheter. In this study we compared the efficacy in induction of labour of two insufflation volumes of Foley catheter bulb 30 mL and 60mL. Methods: This was a randomized, single-blind study conducted in 100 women, randomly allocated to the 30 mL group (n=50) and 60 mL group (n=50). Foley’s cath...

  17. Machine learning of parameters for accurate semiempirical quantum chemical calculations

    International Nuclear Information System (INIS)

    Dral, Pavlo O.; Lilienfeld, O. Anatole von; Thiel, Walter

    2015-01-01

    We investigate possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods through the use of machine learning (ML) models for the parameters. For a given class of compounds, ML techniques require sufficiently large training sets to develop ML models that can be used for adapting SQC parameters to reflect changes in molecular composition and geometry. The ML-SQC approach allows the automatic tuning of SQC parameters for individual molecules, thereby improving the accuracy without deteriorating transferability to molecules with molecular descriptors very different from those in the training set. The performance of this approach is demonstrated for the semiempirical OM2 method using a set of 6095 constitutional isomers C 7 H 10 O 2 , for which accurate ab initio atomization enthalpies are available. The ML-OM2 results show improved average accuracy and a much reduced error range compared with those of standard OM2 results, with mean absolute errors in atomization enthalpies dropping from 6.3 to 1.7 kcal/mol. They are also found to be superior to the results from specific OM2 reparameterizations (rOM2) for the same set of isomers. The ML-SQC approach thus holds promise for fast and reasonably accurate high-throughput screening of materials and molecules

  18. Hong Kong Students' Approaches to Learning: Cross-Cultural Comparisons

    Science.gov (United States)

    Dasari, Bhoomiah

    2009-01-01

    Anecdotal evidence abounds in Hong Kong to the effect that students entering tertiary education are predisposed to a "rote" learning approach. With the internalisation of higher education in many countries, there is still insufficient understanding of how Chinese students approach their learning. Except few studies were conducted…

  19. Description of the sodium loop ML-3

    International Nuclear Information System (INIS)

    Torre, de la M.; Melches, I; Lapena, J.; Martinez, T.A.; Miguel, de D.; Duran, F.

    1979-01-01

    The sodium loop ML-3 is described. The main objective of this facility is to obtain mechanical property data for LMFBR materials in creep and low cycle fatigue testing in flowing sodium. ML-3 includes 10 test stations for creep and two for fatigue. It is possible to operate simultaneously at three different temperature levels. The maximum operating temperature is 650 deg C at flow velocities up to 5 m/s. The ML-3 loop has been located in a manner that permits the fill/dump tank cover gas and security systems to be shared with an earlier circuit, the ML-1. (author)

  20. Comparison of student's learning achievement through realistic mathematics education (RME) approach and problem solving approach on grade VII

    Science.gov (United States)

    Ilyas, Muhammad; Salwah

    2017-02-01

    The type of this research was experiment. The purpose of this study was to determine the difference and the quality of student's learning achievement between students who obtained learning through Realistic Mathematics Education (RME) approach and students who obtained learning through problem solving approach. This study was a quasi-experimental research with non-equivalent experiment group design. The population of this study was all students of grade VII in one of junior high school in Palopo, in the second semester of academic year 2015/2016. Two classes were selected purposively as sample of research that was: year VII-5 as many as 28 students were selected as experiment group I and VII-6 as many as 23 students were selected as experiment group II. Treatment that used in the experiment group I was learning by RME Approach, whereas in the experiment group II by problem solving approach. Technique of data collection in this study gave pretest and posttest to students. The analysis used in this research was an analysis of descriptive statistics and analysis of inferential statistics using t-test. Based on the analysis of descriptive statistics, it can be concluded that the average score of students' mathematics learning after taught using problem solving approach was similar to the average results of students' mathematics learning after taught using realistic mathematics education (RME) approach, which are both at the high category. In addition, It can also be concluded that; (1) there was no difference in the results of students' mathematics learning taught using realistic mathematics education (RME) approach and students who taught using problem solving approach, (2) quality of learning achievement of students who received RME approach and problem solving approach learning was same, which was at the high category.

  1. ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

    Science.gov (United States)

    Bittig, Arne T; Uhrmacher, Adelinde M

    2017-01-01

    Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

  2. Can Learning Motivation Predict Learning Achievement? A Case Study of a Mobile Game-Based English Learning Approach

    Science.gov (United States)

    Tsai, Chia-Hui; Cheng, Ching-Hsue; Yeh, Duen-Yian; Lin, Shih-Yun

    2017-01-01

    This study applied a quasi-experimental design to investigate the influence and predictive power of learner motivation for achievement, employing a mobile game-based English learning approach. A system called the Happy English Learning System, integrating learning material into a game-based context, was constructed and installed on mobile devices…

  3. The Effects of Brain Based Learning Approach on Motivation and Students Achievement in Mathematics Learning

    Science.gov (United States)

    Mekarina, M.; Ningsih, Y. P.

    2017-09-01

    This classroom action research is based by the facts that the students motivation and achievement mathematics learning is less. One of the factors causing is learning that does not provide flexibility to students to empower the potential of the brain optimally. The aim of this research was to improve the student motivation and achievement in mathematics learning by implementing brain based learning approach. The subject of this research was student of grade XI in senior high school. The research consisted of two cycles. Data of student achievement from test, and the student motivation through questionnaire. Furthermore, the finding of this research showed the result of the analysis was the implementation of brain based learning approach can improve student’s achievement and motivation in mathematics learning.

  4. M&C ML: A modeling language for monitoring and control systems

    Energy Technology Data Exchange (ETDEWEB)

    Patwari, Puneet, E-mail: patwari.puneet@tcs.com; Chaudhuri, Subhrojyoti Roy; Natarajan, Swaminathan; Muralikrishna, G

    2016-11-15

    Highlights: • It is challenging to maintain consistency in the current approach to M&C design. • Based on similarity across various projects, it looks ideal to propose a solution at domain level. • Approach to create a DSL for M&C involves viewing a system through lenses of various domains. • M&CML provides a standard vocabulary and the entire process of M&C solution creation domain-aware. • M&CML provides a holistic view of control architecture. • M&CML has support for inherent consistency checks, user assistance and third party support. - Abstract: The use of System Engineering (SE) language such as SysML [1,20] is common within the community of control system designers. However the design handoff to the subsequent phases of the control system development is carried out manually in most cases without much tool support. The approach to agreeing on the control interface between components is a good example where engineers still rely on either manually created Interface Control Documents (ICD) or one off tools implemented by individual projects. Square Kilometer Array (SKA) [2] and International Thermonuclear Experimental Reactor (ITER) [3] are two good examples of such large projects adopting these approaches. This results in non-uniformity in the overall system design since individual groups invent their own vocabulary while using a language like SysML which leads to inconsistencies across the design, interface and realized code. To mitigate this, we propose the development of a Monitoring and Control Modeling Language (M&CML), a domain specific language (DSL) [4,22] for specifying M&C solutions. M&C ML starts with defining a vocabulary borrowing concepts from standard practices used in the control domain and incorporates a language which ensures uniformity and consistency across the M&C design, interfaces and implementation artifacts. In this paper we discuss this language with an analysis of its usage to point out its benefits.

  5. M&C ML: A modeling language for monitoring and control systems

    International Nuclear Information System (INIS)

    Patwari, Puneet; Chaudhuri, Subhrojyoti Roy; Natarajan, Swaminathan; Muralikrishna, G

    2016-01-01

    Highlights: • It is challenging to maintain consistency in the current approach to M&C design. • Based on similarity across various projects, it looks ideal to propose a solution at domain level. • Approach to create a DSL for M&C involves viewing a system through lenses of various domains. • M&CML provides a standard vocabulary and the entire process of M&C solution creation domain-aware. • M&CML provides a holistic view of control architecture. • M&CML has support for inherent consistency checks, user assistance and third party support. - Abstract: The use of System Engineering (SE) language such as SysML [1,20] is common within the community of control system designers. However the design handoff to the subsequent phases of the control system development is carried out manually in most cases without much tool support. The approach to agreeing on the control interface between components is a good example where engineers still rely on either manually created Interface Control Documents (ICD) or one off tools implemented by individual projects. Square Kilometer Array (SKA) [2] and International Thermonuclear Experimental Reactor (ITER) [3] are two good examples of such large projects adopting these approaches. This results in non-uniformity in the overall system design since individual groups invent their own vocabulary while using a language like SysML which leads to inconsistencies across the design, interface and realized code. To mitigate this, we propose the development of a Monitoring and Control Modeling Language (M&CML), a domain specific language (DSL) [4,22] for specifying M&C solutions. M&C ML starts with defining a vocabulary borrowing concepts from standard practices used in the control domain and incorporates a language which ensures uniformity and consistency across the M&C design, interfaces and implementation artifacts. In this paper we discuss this language with an analysis of its usage to point out its benefits.

  6. E-Learning Approach in Teacher Training

    Directory of Open Access Journals (Sweden)

    A. Seda YUCEL

    2006-10-01

    Full Text Available There has been an increasing interest in e-learning in teacher training at universities during the last ten years. With the developing technology, educational methods have differed as well as many other processes. Firstly, a definition on e-learning as a new approach should be given. E-learning could shortly be defined as a web-based educational system on platform with Internet, Intranet or computer access. The concept of e-learning has two main subtitles as synchronized (where a group of students and an instructor actualize an online conference meeting in a computer environment an asynchronized (where individuals actualize self-training in computer environments. Students have access to the course contents whenever they want and communicate with their peers or teachers via communication tools such as e-mail and forums. In order the distance learning system to succeed in e-learning, the program should be planned as both synchronized and asynchronized.

  7. Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data

    Directory of Open Access Journals (Sweden)

    Laura Cornejo-Bueno

    2017-11-01

    Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.

  8. Multivariate Analysis and Machine Learning in Cerebral Palsy Research.

    Science.gov (United States)

    Zhang, Jing

    2017-01-01

    Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.

  9. Enhancing the Teaching-Learning Process: A Knowledge Management Approach

    Science.gov (United States)

    Bhusry, Mamta; Ranjan, Jayanthi

    2012-01-01

    Purpose: The purpose of this paper is to emphasize the need for knowledge management (KM) in the teaching-learning process in technical educational institutions (TEIs) in India, and to assert the impact of information technology (IT) based KM intervention in the teaching-learning process. Design/methodology/approach: The approach of the paper is…

  10. Developing Learning Scenarios for Educational Web Radio: a Learning Design Approach

    DEFF Research Database (Denmark)

    Triantafyllou, Evangelia; Liokou, Effrosyni; Economou, Anastasia

    2018-01-01

    schools. In this paper, we present a survey study that aimed to evaluate a Visual Learning Design (VLD) approach for developing educational scenari-os in web radio. The study results indicated that the VLD approach helped teachers to think about the educational aspects of the web radio production...

  11. A Bayesian Developmental Approach to Robotic Goal-Based Imitation Learning.

    Directory of Open Access Journals (Sweden)

    Michael Jae-Yoon Chung

    Full Text Available A fundamental challenge in robotics today is building robots that can learn new skills by observing humans and imitating human actions. We propose a new Bayesian approach to robotic learning by imitation inspired by the developmental hypothesis that children use self-experience to bootstrap the process of intention recognition and goal-based imitation. Our approach allows an autonomous agent to: (i learn probabilistic models of actions through self-discovery and experience, (ii utilize these learned models for inferring the goals of human actions, and (iii perform goal-based imitation for robotic learning and human-robot collaboration. Such an approach allows a robot to leverage its increasing repertoire of learned behaviors to interpret increasingly complex human actions and use the inferred goals for imitation, even when the robot has very different actuators from humans. We demonstrate our approach using two different scenarios: (i a simulated robot that learns human-like gaze following behavior, and (ii a robot that learns to imitate human actions in a tabletop organization task. In both cases, the agent learns a probabilistic model of its own actions, and uses this model for goal inference and goal-based imitation. We also show that the robotic agent can use its probabilistic model to seek human assistance when it recognizes that its inferred actions are too uncertain, risky, or impossible to perform, thereby opening the door to human-robot collaboration.

  12. Artificial neuron-glia networks learning approach based on cooperative coevolution.

    Science.gov (United States)

    Mesejo, Pablo; Ibáñez, Oscar; Fernández-Blanco, Enrique; Cedrón, Francisco; Pazos, Alejandro; Porto-Pazos, Ana B

    2015-06-01

    Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and astrocytic networks in the most evolved living organisms. Although ANGNs are not a consolidated method, their performance against the traditional approach, i.e. without artificial astrocytes, was already demonstrated on classification problems. However, the corresponding learning algorithms developed so far strongly depends on a set of glial parameters which are manually tuned for each specific problem. As a consequence, previous experimental tests have to be done in order to determine an adequate set of values, making such manual parameter configuration time-consuming, error-prone, biased and problem dependent. Thus, in this paper, we propose a novel learning approach for ANGNs that fully automates the learning process, and gives the possibility of testing any kind of reasonable parameter configuration for each specific problem. This new learning algorithm, based on coevolutionary genetic algorithms, is able to properly learn all the ANGNs parameters. Its performance is tested on five classification problems achieving significantly better results than ANGN and competitive results with ANN approaches.

  13. A Professional Learning Community Approach

    African Journals Online (AJOL)

    This paper provides insights into how Life Sciences teachers in the Eastern Cape can be supported through professional learning communities (PLCs) as a potential approach to enhancing their biodiversity knowledge. PLCs are communities that provide the setting and necessary support for groups of classroom teachers to ...

  14. Influence of open- and closed-book tests on medical students' learning approaches

    NARCIS (Netherlands)

    Heijne-Penninga, Marjolein; Kuks, Jan B. M.; Hofman, W. H. Adriaan; Cohen-Schotanus, Janke

    2008-01-01

    CONTEXT Two learning approaches are consistently distinguished in the literature: deep and surface learning. The deep learning approach is considered preferable. Open-book tests are expected to stimulate deep learning and to offer a possible way of handling the substantial growth in medical

  15. Comparison: Mediation Solutions of WSMOLX and WebML/WebRatio

    Science.gov (United States)

    Zaremba, Maciej; Zaharia, Raluca; Turati, Andrea; Brambilla, Marco; Vitvar, Tomas; Ceri, Stefano

    In this chapter we compare the WSMO/WSML/WSMX andWebML/WebRatio approaches to the SWS-Challenge workshop mediation scenario in terms of the utilized underlying technologies and delivered solutions. In the mediation scenario one partner uses Roset-taNet to define its B2B protocol while the other one operates on a proprietary solution. Both teams shown how these partners could be semantically integrated.

  16. The relationship between learning preferences (styles and approaches) and learning outcomes among pre-clinical undergraduate medical students

    OpenAIRE

    Liew, Siaw-Cheok; Sidhu, Jagmohni; Barua, Ankur

    2015-01-01

    Background Learning styles and approaches of individual undergraduate medical students vary considerably and as a consequence, their learning needs also differ from one student to another. This study was conducted to identify different learning styles and approaches of pre-clinical, undergraduate medical students and also to determine the relationships of learning preferences with performances in the summative examinations. Methods A cross-sectional study was conducted among randomly selected...

  17. Relationship between motivational goal orientations, perceptions of general education classroom learning environment, and deep approaches to learning

    OpenAIRE

    Chanut Poondej; Thanita Lerdpornkulrat

    2016-01-01

    Researchers have reported empirical evidence that the deep approaches to learning account for significant successful learning. The present study aimed to investigate the relationship between students' motivational goal orientation, their perceptions of the general education classroom learning environment, and deep approaches to learning strategies. Participants (N = 494) were first- and second-year college students enrolled in any of the general education courses in higher education in Thaila...

  18. An Expert System-based Context-Aware Ubiquitous Learning Approach for Conducting Science Learning Activities

    Science.gov (United States)

    Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Wen-Hung

    2013-01-01

    Context-aware ubiquitous learning has been recognized as being a promising approach that enables students to interact with real-world learning targets with supports from the digital world. Several researchers have indicated the importance of providing learning guidance or hints to individual students during the context-aware ubiquitous learning…

  19. The Activity Theory Approach to Learning

    Directory of Open Access Journals (Sweden)

    Ritva Engeström

    2014-12-01

    Full Text Available In this paper the author offers a practical view of the theory-grounded research on education action. She draws on studies carried out at the Center for Research on Activity, Development and Learning (CRADLE at the University of Helsinki in Finland. In its work, the Center draws on cultural-historical activity theory (CHAT and is well-known for the theory of Expansive Learning and its more practical application called Developmental Work Research (DWR. These approaches are widely used to understand professional learning and have served as a theoreticaland methodological foundation for studies examining change and professional development in various human activities.

  20. QuakeML - An XML Schema for Seismology

    Science.gov (United States)

    Wyss, A.; Schorlemmer, D.; Maraini, S.; Baer, M.; Wiemer, S.

    2004-12-01

    We propose an extensible format-definition for seismic data (QuakeML). Sharing data and seismic information efficiently is one of the most important issues for research and observational seismology in the future. The eXtensible Markup Language (XML) is playing an increasingly important role in the exchange of a variety of data. Due to its extensible definition capabilities, its wide acceptance and the existing large number of utilities and libraries for XML, a structured representation of various types of seismological data should in our opinion be developed by defining a 'QuakeML' standard. Here we present the QuakeML definitions for parameter databases and further efforts, e.g. a central QuakeML catalog database and a web portal for exchanging codes and stylesheets.

  1. The FITS model: an improved Learning by Design approach

    NARCIS (Netherlands)

    Drs. Ing. Koen Michels; Prof. Dr. Marc de Vries; MEd Dave van Breukelen; MEd Frank Schure

    2016-01-01

    Learning by Design (LBD) is a project-based inquiry approach for interdisciplinary teaching that uses design contexts to learn skills and conceptual knowledge. Research around the year 2000 showed that LBD students achieved high skill performances but disappointing conceptual learning gains. A

  2. A Multi-Faceted Approach to Inquiry-Based Learning

    Science.gov (United States)

    Brudzinski, M. R.; Sikorski, J.

    2009-12-01

    In order to fully attain the benefits of inquiry-based learning, instructors who typically employ the traditional lecture format need to make several adjustments to their approach. This change in styles can be intimidating and logistically difficult to overcome. A stepwise approach to this transformation is likely to be more manageable for individual faculty or departments. In this session, we will describe several features that we are implementing in our introductory geology course with the ultimate goal of converting to an entirely inquiry-based approach. Our project is part of the Miami University initiative in the top 25 enrolled courses to move towards the “student as scholar” model for engaged learning. Some of the features we developed for our course include: student learning outcomes, student development outcomes, out-of-class content quizzes, in-class conceptests, pre-/post-course assessment, reflective knowledge surveys, and daily group activities.

  3. Synthesizing Technology Adoption and Learners' Approaches towards Active Learning in Higher Education

    Science.gov (United States)

    Chan, Kevin; Cheung, George; Wan, Kelvin; Brown, Ian; Luk, Green

    2015-01-01

    In understanding how active and blended learning approaches with learning technologies engagement in undergraduate education, current research models tend to undermine the effect of learners' variations, particularly regarding their styles and approaches to learning, on intention and use of learning technologies. This study contributes to further…

  4. Approaches to learning, need for cognition, and strategic flexibility among university students.

    Science.gov (United States)

    Evans, Christina J; Kirby, John R; Fabrigar, Leandre R

    2003-12-01

    Considerable research has described students' deep and surface approaches to learning. Other research has described individuals' self-regulated learning and need for cognition. There is a need for research examining the relationships among these constructs. This study explored relationships among approaches to learning (deep, surface), need for cognition, and three types of control of learning (adaptive, inflexible, irresolute). Theory suggested similarities among the deep approach, need for cognition, and adaptive control (aspects of self-regulated learning); and among surface, inflexible, and irresolute control (aspects of an ineffective approach to learning). One-factor and two-factor models were proposed. Participants were 226 Canadian military college students. Participants completed the following questionnaires: the Study Process Questionnaire (Biggs, 1978), the Need for Cognition Scale (Cacioppo & Petty, 1982), and the Strategic Flexibility Questionnaire (Cantwell & Moore, 1996). Confirmatory factor analysis supported the identification of the six scale factors. Second order confirmatory factor analysis indicated three factors representing constructs underlying these factors. Neither the one- nor two-factor models accounted adequately for the data. Self-regulated learning was defined by measures of the deep approach to learning, need for cognition, and adaptive control of learning. The second factor divided into one factor consisting of irresolute control, the surface approach, and negative need for cognition; and another consisting of inflexible and negative adaptive control. Substantial relationships among scales support the need for further theory development.

  5. Proceedings ML Family/OCaml Users and Developers workshops

    OpenAIRE

    Kiselyov, Oleg; Garrigue, Jacques

    2015-01-01

    This volume collects the extended versions of selected papers originally presented at the two ACM SIGPLAN workshops: ML Family Workshop 2014 and OCaml 2014. Both were affiliated with ICFP 2014 and took place on two consecutive days, on September 4 and 5, 2014 in Gothenburg, Sweden. The ML Family workshop aims to recognize the entire extended family of ML and ML-like languages: languages that are Higher-order, Typed, Inferred, and Strict. It provides the forum to discuss common issues, both pr...

  6. The wonder approach to learning

    Directory of Open Access Journals (Sweden)

    Catherine eL'Ecuyer

    2014-10-01

    Full Text Available Wonder, innate in the child, is an inner desire to learn that awaits reality in order to be awakened. Wonder is at the origin of reality-based consciousness, thus of learning. The scope of wonder, which occurs at a metaphysical level, is greater than that of curiosity. Unfortunate misinterpretations of neuroscience have led to false brain-based ideas in the field of education, all of these based on the scientifically wrong assumption that children’s learning depends on an enriched environment. These beliefs have re-enforced the Behaviorist Approach to education and to parenting and have contributed to deadening our children’s sense of wonder. We suggest wonder as the center of all motivation and action in the child. Wonder is what makes life genuinely personal. Beauty is what triggers wonder. Wonder attunes to beauty through sensitivity and is unfolded by attachment. When wonder, beauty, sensitivity and secure attachment are present, learning is meaningful.On the contrary, when there is no volitional dimension involved (no wonder, no end or meaning (no beauty and no trusting predisposition (secure attachment, the rigid and limiting mechanical process of so-called learning through mere repetition become a deadening and alienating routine. This could be described as training, not as learning, because it does not contemplate the human being as a whole.

  7. Meaningful Learning in the Teaching of Culture: The Project Based Learning Approach

    Science.gov (United States)

    Kean, Ang Chooi; Kwe, Ngu Moi

    2014-01-01

    This paper reports on a collaborative effort taken by a team of three teacher educators in using the Project Based Learning (PBL) approach in the teaching of Japanese culture with the aim to investigate the presence of actual "meaningful learning" among 15 students of a 12-Week Preparatory Japanese Language course under a teacher…

  8. Advancing the skill set of SCM graduates – An active learning approach

    NARCIS (Netherlands)

    Scholten, Kirstin; Dubois, Anna

    2017-01-01

    Purpose Drawing on a novel approach to active learning in supply chain management, the purpose of this paper is to describe and analyze how the students’ learning process as well as their learning outcomes are influenced by the learning and teaching contexts. Design/methodology/approach A case study

  9. Advancing the skill set of SCM graduates – An active learning approach

    NARCIS (Netherlands)

    Scholten, Kirstin; Dubois, Anna

    Purpose Drawing on a novel approach to active learning in supply chain management, the purpose of this paper is to describe and analyze how the students’ learning process as well as their learning outcomes are influenced by the learning and teaching contexts. Design/methodology/approach A case study

  10. The study of effectiveness of blended learning approach for medical training courses.

    Science.gov (United States)

    Karamizadeh, Z; Zarifsanayei, N; Faghihi, A A; Mohammadi, H; Habibi, M

    2012-01-01

    Blended learning as a method of learning that includes face to face learning, pure E-learning and didactic learning. This study aims to investigate the efficacy of medical education by this approach. This interventional study was performed in 130 students at different clinical levels participating in class sessions on "congenital adrenal hyperplasia and ambiguous genitalia". Sampling was done gradually during 6 months and all of them filled a pretest questionnaire and received an educational compact disk. One week later, a presence class session was held in a question and answer and problem solving method. Two to four weeks later, they filled a posttest questionnaire. There was a significant correlation between pretest and posttest scores and the posttest scores were significantly more than the pretest ones. Sub-specialized residents had the most and the students had the least attitude towards blended learning approach. There was a significant correlation between the research samples' accessibility to computer and their attitude and satisfaction to blended learning approach. Findings generally showed that the blended learning was an effective approach in making a profound learning of academic subjects.

  11. Dental students' perception of their approaches to learning in a PBL programme.

    Science.gov (United States)

    Haghparast, H; Ghorbani, A; Rohlin, M

    2017-08-01

    To compare dental students' perceptions of their learning approaches between different years of a problem-based learning (PBL) programme. The hypothesis was that in a comparison between senior and junior students, the senior students would perceive themselves as having a higher level of deep learning approach and a lower level of surface learning approach than junior students would. This hypothesis was based on the fact that senior students have longer experience of a student-centred educational context, which is supposed to underpin student learning. Students of three cohorts (first year, third year and fifth year) of a PBL-based dental programme were asked to respond to a questionnaire (R-SPQ-2F) developed to analyse students' learning approaches, that is deep approach and surface approach, using four subscales including deep strategy, surface strategy, deep motive and surface motive. The results of the three cohorts were compared using a one-way analysis of variance (ANOVA). A P-value was set at approach than the first-year students (P = 0.020). There was a significant decrease in surface strategy from the first to the fifth year (P = 0.003). No differences were found concerning deep approach or its subscales (deep strategy and deep motive) between the mean scores of the three cohorts. The results did not show the expected increased depth in learning approaches over the programme years. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  12. The colloquial approach: An active learning technique

    Science.gov (United States)

    Arce, Pedro

    1994-09-01

    This paper addresses the very important problem of the effectiveness of teaching methodologies in fundamental engineering courses such as transport phenomena. An active learning strategy, termed the colloquial approach, is proposed in order to increase student involvement in the learning process. This methodology is a considerable departure from traditional methods that use solo lecturing. It is based on guided discussions, and it promotes student understanding of new concepts by directing the student to construct new ideas by building upon the current knowledge and by focusing on key cases that capture the essential aspects of new concepts. The colloquial approach motivates the student to participate in discussions, to develop detailed notes, and to design (or construct) his or her own explanation for a given problem. This paper discusses the main features of the colloquial approach within the framework of other current and previous techniques. Problem-solving strategies and the need for new textbooks and for future investigations based on the colloquial approach are also outlined.

  13. Family, Learning Environments, Learning Approaches, and Student Outcomes in a Malaysian Private University

    Science.gov (United States)

    Kek, Megan A. Yih Chyn; Darmawan, I. Gusti Ngurah; Chen, Yu Sui

    2007-01-01

    This article presents the quantitative findings from a mixed methods study of students and faculty at a private medical university in Malaysia. In particular, the relationships among students' individual characteristics, general self-efficacy, family context, university and classroom learning environments, curriculum, approaches to learning, and…

  14. Actively Teaching Research Methods with a Process Oriented Guided Inquiry Learning Approach

    Science.gov (United States)

    Mullins, Mary H.

    2017-01-01

    Active learning approaches have shown to improve student learning outcomes and improve the experience of students in the classroom. This article compares a Process Oriented Guided Inquiry Learning style approach to a more traditional teaching method in an undergraduate research methods course. Moving from a more traditional learning environment to…

  15. Variability in University Students' Use of Technology: An "Approaches to Learning" Perspective

    Science.gov (United States)

    Mimirinis, Mike

    2016-01-01

    This study reports the results of a cross-case study analysis of how students' approaches to learning are demonstrated in blended learning environments. It was initially propositioned that approaches to learning as key determinants of the quality of student learning outcomes are demonstrated specifically in how students utilise technology in…

  16. Contextual Teaching and Learning Approach of Mathematics in Primary Schools

    Science.gov (United States)

    Selvianiresa, D.; Prabawanto, S.

    2017-09-01

    The Contextual Teaching and Learning (CTL) approach is an approach involving active students in the learning process to discover the concepts learned through to knowledge and experience of the students. Similar to Piaget’s opinion that learning gives students an actives trying to do new things by relating their experiences and building their own minds. When students to connecting mathematics with real life, then students can looking between a conceptual to be learned with a concept that has been studied. So that, students can developing of mathematical connection ability. This research is quasi experiment with a primary school in the city of Kuningan. The result showed that CTL learning can be successful, when learning used a collaborative interaction with students, a high level of activity in the lesson, a connection to real-world contexts, and an integration of science content with other content and skill areas. Therefore, CTL learning can be applied by techer to mathematics learning in primary schools.

  17. Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods.

    Directory of Open Access Journals (Sweden)

    Philippe Burlina

    Full Text Available To evaluate the use of ultrasound coupled with machine learning (ML and deep learning (DL techniques for automated or semi-automated classification of myositis.Eighty subjects comprised of 19 with inclusion body myositis (IBM, 14 with polymyositis (PM, 14 with dermatomyositis (DM, and 33 normal (N subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally were acquired. We considered three problems of classification including (A normal vs. affected (DM, PM, IBM; (B normal vs. IBM patients; and (C IBM vs. other types of myositis (DM or PM. We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification.The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A, 86.6% ± 2.4% for (B and 74.8% ± 3.9% for (C, while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A, 84.3% ± 2.3% for (B and 68.9% ± 2.5% for (C.This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.

  18. Automated diagnosis of myositis from muscle ultrasound: Exploring the use of machine learning and deep learning methods.

    Science.gov (United States)

    Burlina, Philippe; Billings, Seth; Joshi, Neil; Albayda, Jemima

    2017-01-01

    To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.

  19. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Ling-Yu Duan

    2010-01-01

    Full Text Available Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  20. Per-Sample Multiple Kernel Approach for Visual Concept Learning

    Directory of Open Access Journals (Sweden)

    Tian Yonghong

    2010-01-01

    Full Text Available Abstract Learning visual concepts from images is an important yet challenging problem in computer vision and multimedia research areas. Multiple kernel learning (MKL methods have shown great advantages in visual concept learning. As a visual concept often exhibits great appearance variance, a canonical MKL approach may not generate satisfactory results when a uniform kernel combination is applied over the input space. In this paper, we propose a per-sample multiple kernel learning (PS-MKL approach to take into account intraclass diversity for improving discrimination. PS-MKL determines sample-wise kernel weights according to kernel functions and training samples. Kernel weights as well as kernel-based classifiers are jointly learned. For efficient learning, PS-MKL employs a sample selection strategy. Extensive experiments are carried out over three benchmarking datasets of different characteristics including Caltech101, WikipediaMM, and Pascal VOC'07. PS-MKL has achieved encouraging performance, comparable to the state of the art, which has outperformed a canonical MKL.

  1. Harnessing the Power of Learning Management Systems: An E-Learning Approach for Professional Development.

    Science.gov (United States)

    White, Meagan; Shellenbarger, Teresa

    E-learning provides an alternative approach to traditional professional development activities. A learning management system may help nursing professional development practitioners deliver content more efficiently and effectively; however, careful consideration is needed during planning and implementation. This article provides essential information in the selection and use of a learning management system for professional development.

  2. MOOC Design – Dissemination to the Masses or Facilitation of Social Learning and a Deep Approach to Learning?

    DEFF Research Database (Denmark)

    Christensen, Inger-Marie F.; Dam Laursen, Mette; Bøggild, Jacob

    2016-01-01

    This article accounts for the design of the massive open online course (MOOC) Hans Christian Andersen’s Fairy tales on FutureLearn and reports on the effectiveness of this design in terms of engaging learners in social learning and encouraging a deep approach to learning. A learning pathway...... and increased educator feedback. Course data show that that some learners use the space provided for social interaction and mutual support. A learning pathway that engages learners in discussion and progression from week to week facilitates a deep approach to learning. However, this requires more support from...

  3. Machine Learning for High-Throughput Stress Phenotyping in Plants.

    Science.gov (United States)

    Singh, Arti; Ganapathysubramanian, Baskar; Singh, Asheesh Kumar; Sarkar, Soumik

    2016-02-01

    Advances in automated and high-throughput imaging technologies have resulted in a deluge of high-resolution images and sensor data of plants. However, extracting patterns and features from this large corpus of data requires the use of machine learning (ML) tools to enable data assimilation and feature identification for stress phenotyping. Four stages of the decision cycle in plant stress phenotyping and plant breeding activities where different ML approaches can be deployed are (i) identification, (ii) classification, (iii) quantification, and (iv) prediction (ICQP). We provide here a comprehensive overview and user-friendly taxonomy of ML tools to enable the plant community to correctly and easily apply the appropriate ML tools and best-practice guidelines for various biotic and abiotic stress traits. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Quantum machine learning: a classical perspective

    Science.gov (United States)

    Ciliberto, Carlo; Herbster, Mark; Ialongo, Alessandro Davide; Pontil, Massimiliano; Severini, Simone; Wossnig, Leonard

    2018-01-01

    Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning (ML) techniques to impressive results in regression, classification, data generation and reinforcement learning tasks. Despite these successes, the proximity to the physical limits of chip fabrication alongside the increasing size of datasets is motivating a growing number of researchers to explore the possibility of harnessing the power of quantum computation to speed up classical ML algorithms. Here we review the literature in quantum ML and discuss perspectives for a mixed readership of classical ML and quantum computation experts. Particular emphasis will be placed on clarifying the limitations of quantum algorithms, how they compare with their best classical counterparts and why quantum resources are expected to provide advantages for learning problems. Learning in the presence of noise and certain computationally hard problems in ML are identified as promising directions for the field. Practical questions, such as how to upload classical data into quantum form, will also be addressed. PMID:29434508

  5. Quantum machine learning: a classical perspective.

    Science.gov (United States)

    Ciliberto, Carlo; Herbster, Mark; Ialongo, Alessandro Davide; Pontil, Massimiliano; Rocchetto, Andrea; Severini, Simone; Wossnig, Leonard

    2018-01-01

    Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning (ML) techniques to impressive results in regression, classification, data generation and reinforcement learning tasks. Despite these successes, the proximity to the physical limits of chip fabrication alongside the increasing size of datasets is motivating a growing number of researchers to explore the possibility of harnessing the power of quantum computation to speed up classical ML algorithms. Here we review the literature in quantum ML and discuss perspectives for a mixed readership of classical ML and quantum computation experts. Particular emphasis will be placed on clarifying the limitations of quantum algorithms, how they compare with their best classical counterparts and why quantum resources are expected to provide advantages for learning problems. Learning in the presence of noise and certain computationally hard problems in ML are identified as promising directions for the field. Practical questions, such as how to upload classical data into quantum form, will also be addressed.

  6. Quantum machine learning: a classical perspective

    Science.gov (United States)

    Ciliberto, Carlo; Herbster, Mark; Ialongo, Alessandro Davide; Pontil, Massimiliano; Rocchetto, Andrea; Severini, Simone; Wossnig, Leonard

    2018-01-01

    Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning (ML) techniques to impressive results in regression, classification, data generation and reinforcement learning tasks. Despite these successes, the proximity to the physical limits of chip fabrication alongside the increasing size of datasets is motivating a growing number of researchers to explore the possibility of harnessing the power of quantum computation to speed up classical ML algorithms. Here we review the literature in quantum ML and discuss perspectives for a mixed readership of classical ML and quantum computation experts. Particular emphasis will be placed on clarifying the limitations of quantum algorithms, how they compare with their best classical counterparts and why quantum resources are expected to provide advantages for learning problems. Learning in the presence of noise and certain computationally hard problems in ML are identified as promising directions for the field. Practical questions, such as how to upload classical data into quantum form, will also be addressed.

  7. Learning Behavior and Achievement Analysis of a Digital Game-Based Learning Approach Integrating Mastery Learning Theory and Different Feedback Models

    Science.gov (United States)

    Yang, Kai-Hsiang

    2017-01-01

    It is widely accepted that the digital game-based learning approach has the advantage of stimulating students' learning motivation, but simply using digital games in the classroom does not guarantee satisfactory learning achievement, especially in the case of the absence of a teacher. Integrating appropriate learning strategies into a game can…

  8. Student-Centred Learning Environments: An Investigation into Student Teachers' Instructional Preferences and Approaches to Learning

    Science.gov (United States)

    Baeten, Marlies; Dochy, Filip; Struyven, Katrien; Parmentier, Emmeline; Vanderbruggen, Anne

    2016-01-01

    The use of student-centred learning environments in education has increased. This study investigated student teachers' instructional preferences for these learning environments and how these preferences are related to their approaches to learning. Participants were professional Bachelor students in teacher education. Instructional preferences and…

  9. ML at ATLAS&CMS : setting the stage

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    In the early days of the LHC the canonical problems of classification and regression were mostly addressed using simple cut-based techniques. Today, ML techniques (some already pioneered in pre-LHC or non collider experiments) play a fundamental role in the toolbox of any experimentalist. The talk will introduce, through a representative collection of examples, the problems addressed with ML techniques at the LHC. The goal of the talk is to set the stage for a constructive discussion with non-HEP ML practitioners, focusing on the specificities of HEP applications.

  10. Self-Regulatory Behaviors and Approaches to Learning of Arts Students: A Comparison between Professional Training and English Learning

    Science.gov (United States)

    Tseng, Min-chen; Chen, Chia-cheng

    2017-01-01

    This study investigated the self-regulatory behaviors of arts students, namely memory strategy, goal-setting, self-evaluation, seeking assistance, environmental structuring, learning responsibility, and planning and organizing. We also explored approaches to learning, including deep approach (DA) and surface approach (SA), in a comparison between…

  11. A New Design Approach to Game-Based learning

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2012-01-01

    to ground the student’s reason to learn. This paper proposes a different approach: using visualisation in immersive 3D worlds as both documentation of learning progress and as a reward system which motivates further learning. The overall design idea is to build a game based learning system from three......This paper puts forward a new design perspective for gamebased learning. The general idea is to abandon the long sought-after dream of designing a closed learning system, where students in both primary and secondary school could learn – without the interference of teachers – whatever subject......-based learning system, but will also confront aspects of modern learning theory, especially the notion of reference between the content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way of tackling the common experience of the average...

  12. How to develop students’ approaches to learning: Experiences from a programme based on co-regulated learning

    Directory of Open Access Journals (Sweden)

    Stančić Milan

    2017-01-01

    Full Text Available Starting from the insight that during their education students do not manage to learn how to learn, we created the programme called Blooming with the intention of enabling the students to reconsider their own approaches to learning by developing collaborative activities and relations in the classroom. The programme was realised in a secondary school class, and research goals were to explore the contribution of the programme to the change in students’ approach to learning - regarding the learning motivation and strategies - and to obtain an insight into students’ perspective of the benefits of the programme. The changes in learning strategies and students’ motivation were investigated using the MSLQ before and after programme attendance. The data on the programme benefits were obtained via focus groups with students and analysed by the thematic content analysis. It has been established that the students achieved a significant improvement when it comes to the mastering of the learning strategies that refer to self-regulation, critical thinking, peer learning and help seeking. In addition, the students pointed out as benefits a different method of work and pleasant atmosphere, the feeling of autonomy in classes, as well as the development of a different understanding of the nature of knowledge, the learning process and instruction. The results indicate that the use of Bloom’s taxonomy as the tool for co-regulated learning and self-evaluation of students can contribute to the change in students’ learning approaches. This finding is relevant for further considering of the possibility for this method to grow from a special programme into everyday teaching practice.

  13. Machine learning and computer vision approaches for phenotypic profiling.

    Science.gov (United States)

    Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

    2017-01-02

    With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

  14. Multivariate Analysis and Machine Learning in Cerebral Palsy Research

    Directory of Open Access Journals (Sweden)

    Jing Zhang

    2017-12-01

    Full Text Available Cerebral palsy (CP, a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.

  15. Effects of the Digital Game-Development Approach on Elementary School Students' Learning Motivation, Problem Solving, and Learning Achievement

    Science.gov (United States)

    Chu, Hui-Chun; Hung, Chun-Ming

    2015-01-01

    In this study, the game-based development approach is proposed for improving the learning motivation, problem solving skills, and learning achievement of students. An experiment was conducted on a learning activity of an elementary school science course to evaluate the performance of the proposed approach. A total of 59 sixth graders from two…

  16. Superficial and deep learning approaches among medical students in an interdisciplinary integrated curriculum.

    Science.gov (United States)

    Mirghani, Hisham M; Ezimokhai, Mutairu; Shaban, Sami; van Berkel, Henk J M

    2014-01-01

    Students' learning approaches have a significant impact on the success of the educational experience, and a mismatch between instructional methods and the learning approach is very likely to create an obstacle to learning. Educational institutes' understanding of students' learning approaches allows those institutes to introduce changes in their curriculum content, instructional format, and assessment methods that will allow students to adopt deep learning techniques and critical thinking. The objective of this study was to determine and compare learning approaches among medical students following an interdisciplinary integrated curriculum. This was a cross-sectional study in which an electronic questionnaire using the Biggs two-factor Study Process Questionnaire (SPQ) with 20 questions was administered. Of a total of 402 students at the medical school, 214 (53.2%) completed the questionnaire. There was a significant difference in the mean score of superficial approach, motive and strategy between students in the six medical school years. However, no significant difference was observed in the mean score of deep approach, motive and strategy. The mean score for years 1 and 2 showed a significantly higher surface approach, surface motive and surface strategy when compared with students in years 4-6 in medical school. The superficial approach to learning was mostly preferred among first and second year medical students, and the least preferred among students in the final clinical years. These results may be useful in creating future teaching, learning and assessment strategies aiming to enhance a deep learning approach among medical students. Future studies are needed to investigate the reason for the preferred superficial approach among medical students in their early years of study.

  17. Learning approaches as predictors of academic performance in first year health and science students.

    Science.gov (United States)

    Salamonson, Yenna; Weaver, Roslyn; Chang, Sungwon; Koch, Jane; Bhathal, Ragbir; Khoo, Cheang; Wilson, Ian

    2013-07-01

    To compare health and science students' demographic characteristics and learning approaches across different disciplines, and to examine the relationship between learning approaches and academic performance. While there is increasing recognition of a need to foster learning approaches that improve the quality of student learning, little is known about students' learning approaches across different disciplines, and their relationships with academic performance. Prospective, correlational design. Using a survey design, a total of 919 first year health and science students studying in a university located in the western region of Sydney from the following disciplines were recruited to participate in the study - i) Nursing: n = 476, ii) Engineering: n = 75, iii) Medicine: n = 77, iv) Health Sciences: n = 204, and v) Medicinal Chemistry: n = 87. Although there was no statistically significant difference in the use of surface learning among the five discipline groups, there were wide variations in the use of deep learning approach. Furthermore, older students and those with English as an additional language were more likely to use deep learning approach. Controlling for hours spent in paid work during term-time and English language usage, both surface learning approach (β = -0.13, p = 0.001) and deep learning approach (β = 0.11, p = 0.009) emerged as independent and significant predictors of academic performance. Findings from this study provide further empirical evidence that underscore the importance for faculty to use teaching methods that foster deep instead of surface learning approaches, to improve the quality of student learning and academic performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Healthcare students' experiences when integrating e-learning and flipped classroom instructional approaches.

    Science.gov (United States)

    Telford, Mark; Senior, Emma

    2017-06-08

    This article describes the experiences of undergraduate healthcare students taking a module adopting a 'flipped classroom' approach. Evidence suggests that flipped classroom as a pedagogical tool has the potential to enhance student learning and to improve healthcare practice. This innovative approach was implemented within a healthcare curriculum and in a module looking at public health delivered at the beginning of year two of a 3-year programme. The focus of the evaluation study was on the e-learning resources used in the module and the student experiences of these; with a specific aim to evaluate this element of the flipped classroom approach. A mixed-methods approach was adopted and data collected using questionnaires, which were distributed across a whole cohort, and a focus group involving ten participants. Statistical analysis of the data showed the positive student experience of engaging with e-learning. The thematic analysis identified two key themes; factors influencing a positive learning experience and the challenges when developing e-learning within a flipped classroom approach. The study provides guidance for further developments and improvements when developing e-learning as part of the flipped classroom approach.

  19. Inclusive Approach to the Psycho-Pedagogical Assistance of Distance Learning

    Science.gov (United States)

    Akhmetova, Daniya Z.

    2014-01-01

    Author focuses on three groups of problems: quality of distance learning and e-learning; necessity to develop the facilitation skills for teachers who work using distance learning technologies; realization of inclusive approach for the organization of distance learning in inclusive groups where people with disabilities study with people without…

  20. Implementing Project Based Learning Approach to Graphic Design Course

    Science.gov (United States)

    Riyanti, Menul Teguh; Erwin, Tuti Nuriah; Suriani, S. H.

    2017-01-01

    The purpose of this study was to develop a learning model based Commercial Graphic Design Drafting project-based learning approach, was chosen as a strategy in the learning product development research. University students as the target audience of this model are the students of the fifth semester Visual Communications Design Studies Program…

  1. Teaching European Studies: A Blended Learning Approach

    Directory of Open Access Journals (Sweden)

    Alina Christova

    2011-12-01

    Full Text Available This paper will be looking into the teaching method developed by the Institute for European Studies in Brussels, combining an e-learning tool- the E-modules- with face-to-face training sessions and webinars. The main aim is to analyse the three different components of this “blended learning” pedagogical approach, as well as the way they complement each other and to address a few of the challenges that have emerged from the experience of working with them so far. The E-modules are an e-learning platform that has been designed with the purpose of offering a structured and interactive way of learning how the European Union functions. The face-to-face training component currently takes the form of three days in-house seminars, covering in an intensive manner the most important areas of the curriculum. The lectures are held by a mix of academics and practitioners, hereby ensuring a balanced approach, in which theory and practice come together to facilitate the learning experience. The third element of the “blended learning” method is placed in-between online and face-to-face learning: interactive seminars and debates are held online, giving the participants the chance to deepen their knowledge in certain fields of interest and to discuss the content of the course with specialists and among themselves. The mixture of delivery and interaction methods was chosen in order to accommodate a large variety of target groups, ranging from students to professionals working with EU-related issues, with different backgrounds and geographical origins. One of the main challenges is to use each medium for the functionalities it is best designed for and to ensure that the various pieces of the pedagogical puzzle fit together perfectly, while allowing the learners the flexibility that had initially directed them towards “blended learning” instead of a classical classroom approach.

  2. Integrating transformative learning and action learning approaches to enhance ethical leadership for supervisors in the hotel business

    Directory of Open Access Journals (Sweden)

    Boonyuen Saranya

    2016-01-01

    Full Text Available Ethical leadership is now increasingly focused in leadership development. The main purpose of this study is to explore two methods of adult learning, action learning and transformative learning, and to use the methods to enhance ethical leadership. Building ethical leadership requires an approach that focuses on personal values, beliefs, or frames of references, which is transformative learning. Transformative learning requires a series of meetings to conduct critical discourse and to follow up the learning of learners. By organizing such action learning, human resource developers can optimize their time and effort more effectively. The authors have created a comprehensive model to integrate the two learning approaches in a general way that focuses not only on ethical leadership, but also on all kinds of behavioral transformation in the workplace in the hotel business or even other types of business.

  3. Model-driven Service Engineering with SoaML

    Science.gov (United States)

    Elvesæter, Brian; Carrez, Cyril; Mohagheghi, Parastoo; Berre, Arne-Jørgen; Johnsen, Svein G.; Solberg, Arnor

    This chapter presents a model-driven service engineering (MDSE) methodology that uses OMG MDA specifications such as BMM, BPMN and SoaML to identify and specify services within a service-oriented architecture. The methodology takes advantage of business modelling practices and provides a guide to service modelling with SoaML. The presentation is case-driven and illuminated using the telecommunication example. The chapter focuses in particular on the use of the SoaML modelling language as a means for expressing service specifications that are aligned with business models and can be realized in different platform technologies.

  4. Organizational Approach to the Ergonomic Examination of E-Learning Modules

    Science.gov (United States)

    Lavrov, Evgeniy; Kupenko, Olena; Lavryk, Tetiana; Barchenko, Natalia

    2013-01-01

    With a significant increase in the number of e-learning resources the issue of quality is of current importance. An analysis of existing scientific and methodological literature shows the variety of approaches, methods and tools to evaluate e-learning materials. This paper proposes an approach based on the procedure for estimating parameters of…

  5. The FITS model: an improved Learning by Design approach

    OpenAIRE

    Michels, Koen; Vries, de, Marc; Breukelen, van, Dave; Schure, Frank

    2016-01-01

    Learning by Design (LBD) is a project-based inquiry approach for interdisciplinary teaching that uses design contexts to learn skills and conceptual knowledge. Research around the year 2000 showed that LBD students achieved high skill performances but disappointing conceptual learning gains. A series of exploratory studies, previous to the study in this paper, indicated how to enhance concept learning. Small-scale tested modifications, based on explicit teaching and scaffolding, were promisin...

  6. Meta-analysis of Jelajah Alam Sekitar (JAS Approach Implementation in Learning Procces

    Directory of Open Access Journals (Sweden)

    S. Ngabekti

    2017-04-01

    Full Text Available The results of tracer studies on the approach of Jelajah Alam Sekitar (JAS or environment exploring learning has been detected is used in eight provinces in Indonesia and studied in the learning begin primary school to college. Then, how the effectiveness of the implementation of the JAS approach in improving the learning process. This study uses meta-analysis-data in the form of descriptive exploratory qualitative. Data was taken from the various thesis, and research faculty in the last 10 years. Data analysis was performed by calculating the percentage of the same findings for similar problems. The results showed a wide range of studies using different methods and approach such as qualitative descriptive, quasi-experimental, PTK and R and D to produce evidence that the approach JAS effective when applied in teaching, especially teaching biology in a variety of teaching materials. Various studies have shown the approach JAS managed to increase learning outcomes, can differentiate learning outcomes between treatment and control groups in which the treatment group had a mean score higher. Models/strategies/methods centered learning students are very relevant to implementation approach JAS making it seem more real, like a model of cooperative learning, think pair share, strategy role-playing, the investigation group, learning cycle 5e, hands-on activity, and so on, making it possible to continuously assessed and developed in the paradigm of competency-based curriculum developed.

  7. Machine Learning of Musical Gestures

    OpenAIRE

    Caramiaux, Baptiste; Tanaka, Atau

    2013-01-01

    We present an overview of machine learning (ML) techniques and theirapplication in interactive music and new digital instruments design. We firstgive to the non-specialist reader an introduction to two ML tasks,classification and regression, that are particularly relevant for gesturalinteraction. We then present a review of the literature in current NIMEresearch that uses ML in musical gesture analysis and gestural sound control.We describe the ways in which machine learning is useful for cre...

  8. IMPROVING TRUST THROUGH ETHICAL LEADERSHIP: MOVING BEYOND THE SOCIAL LEARNING THEORY TO A HISTORICAL LEARNING APPROACH

    Directory of Open Access Journals (Sweden)

    Omoregie Charles Osifo

    2016-12-01

    Full Text Available The complex nature of trust and its evolving relative concepts require a more idealistic and simpler review. Ethical leadership is related to trust, honesty, transparency, compassion, empathy, results-orientedness, and many other behavioral attributes. Ethical leadership and good leadership are the same, because they represent practicing what one preaches or showing a way to the accomplishment of set goals. The outcomes and findings of many research papers on trust and ethical leadership report positive correlations between ethical leadership and trust. Improving trust from different rational standpoints requires moving and looking beyond the popular theoretical framework through which most results are derived in order to create a new thinking perspective. Social learning theory strongly emphasizes modelling while the new historical learning approach, proposed by the author, is defined as an approach that creates unique historical awareness among individuals, groups, institutions, societies, and nations to use previous experience(s or occurrence(s as a guide in developing positive opinion(s and framework(s in order to tackle the problems and issues of today and tomorrow. Social learning theory is seen as limited from the perspectives of balancing the equation between leadership and trust, the non-compatibility of the values of different generations at work, and other approaches and methods that support the historical approach. This paper is argumentative, adopts a writer´s perspective, and employs a logical analysis of the literature. The main contention is that a historical learning approach can inform an independent-learning to improve trust and its relatives (e.g. motivation and performance, because independent learning can positively shape the value of integrity, which is an integral part of ethical leadership. Historical learning can positively shape leadership in every perspective, because good leadership can develop based on history and

  9. E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education

    Science.gov (United States)

    Laksitowening, K. A.; Santoso, H. B.; Hasibuan, Z. A.

    2017-01-01

    E-Learning can be a tool in monitoring learning process and progress towards the targeted competency. Process and progress on every learner can be different one to another, since every learner may have different learning type. Learning type itself can be identified by taking into account learning style, motivation, and knowledge ability. This study explores personalization for learning type based on Triple-Factor Approach. Considering that factors in Triple-Factor Approach are dynamic, the personalization system needs to accommodate the changes that may occurs. Originated from the issue, this study proposed personalization that guides learner progression dynamically towards stages of their learning process. The personalization is implemented in the form of interventions that trigger learner to access learning contents and discussion forums more often as well as improve their level of knowledge ability based on their state of learning type.

  10. Undergraduate Students' Earth Science Learning: Relationships among Conceptions, Approaches, and Learning Self-Efficacy in Taiwan

    Science.gov (United States)

    Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen

    2016-01-01

    In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to…

  11. Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology.

    Science.gov (United States)

    Min, Hua; Mobahi, Hedyeh; Irvin, Katherine; Avramovic, Sanja; Wojtusiak, Janusz

    2017-09-16

    Bio-ontologies are becoming increasingly important in knowledge representation and in the machine learning (ML) fields. This paper presents a ML approach that incorporates bio-ontologies and its application to the SEER-MHOS dataset to discover patterns of patient characteristics that impact the ability to perform activities of daily living (ADLs). Bio-ontologies are used to provide computable knowledge for ML methods to "understand" biomedical data. This retrospective study included 723 cancer patients from the SEER-MHOS dataset. Two ML methods were applied to create predictive models for ADL disabilities for the first year after a patient's cancer diagnosis. The first method is a standard rule learning algorithm; the second is that same algorithm additionally equipped with methods for reasoning with ontologies. The models showed that a patient's race, ethnicity, smoking preference, treatment plan and tumor characteristics including histology, staging, cancer site, and morphology were predictors for ADL performance levels one year after cancer diagnosis. The ontology-guided ML method was more accurate at predicting ADL performance levels (P ontologies. This study demonstrated that bio-ontologies can be harnessed to provide medical knowledge for ML algorithms. The presented method demonstrates that encoding specific types of hierarchical relationships to guide rule learning is possible, and can be extended to other types of semantic relationships present in biomedical ontologies. The ontology-guided ML method achieved better performance than the method without ontologies. The presented method can also be used to promote the effectiveness and efficiency of ML in healthcare, in which use of background knowledge and consistency with existing clinical expertise is critical.

  12. Workplace-based assessment and students' approaches to learning: a qualitative inquiry.

    Science.gov (United States)

    Al-Kadri, Hanan M; Al-Kadi, Mohammed T; Van Der Vleuten, Cees P M

    2013-01-01

    We have performed this research to assess the effect of work-place based assessment (WBA) practice on medical students' learning approaches. The research was conducted at the King Saud bin Abdulaziz University for Health Sciences, College of Medicine from 1 March to 31 July 2012. We conducted a qualitative, phenomenological research utilizing semi-structured individual interviews with medical students exposed to WBA. The audio-taped interviews were transcribed verbatim, analyzed, and themes were identified. We preformed investigators' triangulation, member checking with clinical supervisors and we triangulated the data with a similar research performed prior to the implementation of WBA. WBA results in variable learning approaches. Based on several affecting factors; clinical supervisors, faculty-given feedback, and assessment function, students may swing between surface, deep and effort and achievement learning approaches. Students' and supervisors' orientations on the process of WBA, utilization of peer feedback and formative rather than summative assessment facilitate successful implementation of WBA and lead to students' deeper approaches to learning. Interestingly, students and their supervisors have contradicting perceptions to WBA. A change in culture to unify students' and supervisors' perceptions of WBA, more accommodation of formative assessment, and feedback may result in students' deeper approach to learning.

  13. Blending Online Learning with Traditional Approaches: Changing Practices

    Science.gov (United States)

    Condie, Rae; Livingston, Kay

    2007-01-01

    Considerable claims have been made for the development of e-learning, either as stand-alone programmes or alongside more traditional approaches to teaching and learning, for students across school and tertiary education. National initiatives have improved the position of schools in terms of access to hardware and electronic networking, software…

  14. Arts-Based Learning: A New Approach to Nursing Education Using Andragogy.

    Science.gov (United States)

    Nguyen, Megan; Miranda, Joyal; Lapum, Jennifer; Donald, Faith

    2016-07-01

    Learner-oriented strategies focusing on learning processes are needed to prepare nursing students for complex practice situations. An arts-based learning approach uses art to nurture cognitive and emotional learning. Knowles' theory of andragogy aims to develop the skill of learning and can inform the process of implementing arts-based learning. This article explores the use and evaluation of andragogy-informed arts-based learning for teaching nursing theory at the undergraduate level. Arts-based learning activities were implemented and then evaluated by students and instructors using anonymous questionnaires. Most students reported that the activities promoted learning. All instructors indicated an interest in integrating arts-based learning into the curricula. Facilitators and barriers to mainstreaming arts-based learning were highlighted. Findings stimulate implications for prospective research and education. Findings suggest that arts-based learning approaches enhance learning by supporting deep inquiry and different learning styles. Further exploration of andragogy-informed arts-based learning in nursing and other disciplines is warranted. [J Nurs Educ. 2016;55(7):407-410.]. Copyright 2016, SLACK Incorporated.

  15. Relationships between Learning Approach, Procrastination and Academic Achievement amongst First-Year University Students

    Science.gov (United States)

    Saele, Rannveig Grøm; Dahl, Tove Irene; Sørlie, Tore; Friborg, Oddgeir

    2017-01-01

    Individual differences in student learning influence academic performance, and two aspects influencing the learning process are the particular learning approach the students use and procrastination behaviour. We examined the relationships between learning approaches, procrastination and academic achievement (measured 1 year later as the grade…

  16. Students' Conception of Learning Environment and Their Approach to Learning and Its Implication on Quality Education

    Science.gov (United States)

    Belaineh, Matheas Shemelis

    2017-01-01

    Quality of education in higher institutions can be affected by different factors. It partly rests on the learning environment created by teachers and the learning approach students are employing during their learning. The main purpose of this study is to examine the learning environment at Mizan Tepi University from students' perspective and their…

  17. Game-Enhanced Simulation as an Approach to Experiential Learning in Business English

    Science.gov (United States)

    Punyalert, Sansanee

    2017-01-01

    This dissertation aims to integrate various learning approaches, i.e., multiple literacies, experiential learning, game-enhanced learning, and global simulation, into an extracurricular module, in which it remodels traditional ways of teaching input, specifically, the lexical- and grammatical-only approaches of business English at a private…

  18. Using Flipped Classroom Approach to Explore Deep Learning in Large Classrooms

    Directory of Open Access Journals (Sweden)

    Brenda Danker

    2015-01-01

    Full Text Available This project used two Flipped Classroom approaches to stimulate deep learning in large classrooms during the teaching of a film module as part of a Diploma in Performing Arts course at Sunway University, Malaysia. The flipped classes utilized either a blended learning approach where students first watched online lectures as homework, and then completed their assignments and practical work in class; or utilized a guided inquiry approach at the beginning of class using this same process. During the class the lecturers were present to help the students, and in addition, the students were advantaged by being able to help one another. The in-class learning activities also included inquiry-based learning, active learning, and peer-learning. This project used an action research approach to improve the in-class instructional design progressively to achieve its impact of deep learning among the students. The in-class learning activities that was included in the later flipped classes merged aspects of blended learning with an inquiry-based learning cycle which focused on the exploration of concepts. Data was gathered from questionnaires filled out by the students and from short interviews with the students, as well as from the teacher’s reflective journals. The findings verified that the flipped classrooms were able to remodel large lecture classes into active-learning classes. The results also support the possibility of individualised learning for the students as being high as a result of the teacher’s ability to provide one-on-one tutoring through technology-infused lessons. It is imperative that the in-class learning activities are purposefully designed as the inclusion of the exploratory learning through guided inquiry-based activities in the flipped classes was a successful way to engage students on a deeper level and increased the students’ curiosity and engaged them to develop higher-order thinking skills. This project also concluded that

  19. Students' Feedback of mDPBL Approach and the Learning Impact towards Computer Networks Teaching and Learning

    Science.gov (United States)

    Winarno, Sri; Muthu, Kalaiarasi Sonai; Ling, Lew Sook

    2018-01-01

    This study presents students' feedback and learning impact on design and development of a multimedia learning in Direct Problem-Based Learning approach (mDPBL) for Computer Networks in Dian Nuswantoro University, Indonesia. This study examined the usefulness, contents and navigation of the multimedia learning as well as learning impacts towards…

  20. E-learning on the job : training taking a more virtual approach

    Energy Technology Data Exchange (ETDEWEB)

    Macedo, R.

    2008-07-15

    A growing number of companies are using web-based e-learning systems to train employees. The activities of 3 E-learning companies were described in this article, notably dominKnow Learning Systems, NGRAIN Corporation and Blatant Media. One of the greatest challenges facing the oilsands industry is to build a skilled labour force to operate massive upgraders. The benefit of the e-learning approach is that consistent information can be delivered to learners, with no variation in information. The training takes on many forms, either through online simulations or simply placing a manual online. In addition to saving time, e-learning familiarizes workers with specific pieces of equipment that would be much too expensive to purchase. Three-dimensional equipment simulations are also made available for training purposes. This article presented an online e-learning approach that has been used effectively for safety training and corporate governance. E-learning simplified the process compared to actual classroom training. It allowed staff to combine training time with regular work schedules. The online e-learning approach was shown to save companies many of hours in training time. 2 figs.

  1. Translation in language learning: a ‘what for’ approach

    Directory of Open Access Journals (Sweden)

    Paolo E. Balboni

    2017-12-01

    Full Text Available Literature about translation in language learning and teaching shows the prominence of the ‘for and against’ approach, while a ‘what for’ approach would be more profitable. In order to prevent the latter approach from becoming a random list of the potential benefits of the use of translation in language teaching, this essay suggests the use of a formal model of communicative competence, to see which of its components can profit of translation activities. The result is a map of the effects of translation in the wide range of competences and abilities which constitute language learning.

  2. Learning Outcomes in Vocational Education: A Business Plan Development by Production-Based Learning Model Approach

    Science.gov (United States)

    Kusumaningrum, Indrati; Hidayat, Hendra; Ganefri; Anori, Sartika; Dewy, Mega Silfia

    2016-01-01

    This article describes the development of a business plan by using production-based learning approach. In addition, this development also aims to maximize learning outcomes in vocational education. Preliminary analysis of curriculum and learning and the needs of the market and society become the basic for business plan development. To produce a…

  3. Benefiting from Customer and Competitor Knowledge: A Market-Based Approach to Organizational Learning

    Science.gov (United States)

    Hoe, Siu Loon

    2008-01-01

    Purpose: The purpose of this paper is to review the organizational learning, market orientation and learning orientation concepts, highlight the importance of market knowledge to organizational learning and recommend ways in adopting a market-based approach to organizational learning. Design/methodology/approach: The extant organizational learning…

  4. A machine learning approach using EEG data to predict response to SSRI treatment for major depressive disorder.

    Science.gov (United States)

    Khodayari-Rostamabad, Ahmad; Reilly, James P; Hasey, Gary M; de Bruin, Hubert; Maccrimmon, Duncan J

    2013-10-01

    The problem of identifying, in advance, the most effective treatment agent for various psychiatric conditions remains an elusive goal. To address this challenge, we investigate the performance of the proposed machine learning (ML) methodology (based on the pre-treatment electroencephalogram (EEG)) for prediction of response to treatment with a selective serotonin reuptake inhibitor (SSRI) medication in subjects suffering from major depressive disorder (MDD). A relatively small number of most discriminating features are selected from a large group of candidate features extracted from the subject's pre-treatment EEG, using a machine learning procedure for feature selection. The selected features are fed into a classifier, which was realized as a mixture of factor analysis (MFA) model, whose output is the predicted response in the form of a likelihood value. This likelihood indicates the extent to which the subject belongs to the responder vs. non-responder classes. The overall method was evaluated using a "leave-n-out" randomized permutation cross-validation procedure. A list of discriminating EEG biomarkers (features) was found. The specificity of the proposed method is 80.9% while sensitivity is 94.9%, for an overall prediction accuracy of 87.9%. There is a 98.76% confidence that the estimated prediction rate is within the interval [75%, 100%]. These results indicate that the proposed ML method holds considerable promise in predicting the efficacy of SSRI antidepressant therapy for MDD, based on a simple and cost-effective pre-treatment EEG. The proposed approach offers the potential to improve the treatment of major depression and to reduce health care costs. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  5. Video Quality Assessment and Machine Learning: Performance and Interpretability

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Forchhammer, Søren; Korhonen, Jari

    2015-01-01

    In this work we compare a simple and a complex Machine Learning (ML) method used for the purpose of Video Quality Assessment (VQA). The simple ML method chosen is the Elastic Net (EN), which is a regularized linear regression model and easier to interpret. The more complex method chosen is Support...... Vector Regression (SVR), which has gained popularity in VQA research. Additionally, we present an ML-based feature selection method. Also, it is investigated how well the methods perform when tested on videos from other datasets. Our results show that content-independent cross-validation performance...... on a single dataset can be misleading and that in the case of very limited training and test data, especially in regards to different content as is the case for many video datasets, a simple ML approach is the better choice....

  6. Exploring students learning approaches in MOOCs

    OpenAIRE

    Faucon, Louis Pierre

    2017-01-01

    This study aims at understanding different students approaches for solving assignments in MOOCs. It makes use of a large dataset of logs from students interaction with the MOOC platform Coursera on a course about functional programming with Scala. In total more than 10.000 students participated in the assignments. Learning approaches are divided in two categories: starting with video lectures (V) and start- ing with the assignment (A); and students are divided in three groups: those applying ...

  7. Assessing reflective thinking and approaches to learning.

    Science.gov (United States)

    Dunn, Louise; Musolino, Gina M

    2011-01-01

    Facilitation of reflective practice is critical for the ongoing demands of health care practitioners. Reflective thinking concepts, grounded in the work of Dewey and Schön, emphasize critical reflection to promote transformation in beliefs and learning necessary for reflective practice. The Reflective Thinking Questionnaire (QRT) and Revised Study Process Questionnaire (RSPQ-2F) assess skill aspects of professional reasoning, with promise for measuring changes over time. The purpose of this study was to examine the reliability and responsiveness and the model validity of reflective thinking and approaches to learning measures for U.S. health professions students enrolled in entry-level occupational (MOT) and physical therapy (DPT) programs. This measurement study addressed reliability and responsiveness of two measures, the QRT and RSPQ-2F, for graduate health professionals. A convenience sample of 125 MOT and DPT students participated in the two-measure, test-retest investigation, with electronic data collection. Outcomes support the stability of the four-scale QRT (ICC 0.63 to 0.82) and the two-scale RSPQ-2F (ICC 0.91 and 0.87). Descriptive data supporting responsiveness are presented. With noted limitations, the results support the use of the QRT and RSPQ-2F measures to assess changes in reflective thinking and approaches to learning. Measurement of these learning outcomes furthers our understanding and knowledge about instructional strategies, development of professional reasoning, and fostering of self-directed learning within MOT and DPT programs.

  8. Effects of a blended learning approach on student outcomes in a graduate-level public health course.

    Science.gov (United States)

    Kiviniemi, Marc T

    2014-03-11

    Blended learning approaches, in which in-person and online course components are combined in a single course, are rapidly increasing in health sciences education. Evidence for the relative effectiveness of blended learning versus more traditional course approaches is mixed. The impact of a blended learning approach on student learning in a graduate-level public health course was examined using a quasi-experimental, non-equivalent control group design. Exam scores and course point total data from a baseline, "traditional" approach semester (n = 28) was compared to that from a semester utilizing a blended learning approach (n = 38). In addition, student evaluations of the blended learning approach were evaluated. There was a statistically significant increase in student performance under the blended learning approach (final course point total d = 0.57; a medium effect size), even after accounting for previous academic performance. Moreover, student evaluations of the blended approach were very positive and the majority of students (83%) preferred the blended learning approach. Blended learning approaches may be an effective means of optimizing student learning and improving student performance in health sciences courses.

  9. Improving Problem Solving Skill and Self Regulated Learning of Senior High School Students through Scientific Approach using Quantum Learning strategy

    Directory of Open Access Journals (Sweden)

    M Sudirman

    2017-12-01

    Full Text Available This research is quasi experiment with control group pretest-postest design. The sampel in this research using the techique of purposive sampling so the samples used were two classes of the 11th grade students of SMAN 14 Bandung in the academic year 2017/2018. The experiment group uses saintific approach using Quantum Learning strategy and control group uses saintific approach. In collecting the data the researcher will use the test of problem solving ability and self regulated learning as the instrument. The aims of this research are to:1find out the improvement of students mathematical problem solving through scientific approach using Quantum Learning study, 2 find out students self regulated learning through scientific approach using Quantum Learning.

  10. Missing links between lean startup, design thinking, and experiential learning approaches in entrepreneurship education

    DEFF Research Database (Denmark)

    Ramsgaard, Michael Breum; Christensen, Marie Ernst

    2016-01-01

    Questions we care about • How do different pedagogical teaching approaches in entrepreneurship education construct learning outcome when comparing the underlying pedagogical models? • Where can unidentified fields and correlations of pedagogical insights between the approaches of lean startup......, design thinking, and experiential learning be identified? • How can new concepts of learning models, taking lean startup, design thinking and experiential learning approaches into account, be developed in entrepreneurship education? Approach This 3e conference paper begins as a conceptual paper...... highlighting the theories and underlying learning models behind three pedagogical approaches within entrepreneurship education, namely lean startup, design thinking and experiential learning. The paper builds this knowledge framework in order to set the design for an empirical investigation of the proposed...

  11. TIME-ON-TASK IN PRIMARY CLASSROOMS, DURING DIFFERENT TEACHING-LEARNING APPROACHES

    OpenAIRE

    Sachin Mohite; Meenal Dashputre

    2017-01-01

    The entire education system is moving from the teacher-centered teaching-learning approaches towards student-centered teaching-learning approaches, with anticipation that it would increase the learning outcomes. This empirical study was carried out to compare the traditional and non-traditional classrooms. It also tried to understand the effectiveness of the Alternate Instructions in the Mathematics and Primary Language (Marathi) classrooms. This study collected about 8000 snapshots from the ...

  12. Learning Assessment in physical education: the relationship between assessment practices of teachers and learning approaches

    Directory of Open Access Journals (Sweden)

    Marco Vinicio Gutiérrez

    2015-02-01

    Full Text Available This article shows the result of an investigation that studied teachers’ assessment practices in Physical Education in public schools from Suba in Bogota and the relationship between these practices with both superfluous and superficial learning approaches. It is organized into two sections; the first presents a classification of the evaluation practices, and the second establishes the relationship between these practices with the superficial and profound learning approaches. This article nourishes itself from a mixed-method research approach wherein the sample consisted of 68 teachers from whom data was collected using a survey. This data was then analyzed using the statistical software R. The results show the object, the purpose, procedures and ways in which teachers develop their assessment practice in physical education, and as well show a trend towards promoting meaningful and profound learning.

  13. AN ANALYSIS ON THE ADVANTAGES OF COOPERATIVE LEARNING APPROACH IN TEACHING WRITING

    Directory of Open Access Journals (Sweden)

    Chamisah Chamisah

    2013-11-01

    Full Text Available This article aims to explain an analysis of cooperative learning approach advantages in teaching writing. Accordingly, learning writing by using cooperative learning makes the students easier in developing the ideas to write. This approach is more than just putting students into groups, but the students can work together, share information, and they are responsible for completion of the tasks in group as well. Besides, in this approach, the students can transfer their information and knowledge to the others and help each other in getting the ideas to develop in written communication during teaching-learning process.

  14. Classroom quality and academic skills: Approaches to learning as a moderator.

    Science.gov (United States)

    Meng, Christine

    2015-12-01

    The purpose of this study was to examine whether approaches to learning moderated the association between child care classroom environment and Head Start children's academic skills. The data came from the Head Start Family and Child Experiences Survey (FACES-2003 Cohort). The dataset is a nationally representative longitudinal study of Head Start children. The sample was selected using the stratified 4-stage sampling procedure. Data was collected in fall 2003, spring 2004, spring 2005, and spring 2006 in the first year of kindergarten. Participants included 3- and 4-year-old Head Start children (n = 786; 387 boys, 399 girls; 119 Hispanic children, 280 African American children, 312 Caucasian children). Head Start children's academic skills in letter-word identification, dictation/spelling, and mathematics at the 4 time points were measured by the Woodcock-Johnson Achievement Battery tests. Approaches to learning in fall 2003 was measured by the teacher report of the Preschool Learning Behaviors Scale. Child care classroom quality in fall 2003 was measured by the revised Early Childhood Environment Rating Scale. Results of the linear mixed effects models demonstrated that approaches to learning significantly moderated the effect of child care classroom quality on Head Start children's writing and spelling. Specifically, positive approaches to learning mitigated the negative effect of lower levels of classroom quality on dictation/spelling. Results underscore the important role of approaches to learning as a protective factor. Implications for early childhood educators with an emphasis on learning goals for disengaged children are discussed. (c) 2015 APA, all rights reserved).

  15. A New Approach to Programming Language Education for Beginners with Top-Down Learning

    Directory of Open Access Journals (Sweden)

    Daisuke Saito

    2013-12-01

    Full Text Available There are two basic approaches in learning new programming language: a bottom-up approach and a top-down approach. It has been said that if a learner has already acquired one language, the top-down approach is more efficient to learn another while, for a person who has absolutely no knowledge of any programming languages; the bottom-up approach is preferable. The major problem of the bottom-up approach is that it requires longer period to acquire the language. For quicker learning, this paper applies a top-down approach for a beginners who has not yet acquired any programming languages.

  16. Episodic reinforcement learning control approach for biped walking

    Directory of Open Access Journals (Sweden)

    Katić Duško

    2012-01-01

    Full Text Available This paper presents a hybrid dynamic control approach to the realization of humanoid biped robotic walk, focusing on the policy gradient episodic reinforcement learning with fuzzy evaluative feedback. The proposed structure of controller involves two feedback loops: a conventional computed torque controller and an episodic reinforcement learning controller. The reinforcement learning part includes fuzzy information about Zero-Moment- Point errors. Simulation tests using a medium-size 36-DOF humanoid robot MEXONE were performed to demonstrate the effectiveness of our method.

  17. Deep and shallow approaches to learning mathematics are not mutually exclusive.

    OpenAIRE

    Mathias, J.; Newton, D.P.

    2016-01-01

    From time to time, students are characterised as having a deep or shallow approach to learning. A deep approach to learning tends to attract more approval than a shallow approach, at least in the West. Students on a university-based Foundation course to prepare them for undergraduate studies were divided into those likely to have a deep approach (26) and those likely to have a shallow approach (18). Their performance in a test of problem solving in an aspect of applied mathematics was compare...

  18. Supporting teachers integrating web 2.0 in a Problem Based Learning approach

    DEFF Research Database (Denmark)

    Buus, Lillian

    2010-01-01

    Based on theoretical and methodological considerations within problem-based learning (PBL), web 2.0 technologies and learning designs, the article try to illustrate a design model for supporting teachers in their learning design trying to integrate web 2.0 technologies into their PBL approach...... that a transition from curriculum-based teaching to PBL entails a movement from a teacher-centered approach to a learner-centered approach [4],[5]. This move can in many ways be compared to the conceptual move from web 1.0 to web 2.0 that by some is seen as a transition from ‘users/learners as consumers’ towards...... ‘users/learners as producers’ [6]. Consequently, it makes good sense to connect Web 2.0 with a problem-based approach to learning. Therefore it’s interesting to look upon a learning design model supporting teachers at AAU in their pedagogical design combining these two. The Collaborative E...

  19. MLitB: machine learning in the browser

    Directory of Open Access Journals (Sweden)

    Edward Meeds

    2015-07-01

    Full Text Available With few exceptions, the field of Machine Learning (ML research has largely ignored the browser as a computational engine. Beyond an educational resource for ML, the browser has vast potential to not only improve the state-of-the-art in ML research, but also, inexpensively and on a massive scale, to bring sophisticated ML learning and prediction to the public at large. This paper introduces MLitB, a prototype ML framework written entirely in Javascript, capable of performing large-scale distributed computing with heterogeneous classes of devices. The development of MLitB has been driven by several underlying objectives whose aim is to make ML learning and usage ubiquitous (by using ubiquitous compute devices, cheap and effortlessly distributed, and collaborative. This is achieved by allowing every internet capable device to run training algorithms and predictive models with no software installation and by saving models in universally readable formats. Our prototype library is capable of training deep neural networks with synchronized, distributed stochastic gradient descent. MLitB offers several important opportunities for novel ML research, including: development of distributed learning algorithms, advancement of web GPU algorithms, novel field and mobile applications, privacy preserving computing, and green grid-computing. MLitB is available as open source software.

  20. 1st International Conference on Machine Learning for Cyber Physical Systems and Industry 4.0

    CERN Document Server

    Beyerer, Jürgen

    2016-01-01

    The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Lemgo, October 1-2, 2015. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.

  1. Effects of a blended learning approach on student outcomes in a graduate-level public health course

    Science.gov (United States)

    2014-01-01

    Background Blended learning approaches, in which in-person and online course components are combined in a single course, are rapidly increasing in health sciences education. Evidence for the relative effectiveness of blended learning versus more traditional course approaches is mixed. Method The impact of a blended learning approach on student learning in a graduate-level public health course was examined using a quasi-experimental, non-equivalent control group design. Exam scores and course point total data from a baseline, “traditional” approach semester (n = 28) was compared to that from a semester utilizing a blended learning approach (n = 38). In addition, student evaluations of the blended learning approach were evaluated. Results There was a statistically significant increase in student performance under the blended learning approach (final course point total d = 0.57; a medium effect size), even after accounting for previous academic performance. Moreover, student evaluations of the blended approach were very positive and the majority of students (83%) preferred the blended learning approach. Conclusions Blended learning approaches may be an effective means of optimizing student learning and improving student performance in health sciences courses. PMID:24612923

  2. Quantum Machine Learning

    OpenAIRE

    Romero García, Cristian

    2017-01-01

    [EN] In a world in which accessible information grows exponentially, the selection of the appropriate information turns out to be an extremely relevant problem. In this context, the idea of Machine Learning (ML), a subfield of Artificial Intelligence, emerged to face problems in data mining, pattern recognition, automatic prediction, among others. Quantum Machine Learning is an interdisciplinary research area combining quantum mechanics with methods of ML, in which quantum properties allow fo...

  3. jmzIdentML API: A Java interface to the mzIdentML standard for peptide and protein identification data.

    Science.gov (United States)

    Reisinger, Florian; Krishna, Ritesh; Ghali, Fawaz; Ríos, Daniel; Hermjakob, Henning; Vizcaíno, Juan Antonio; Jones, Andrew R

    2012-03-01

    We present a Java application programming interface (API), jmzIdentML, for the Human Proteome Organisation (HUPO) Proteomics Standards Initiative (PSI) mzIdentML standard for peptide and protein identification data. The API combines the power of Java Architecture of XML Binding (JAXB) and an XPath-based random-access indexer to allow a fast and efficient mapping of extensible markup language (XML) elements to Java objects. The internal references in the mzIdentML files are resolved in an on-demand manner, where the whole file is accessed as a random-access swap file, and only the relevant piece of XMLis selected for mapping to its corresponding Java object. The APIis highly efficient in its memory usage and can handle files of arbitrary sizes. The APIfollows the official release of the mzIdentML (version 1.1) specifications and is available in the public domain under a permissive licence at http://www.code.google.com/p/jmzidentml/. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. Meta-Analysis of Jelajah Alam Sekitar (JAS) Approach Implementation in Learning Process

    Science.gov (United States)

    Ngabekti, S.; Ridlo, S.; Peniati, E.; Martanto, R.

    2017-01-01

    The results of tracer studies on the approach of Jelajah Alam Sekitar (JAS) or environment exploring learning has been detected is used in eight provinces in Indonesia and studied in the learning begin primary school to college. Then, how the effectiveness of the implementation of the JAS approach in improving the learning process. This study uses…

  5. Adult Learning in Health and Safety: Some Issues and Approaches.

    Science.gov (United States)

    O Fathaigh, Mairtin

    This document, which was developed for presentation at a seminar on adult learning and safety, examines approaches to occupational safety and health (OSH) learning/training in the workplace. Section 1 examines selected factors affecting adults' learning in workplace OSH programs. The principal dimensions along which individual adult learners will…

  6. Holistic Approach to Learning and Teaching Introductory Object-Oriented Programming

    Science.gov (United States)

    Thota, Neena; Whitfield, Richard

    2010-01-01

    This article describes a holistic approach to designing an introductory, object-oriented programming course. The design is grounded in constructivism and pedagogy of phenomenography. We use constructive alignment as the framework to align assessments, learning, and teaching with planned learning outcomes. We plan learning and teaching activities,…

  7. High school students educational usage of Internet and their learning approaches

    Directory of Open Access Journals (Sweden)

    M. Betül Yılmaz, Feza Orhan

    2010-08-01

    Full Text Available This study examines the Internet usage of high school students for educational needs in respect to their learning approaches. The “learning approach” categorizes individuals as ‘surface learners’ and ‘deep learners’. Surface learners mainly choose to rehearse and memorize the course material they work on and they acquire the information they need to learn in a disconnected way, by memorization. On the other hand, deep learners want to grasp the meaning of the course material. In the study, adapted Turkish version of Learning Process Questionnaire (LPQ was used to determine high school students’ learning approaches. 921 secondary school students were subjected and the Cronbach alpha values were 0.73 for a deep approach and 0.66 for a surface approach. According to the data obtained, surface learners use the Internet more when compared to deep learners, though they use it for non-instructional purposes. The ratios of the Internet use of deep learners for educational needs are higher when compared to those of surface learners. Ratios of the Internet use for educational needs by the students who are given assignments requiring the use of the Internet are higher.

  8. Learning Matlab a problem solving approach

    CERN Document Server

    Gander, Walter

    2015-01-01

    This comprehensive and stimulating introduction to Matlab, a computer language now widely used for technical computing, is based on an introductory course held at Qian Weichang College, Shanghai University, in the fall of 2014.  Teaching and learning a substantial programming language aren’t always straightforward tasks. Accordingly, this textbook is not meant to cover the whole range of this high-performance technical programming environment, but to motivate first- and second-year undergraduate students in mathematics and computer science to learn Matlab by studying representative problems, developing algorithms and programming them in Matlab. While several topics are taken from the field of scientific computing, the main emphasis is on programming. A wealth of examples are completely discussed and solved, allowing students to learn Matlab by doing: by solving problems, comparing approaches and assessing the proposed solutions.

  9. A work-based learning approach for clinical support workers on mental health inpatient wards.

    Science.gov (United States)

    Kemp, Philip; Gilding, Moorene; Seewooruttun, Khooseal; Walsh, Hannah

    2016-09-14

    Background With a rise in the number of unqualified staff providing health and social care, and reports raising concerns about the quality of care provided, there is a need to address the learning needs of clinical support workers. This article describes a qualitative evaluation of a service improvement project that involved a work-based learning approach for clinical support workers on mental health inpatient wards. Aim To investigate and identify insights in relation to the content and process of learning using a work-based learning approach for clinical support workers. Method This was a qualitative evaluation of a service improvement project involving 25 clinical support workers at the seven mental health inpatient units in South London and Maudsley NHS Foundation Trust. Three clinical skills tutors were appointed to develop, implement and evaluate the work-based learning approach. Four sources of data were used to evaluate this approach, including reflective journals, qualitative responses to questionnaires, three focus groups involving the clinical support workers and a group interview involving the clinical skills tutors. Data were analysed using thematic analysis. Findings The work-based learning approach was highly valued by the clinical support workers and enhanced learning in practice. Face-to-face learning in practice helped the clinical support workers to develop practice skills and reflective learning skills. Insights relating to the role of clinical support workers were also identified, including the benefits of face-to-face supervision in practice, particularly in relation to the interpersonal aspects of care. Conclusion A work-based learning approach has the potential to enhance care delivery by meeting the learning needs of clinical support workers and enabling them to apply learning to practice. Care providers should consider how the work-based learning approach can be used on a systematic, organisation-wide basis in the context of budgetary

  10. A study of active learning methods for named entity recognition in clinical text.

    Science.gov (United States)

    Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua

    2015-12-01

    Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random

  11. Adductor Canal Block With 10 mL Versus 30 mL Local Anesthetics and Quadriceps Strength

    DEFF Research Database (Denmark)

    Jæger, Pia; Koscielniak-Nielsen, Zbigniew J; Hilsted, Karen Lisa

    2015-01-01

    weakness. METHODS: We performed a paired, blinded, randomized trial including healthy men. All subjects received bilateral ACBs with ropivacaine 0.1%; 10 mL in 1 leg and 30 mL in the other leg. The primary outcome was the difference in number of subjects with quadriceps strength reduced by more than 25...... of the predefined time points or in sensory block. The only statistically significant difference between volumes was found in the 30-Second Chair Stand Test at 2 hours (P = 0.02), but this difference had disappeared at 4 hours (P = 0.06). CONCLUSIONS: Varying the volume of ropivacaine 0.1% used for ACB between 10...

  12. Contract Learning as an Approach to Individualizing EFL Education in the Context of Assessment for Learning

    Science.gov (United States)

    Zandi, Hamed; Kaivanpanah, Shiva; Alavi, Sayyed Mohammad

    2015-01-01

    Contract learning as an approach to individualizing education in the context of assessment for learning is relatively underexplored in English as a Foreign Language instruction. The present study used a mixed-methods design to investigate its efficacy to provide feedback to students and improve self-directed learning. Furthermore, it studied…

  13. PepArML: A Meta-Search Peptide Identification Platform for Tandem Mass Spectra.

    Science.gov (United States)

    Edwards, Nathan J

    2013-12-01

    The PepArML meta-search peptide identification platform for tandem mass spectra provides a unified search interface to seven search engines; a robust cluster, grid, and cloud computing scheduler for large-scale searches; and an unsupervised, model-free, machine-learning-based result combiner, which selects the best peptide identification for each spectrum, estimates false-discovery rates, and outputs pepXML format identifications. The meta-search platform supports Mascot; Tandem with native, k-score and s-score scoring; OMSSA; MyriMatch; and InsPecT with MS-GF spectral probability scores—reformatting spectral data and constructing search configurations for each search engine on the fly. The combiner selects the best peptide identification for each spectrum based on search engine results and features that model enzymatic digestion, retention time, precursor isotope clusters, mass accuracy, and proteotypic peptide properties, requiring no prior knowledge of feature utility or weighting. The PepArML meta-search peptide identification platform often identifies two to three times more spectra than individual search engines at 10% FDR.

  14. EnzML: multi-label prediction of enzyme classes using InterPro signatures

    Directory of Open Access Journals (Sweden)

    De Ferrari Luna

    2012-04-01

    Full Text Available Abstract Background Manual annotation of enzymatic functions cannot keep up with automatic genome sequencing. In this work we explore the capacity of InterPro sequence signatures to automatically predict enzymatic function. Results We present EnzML, a multi-label classification method that can efficiently account also for proteins with multiple enzymatic functions: 50,000 in UniProt. EnzML was evaluated using a standard set of 300,747 proteins for which the manually curated Swiss-Prot and KEGG databases have agreeing Enzyme Commission (EC annotations. EnzML achieved more than 98% subset accuracy (exact match of all correct Enzyme Commission classes of a protein for the entire dataset and between 87 and 97% subset accuracy in reannotating eight entire proteomes: human, mouse, rat, mouse-ear cress, fruit fly, the S. pombe yeast, the E. coli bacterium and the M. jannaschii archaebacterium. To understand the role played by the dataset size, we compared the cross-evaluation results of smaller datasets, either constructed at random or from specific taxonomic domains such as archaea, bacteria, fungi, invertebrates, plants and vertebrates. The results were confirmed even when the redundancy in the dataset was reduced using UniRef100, UniRef90 or UniRef50 clusters. Conclusions InterPro signatures are a compact and powerful attribute space for the prediction of enzymatic function. This representation makes multi-label machine learning feasible in reasonable time (30 minutes to train on 300,747 instances with 10,852 attributes and 2,201 class values using the Mulan Binary Relevance Nearest Neighbours algorithm implementation (BR-kNN.

  15. AllerML: markup language for allergens.

    Science.gov (United States)

    Ivanciuc, Ovidiu; Gendel, Steven M; Power, Trevor D; Schein, Catherine H; Braun, Werner

    2011-06-01

    Many concerns have been raised about the potential allergenicity of novel, recombinant proteins into food crops. Guidelines, proposed by WHO/FAO and EFSA, include the use of bioinformatics screening to assess the risk of potential allergenicity or cross-reactivities of all proteins introduced, for example, to improve nutritional value or promote crop resistance. However, there are no universally accepted standards that can be used to encode data on the biology of allergens to facilitate using data from multiple databases in this screening. Therefore, we developed AllerML a markup language for allergens to assist in the automated exchange of information between databases and in the integration of the bioinformatics tools that are used to investigate allergenicity and cross-reactivity. As proof of concept, AllerML was implemented using the Structural Database of Allergenic Proteins (SDAP; http://fermi.utmb.edu/SDAP/) database. General implementation of AllerML will promote automatic flow of validated data that will aid in allergy research and regulatory analysis. Copyright © 2011 Elsevier Inc. All rights reserved.

  16. A Bayesian concept learning approach to crowdsourcing

    DEFF Research Database (Denmark)

    Viappiani, P.; Zilles, S.; Hamilton, H.J.

    2011-01-01

    techniques, inference methods, and query selection strategies to assist a user charged with choosing a configuration that satisfies some (partially known) concept. Our model is able to simultaneously learn the concept definition and the types of the experts. We evaluate our model with simulations, showing......We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated according to (noisy) observations from experts, whose behaviors are modeled using discrete types. We propose recommendation...

  17. systemic approach to teaching and learning chemistry

    African Journals Online (AJOL)

    unesco

    2National Core Group in Chemistry, H.E.J Research Institute of Chemistry,. University of ... innovative way of teaching and learning through systemic approach (SATL) has been .... available to do useful work in a thermodynamic process.

  18. The flipped learning approach in teaching degrees: students’ perceptions

    Directory of Open Access Journals (Sweden)

    Déborah Martín R.

    2017-05-01

    Full Text Available In this paper, we analyze the students' perception of a university teaching-learning strategy, with a flipped learning approach, in the development of the subject Orientación educativa y plan de acción tutorial del Grado de Educación Primaria. The 21st century skills proposed by Fullan (2013 and known as the six Cs (Character, Communication, Collaboration, Citizenship, Critical Thinking and Creativity are used as a frame of reference. An experimental design of two groups, with a non-equivalent control group, has been used to analyze the students' perceptions of their learning in a conventional teaching environment and under a flipped environment based on m-learning. The differences found were statistically significant in all the analyzed dimensions, with favorable increases in the experimental methodology in all cases. The differences in Citizenship, Character, and Communication are of particular relevance. The analysis of the items reveals some difficulties in the functional literacy of students in the use of digital technology to improve their learning. Likewise, it is evident that the active methodologies improve, according to the perception of the students, the skills development, and learning. It is confirmed the hypothesis proposed in this study that the use of m-learning with a pedagogical approach centered on learning, with active methodologies, is a support that improves the development of the competences of the 21st century and, specifically, those described as the 6C's.

  19. A Blended Learning Approach to Teach Fluid Mechanics in Engineering

    Science.gov (United States)

    Rahman, Ataur

    2017-01-01

    This paper presents a case study on the teaching and learning of fluid mechanics at the University of Western Sydney (UWS), Australia, by applying a blended learning approach (BLA). In the adopted BLA, various flexible learning materials have been made available to the students such as online recorded lectures, online recorded tutorials, hand…

  20. Exploring a Problem-Based Learning Approach in Pharmaceutics

    Directory of Open Access Journals (Sweden)

    Barbara McKenzie

    2017-09-01

    Full Text Available Objective. The basis of this study was to explore the impact of the initiation of a Problem-Base Learning (PBL approach within a second-year pharmaceutics degree on a Master of Pharmacy programme, introduced as a way of improving deep learning and to foster independent learning. Design. A semi-structured interview was used to seek feedback from the students, and feedback from staff was secured though a focus group. A thematic approach was used for the analysis, once data saturation had been reached. Exam pass-rate statistics were also analysed. Assessment. Five parent themes were identified from the student interviews: Module structure, Promoting lifelong learning, Integration and future practice, Outcomes and Student experience. The third year exam pass rate improved by 12% in the year following the introduction of PBL in second year. Conclusions. Various recommendations were proposed to further improve the module, based on the findings of this study. These include improving feedback and support through tutorials, reducing the volume of directed study, as well as highlighting the relevance of pharmaceutics to the pharmacy degree. A long-term review would be needed to assess the full implications of PBL teaching within this course.

  1. Towards a Semantic E-Learning Theory by Using a Modelling Approach

    Science.gov (United States)

    Yli-Luoma, Pertti V. J.; Naeve, Ambjorn

    2006-01-01

    In the present study, a semantic perspective on e-learning theory is advanced and a modelling approach is used. This modelling approach towards the new learning theory is based on the four SECI phases of knowledge conversion: Socialisation, Externalisation, Combination and Internalisation, introduced by Nonaka in 1994, and involving two levels of…

  2. Using Flipped Classroom Approach to Explore Deep Learning in Large Classrooms

    Science.gov (United States)

    Danker, Brenda

    2015-01-01

    This project used two Flipped Classroom approaches to stimulate deep learning in large classrooms during the teaching of a film module as part of a Diploma in Performing Arts course at Sunway University, Malaysia. The flipped classes utilized either a blended learning approach where students first watched online lectures as homework, and then…

  3. Comparing deep neural network and other machine learning algorithms for stroke prediction in a large-scale population-based electronic medical claims database.

    Science.gov (United States)

    Chen-Ying Hung; Wei-Chen Chen; Po-Tsun Lai; Ching-Heng Lin; Chi-Chun Lee

    2017-07-01

    Electronic medical claims (EMCs) can be used to accurately predict the occurrence of a variety of diseases, which can contribute to precise medical interventions. While there is a growing interest in the application of machine learning (ML) techniques to address clinical problems, the use of deep-learning in healthcare have just gained attention recently. Deep learning, such as deep neural network (DNN), has achieved impressive results in the areas of speech recognition, computer vision, and natural language processing in recent years. However, deep learning is often difficult to comprehend due to the complexities in its framework. Furthermore, this method has not yet been demonstrated to achieve a better performance comparing to other conventional ML algorithms in disease prediction tasks using EMCs. In this study, we utilize a large population-based EMC database of around 800,000 patients to compare DNN with three other ML approaches for predicting 5-year stroke occurrence. The result shows that DNN and gradient boosting decision tree (GBDT) can result in similarly high prediction accuracies that are better compared to logistic regression (LR) and support vector machine (SVM) approaches. Meanwhile, DNN achieves optimal results by using lesser amounts of patient data when comparing to GBDT method.

  4. The Development of Blended-Learning Teaching Portfolio Course Using TBL Approach

    Science.gov (United States)

    Pardamean, Bens; Prabowo, Harjanto; Muljo, Hery Harjono; Suparyanto, Teddy; Masli, Eryadi K.; Donovan, Jerome

    2017-01-01

    This article was written to develop a teaching portfolio that helps lecturers maximize the benefits of blended learning, a combination of in-person and online learning, through the use of Team-Based Learning (TBL) teaching and learning approach. Studies show that TBL can provide opportunities in developing teamwork capabilities and enhancing…

  5. The Trialogical Learning Approach to innovate teaching

    Directory of Open Access Journals (Sweden)

    Nadia Sansone

    2016-11-01

    Full Text Available This article focuses on a case of implementing the Trialogical Learning Approach (TLA in two classes in the first year of a university school for future osteopaths (N = 36. The approach involves the creation of useful and tangible objects through alternation between individual and group activities, supported by digital technologies. The aim of the study is to observe the impact of TLA on the quality of learning products made by students and on teaching style, as well as to collect students’ views on activities. The collected data (individual and group products, notes inserted online, audio recordings of lessons, final questionnaires have been analyzed using a mixed qualitative and quantitative approach. The results show: a positive evolution in the quality of individual and group products; b progression from a transmissive teaching style towards one more oriented to collaboration and knowledge building; c general appreciation of the innovative method and its potential for fostering social skills useful for future employment.

  6. QuakeML: Recent Development and First Applications of the Community-Created Seismological Data Exchange Standard

    Science.gov (United States)

    Euchner, F.; Schorlemmer, D.; Kästli, P.; Quakeml Group, T

    2008-12-01

    QuakeML is an XML-based exchange format for seismological data which is being developed using a community-driven approach. It covers basic event description, including picks, arrivals, amplitudes, magnitudes, origins, focal mechanisms, and moment tensors. Contributions have been made from ETH, GFZ, USC, SCEC, USGS, IRIS DMC, EMSC, ORFEUS, GNS, ZAMG, BRGM, and ISTI. The current release (Version 1.1, Proposed Recommendation) reflects the results of a public Request for Comments process which has been documented online at http://quakeml.org/RFC_BED_1.0. QuakeML has recently been adopted as a distribution format for earthquake catalogs by GNS Science, New Zealand, and the European-Mediterranean Seismological Centre (EMSC). These institutions provide prototype QuakeML web services. Furthermore, integration of the QuakeML data model in the CSEP (Collaboratory for the Study of Earthquake Predictability, http://www.cseptesting.org) testing center software developed by SCEC is under way. QuakePy is a Python- based seismicity analysis toolkit which is based on the QuakeML data model. Recently, QuakePy has been used to implement the PMC method for calculating network recording completeness (Schorlemmer and Woessner 2008, in press). Completeness results for seismic networks in Southern California and Japan can be retrieved through the CompletenessWeb (http://completenessweb.org). Future QuakeML development will include an extension for macroseismic information. Furthermore, development on seismic inventory information, resource identifiers, and resource metadata is under way. Online resources: http://www.quakeml.org, http://www.quakepy.org

  7. Epistemological Belief and Learning Approaches of Students in Higher Institutions of Learning in Malaysia

    Science.gov (United States)

    Ismail, Habsah; Hassan, Aminuddin; Muhamad, Mohd. Mokhtar; Ali, Wan Zah Wan; Konting, Mohd. Majid

    2013-01-01

    This is an investigation of the students' beliefs about the nature of knowledge or epistemological beliefs, and the relation of these beliefs on their learning approaches. Students chosen as samples of the study were from both public and private higher institutions of learning in Malaysia. The instrument used in the study consists of 49 items…

  8. E-learning paradigms and applications agent-based approach

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    Teaching and learning paradigms have attracted increased attention especially in the last decade. Immense developments of different ICT technologies and services have paved the way for alternative but effective approaches in educational processes. Many concepts of the agent technology, such as intelligence, autonomy, and cooperation, have had a direct positive impact on many of the requests imposed on modern e-learning systems and educational processes. This book presents the state-of-the-art of e-learning and tutoring systems, and discusses their capabilities and benefits that stem from integrating software agents. We hope that the presented work will be of a great use to our colleagues and researchers interested in the e-learning and agent technology.    

  9. Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

    Science.gov (United States)

    Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin

    2017-08-10

    Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.

  10. Multimodal approaches to use mobile, digital devices in learning practies

    DEFF Research Database (Denmark)

    Buhl, Mie

    , anthropology, psychology and sociology) and outlines the prospect of a trans-disciplinary learning mode. The learning mode reflects the current society where knowledge production is social collaborative process and is produced in formal as well as informal and non-formal contexts. My discussion’s theoretical......In this paper, I discuss the potential of multimodal approaches to enhance learning processes. I draw on a case based on Danish Master Courses in ICT and didactic designs where multimodal approaches are in the center of students’ practical design experience as well as in generation of theoretical...... knowledge. The design of the master courses takes its starting point in the assumption that theoretical knowledge generates from practical experiences. Thus, the organization of the students’ learning processes revolves around practical multimodal experiences followed by iterative reflexive sessions...

  11. Cultivating collaborative improvement: an action learning approach

    NARCIS (Netherlands)

    Middel, H.G.A.; McNichols, Timothy

    2006-01-01

    The process of implementing collaborative initiatives across disparate members of supply networks is fraught with difficulties. One approach designed to tackle the difficulties of organisational change and interorganisational improvement in practice is 'action learning'. This paper examines the

  12. An Interactive Approach to Learning and Teaching in Visual Arts Education

    Science.gov (United States)

    Tomljenovic, Zlata

    2015-01-01

    The present research focuses on modernising the approach to learning and teaching the visual arts in teaching practice, as well as examining the performance of an interactive approach to learning and teaching in visual arts classes with the use of a combination of general and specific (visual arts) teaching methods. The study uses quantitative…

  13. Influence of the Constructivist Learning Approach on Students' Levels of Learning Trigonometry and on Their Attitudes towards Mathematics

    OpenAIRE

    İNAN, CEMİL

    2014-01-01

    In this experimental study, the influence of the constructivist learning approach on students’ levels of learning trigonometry and on their attitudes towards mathematics was examined in comparison with the traditional methods of instruction. The constructivist learning approach was the independent variable, while mathematics achievement, the lessons of trigonometry and the attitudes towards mathematics constituted the dependent variables. The study was designed as the pretest-posttest control...

  14. Integrating transformative learning and action learning approaches to enhance ethical leadership for supervisors in the hotel business

    OpenAIRE

    Boonyuen Saranya; Charungkaittikul Suwithida; Ratana-ubol Archanya

    2016-01-01

    Ethical leadership is now increasingly focused in leadership development. The main purpose of this study is to explore two methods of adult learning, action learning and transformative learning, and to use the methods to enhance ethical leadership. Building ethical leadership requires an approach that focuses on personal values, beliefs, or frames of references, which is transformative learning. Transformative learning requires a series of meetings to conduct critical discourse and to follow ...

  15. The Semiotic Approach and Language Teaching and Learning

    Directory of Open Access Journals (Sweden)

    Müfit Şenel

    2007-04-01

    Full Text Available This study investigates the relation of the Foreign Language Teaching with the SemioticApproach that gains more importance recently and tries to explain how this concept has beenused as Semiotic Approach in Foreign Language Teaching and Learning and teacher-learnerroles, strong-weak sides, types of activities, etc. have been handled.

  16. Digging deeper on "deep" learning: A computational ecology approach.

    Science.gov (United States)

    Buscema, Massimo; Sacco, Pier Luigi

    2017-01-01

    We propose an alternative approach to "deep" learning that is based on computational ecologies of structurally diverse artificial neural networks, and on dynamic associative memory responses to stimuli. Rather than focusing on massive computation of many different examples of a single situation, we opt for model-based learning and adaptive flexibility. Cross-fertilization of learning processes across multiple domains is the fundamental feature of human intelligence that must inform "new" artificial intelligence.

  17. Rainfall Prediction of Indian Peninsula: Comparison of Time Series Based Approach and Predictor Based Approach using Machine Learning Techniques

    Science.gov (United States)

    Dash, Y.; Mishra, S. K.; Panigrahi, B. K.

    2017-12-01

    Prediction of northeast/post monsoon rainfall which occur during October, November and December (OND) over Indian peninsula is a challenging task due to the dynamic nature of uncertain chaotic climate. It is imperative to elucidate this issue by examining performance of different machine leaning (ML) approaches. The prime objective of this research is to compare between a) statistical prediction using historical rainfall observations and global atmosphere-ocean predictors like Sea Surface Temperature (SST) and Sea Level Pressure (SLP) and b) empirical prediction based on a time series analysis of past rainfall data without using any other predictors. Initially, ML techniques have been applied on SST and SLP data (1948-2014) obtained from NCEP/NCAR reanalysis monthly mean provided by the NOAA ESRL PSD. Later, this study investigated the applicability of ML methods using OND rainfall time series for 1948-2014 and forecasted up to 2018. The predicted values of aforementioned methods were verified using observed time series data collected from Indian Institute of Tropical Meteorology and the result revealed good performance of ML algorithms with minimal error scores. Thus, it is found that both statistical and empirical methods are useful for long range climatic projections.

  18. Is a volume of 3.6 mL better than 1.8 mL for inferior alveolar nerve blocks in patients with symptomatic irreversible pulpitis?

    Science.gov (United States)

    Fowler, Sara; Reader, Al

    2013-08-01

    The purpose of this retrospective study was to determine the success of the inferior alveolar nerve (IAN) block using either 3.6 mL or 1.8 mL 2% lidocaine with 1:100,000 epinephrine in patients presenting with symptomatic irreversible pulpitis. As part of 7 previously published studies, 319 emergency patients presenting with symptomatic irreversible pulpitis received either a 1.8-mL volume or 3.6-mL volume of 2% lidocaine with 1:100,000 epinephrine in an IAN block. One hundred ninety patients received a 1.8-mL volume, and 129 received a 3.6-mL volume. Endodontic emergency treatment was completed on each subject. Success was defined as the ability to access and instrument the tooth without pain (visual analog scale score of 0) or mild pain (VAS rating ≤54 mm). Success of the 1.8-mL volume was 28%, and for the 3.6-mL volume it was 39%. There was no statistically significant difference between the 2 volumes. In conclusion, for patients presenting with irreversible pulpitis, success was not significantly different between a 3.6-mL volume and a 1.8-mL volume of 2% lidocaine with 1:100,000 epinephrine. The success rates (28%-39%) with either volume were not high enough to ensure complete pulpal anesthesia. Copyright © 2013 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

  19. ML-MG: Multi-label Learning with Missing Labels Using a Mixed Graph

    KAUST Repository

    Wu, Baoyuan; Lyu, Siwei; Ghanem, Bernard

    2015-01-01

    This work focuses on the problem of multi-label learning with missing labels (MLML), which aims to label each test instance with multiple class labels given training instances that have an incomplete/partial set of these labels (i.e. some

  20. Study Circles in Online Learning Environment in the Spirit of Learning-Centered Approach

    Directory of Open Access Journals (Sweden)

    Simándi Szilvia

    2017-08-01

    Full Text Available Introduction: In the era of information society and knowledge economy, learning in non-formal environments gets a highlighted role: it can supplement, replace or raise the knowledge and skills gained in the school system to a higher level (Forray & Juhász, 2008, as the so-called “valid” knowledge significantly changes due to the acceleration of development. With the appearance of information technology means and their booming development, the possibilities of gaining information have widened and, according to the forecasts, the role of learning communities will grow. Purpose: Our starting point is that today, with the involvement of community sites (e.g. Google+, Facebook etc. there is a new possibility for inspiring learning communities: by utilizing the power of community and the possibilities of network-based learning (Ollé & Lévai, 2013. Methods: We intend to make a synthesis based on former research and literature focusing on the learning-centered approach, online learning environment, learning communities and study circles (Noesgaard & Ørngreen, 2015; Biggs & Tang, 2007; Kindström, 2010 Conclusions: The online learning environment can be well utilized for community learning. In the online learning environment, the process of learning is built on activity-oriented work for which active participation, and an intensive, initiative communication are necessary and cooperative and collaborative learning get an important role.

  1. Affective Underpinnings of Surface Approaches to Learning and Their Relationship with Sensation Seeking

    Science.gov (United States)

    Robinson, Peter M.

    2018-01-01

    Surface approaches to learning materials and tasks are a commonplace challenge to teachers, and they prove difficult to shift, even among students who are otherwise talented or motivated to learn. The present study investigates a theory that surface approaches are triggered by a suboptimal, aversive response to learning stimuli, which overrides…

  2. Developing a Competency-Based Assessment Approach for Student Learning

    Science.gov (United States)

    Dunning, Pamela T.

    2014-01-01

    Higher education accrediting bodies are increasing the emphasis on assessing student learning outcomes as opposed to teaching methodology. The purpose of this article is to describe the process used by Troy University's Master of Public Administration program to change their assessment approach from a course learning objective perspective to a…

  3. ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings

    NARCIS (Netherlands)

    Drachsler, Hendrik; Pecceu, Dries; Arts, Tanja; Hutten, Edwin; Rutledge, Lloyd; Van Rosmalen, Peter; Hummel, Hans; Koper, Rob

    2009-01-01

    Drachsler, H., Peccau, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (2009). ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings. Presentation at the 2nd Workshop Mash-Up Personal Learning

  4. ONLINE EDUCATION, ACTIVE LEARNING, AND ANDRAGOGY: An approach for Student Engagement

    OpenAIRE

    CARUTH, Gail D.

    2015-01-01

    Online learning opportunities have become essential for today’s colleges and universities. Online technology can support active learning approaches to learning. The purpose of the paper was to investigate why active learning in online classes has a positive effect on student engagement. A review of the literature revealed that research studies have been conducted to investigate the benefits of active learning. There exists extensive evidence to support the notion that active learning enhances...

  5. Machine Learning of Fault Friction

    Science.gov (United States)

    Johnson, P. A.; Rouet-Leduc, B.; Hulbert, C.; Marone, C.; Guyer, R. A.

    2017-12-01

    We are applying machine learning (ML) techniques to continuous acoustic emission (AE) data from laboratory earthquake experiments. Our goal is to apply explicit ML methods to this acoustic datathe AE in order to infer frictional properties of a laboratory fault. The experiment is a double direct shear apparatus comprised of fault blocks surrounding fault gouge comprised of glass beads or quartz powder. Fault characteristics are recorded, including shear stress, applied load (bulk friction = shear stress/normal load) and shear velocity. The raw acoustic signal is continuously recorded. We rely on explicit decision tree approaches (Random Forest and Gradient Boosted Trees) that allow us to identify important features linked to the fault friction. A training procedure that employs both the AE and the recorded shear stress from the experiment is first conducted. Then, testing takes place on data the algorithm has never seen before, using only the continuous AE signal. We find that these methods provide rich information regarding frictional processes during slip (Rouet-Leduc et al., 2017a; Hulbert et al., 2017). In addition, similar machine learning approaches predict failure times, as well as slip magnitudes in some cases. We find that these methods work for both stick slip and slow slip experiments, for periodic slip and for aperiodic slip. We also derive a fundamental relationship between the AE and the friction describing the frictional behavior of any earthquake slip cycle in a given experiment (Rouet-Leduc et al., 2017b). Our goal is to ultimately scale these approaches to Earth geophysical data to probe fault friction. References Rouet-Leduc, B., C. Hulbert, N. Lubbers, K. Barros, C. Humphreys and P. A. Johnson, Machine learning predicts laboratory earthquakes, in review (2017). https://arxiv.org/abs/1702.05774Rouet-LeDuc, B. et al., Friction Laws Derived From the Acoustic Emissions of a Laboratory Fault by Machine Learning (2017), AGU Fall Meeting Session S025

  6. Multi-modal Social Networks: A MRF Learning Approach

    Science.gov (United States)

    2016-06-20

    Network forensics: random infection vs spreading epidemic , Proceedings of ACM Sigmetrics. 11-JUN-12, London, UK. : , TOTAL: 4 06/09/2016 Received Paper...Multi-modal Social Networks A MRF Learning Approach The work primarily focused on two lines of research. 1. We propose new greedy algorithms...Box 12211 Research Triangle Park, NC 27709-2211 social networks , learning and inference REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT

  7. Learning from project experiences using a legacy-based approach

    Science.gov (United States)

    Cooper, Lynne P.; Majchrzak, Ann; Faraj, Samer

    2005-01-01

    As project teams become used more widely, the question of how to capitalize on the knowledge learned in project teams remains an open issue. Using previous research on shared cognition in groups, an approach to promoting post-project learning was developed. This Legacy Review concept was tested on four in tact project teams. The results from those test sessions were used to develop a model of team learning via group cognitive processes. The model and supporting propositions are presented.

  8. A Challenge-Feedback Learning Approach to Teaching International Business

    Science.gov (United States)

    Sternad, Dietmar

    2015-01-01

    This article introduces a challenge-feedback learning (CFL) approach based on the goal-setting theory of human motivation, the deliberate practice theory of expert performance, and findings from the research on active and collaborative learning. The core of the teaching concept is the CFL cycle in which students repeatedly progress through four…

  9. Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

    Science.gov (United States)

    Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

    2017-11-01

    This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.

  10. Stacking machine learning classifiers to identify Higgs bosons at the LHC

    International Nuclear Information System (INIS)

    Alves, A.

    2017-01-01

    Machine learning (ML) algorithms have been employed in the problem of classifying signal and background events with high accuracy in particle physics. In this paper, we compare the performance of a widespread ML technique, namely, stacked generalization , against the results of two state-of-art algorithms: (1) a deep neural network (DNN) in the task of discovering a new neutral Higgs boson and (2) a scalable machine learning system for tree boosting, in the Standard Model Higgs to tau leptons channel, both at the 8 TeV LHC. In a cut-and-count analysis, stacking three algorithms performed around 16% worse than DNN but demanding far less computation efforts, however, the same stacking outperforms boosted decision trees. Using the stacked classifiers in a multivariate statistical analysis (MVA), on the other hand, significantly enhances the statistical significance compared to cut-and-count in both Higgs processes, suggesting that combining an ensemble of simpler and faster ML algorithms with MVA tools is a better approach than building a complex state-of-art algorithm for cut-and-count.

  11. Malignant lymphomas (ML and HIV infection in Tanzania

    Directory of Open Access Journals (Sweden)

    Mwakigonja Amos R

    2008-06-01

    Full Text Available Abstract Background HIV infection is reported to be associated with some malignant lymphomas (ML so called AIDS-related lymphomas (ARL, with an aggressive behavior and poor prognosis. The ML frequency, pathogenicity, clinical patterns and possible association with AIDS in Tanzania, are not well documented impeding the development of preventive and therapeutic strategies. Methods Sections of 176 archival formalin-fixed paraffin-embedded biopsies of ML patients at Muhimbili National Hospital (MNH/Muhimbili University of Health and Allied Sciences (MUHAS, Tanzania from 1996–2001 were stained for hematoxylin and eosin and selected (70 cases for expression of pan-leucocytic (CD45, B-cell (CD20, T-cell (CD3, Hodgkin/RS cell (CD30, histiocyte (CD68 and proliferation (Ki-67 antigen markers. Corresponding clinical records were also evaluated. Available sera from 38 ML patients were screened (ELISA for HIV antibodies. Results The proportion of ML out of all diagnosed tumors at MNH during the 6 year period was 4.2% (176/4200 comprising 77.84% non-Hodgkin (NHL including 19.32% Burkitt's (BL and 22.16% Hodgkin's disease (HD. The ML tumors frequency increased from 0.42% (1997 to 0.70% (2001 and 23.7% of tested sera from these patients were HIV positive. The mean age for all ML was 30, age-range 3–91 and peak age was 1–20 years. The male:female ratio was 1.8:1. Supra-diaphragmatic presentation was commonest and histological sub-types were mostly aggressive B-cell lymphomas however, no clear cases of primary effusion lymphoma (PEL and primary central nervous system lymphoma (PCNSL were diagnosed. Conclusion Malignant lymphomas apparently, increased significantly among diagnosed tumors at MNH between 1996 and 2001, predominantly among the young, HIV infected and AIDS patients. The frequent aggressive clinical and histological presentation as well as the dominant B-immunophenotype and the HIV serology indicate a pathogenic association with AIDS. Therefore

  12. Malignant lymphomas (ML) and HIV infection in Tanzania.

    Science.gov (United States)

    Mwakigonja, Amos R; Kaaya, Ephata E; Mgaya, Edward M

    2008-06-10

    HIV infection is reported to be associated with some malignant lymphomas (ML) so called AIDS-related lymphomas (ARL), with an aggressive behavior and poor prognosis. The ML frequency, pathogenicity, clinical patterns and possible association with AIDS in Tanzania, are not well documented impeding the development of preventive and therapeutic strategies. Sections of 176 archival formalin-fixed paraffin-embedded biopsies of ML patients at Muhimbili National Hospital (MNH)/Muhimbili University of Health and Allied Sciences (MUHAS), Tanzania from 1996-2001 were stained for hematoxylin and eosin and selected (70) cases for expression of pan-leucocytic (CD45), B-cell (CD20), T-cell (CD3), Hodgkin/RS cell (CD30), histiocyte (CD68) and proliferation (Ki-67) antigen markers. Corresponding clinical records were also evaluated. Available sera from 38 ML patients were screened (ELISA) for HIV antibodies. The proportion of ML out of all diagnosed tumors at MNH during the 6 year period was 4.2% (176/4200) comprising 77.84% non-Hodgkin (NHL) including 19.32% Burkitt's (BL) and 22.16% Hodgkin's disease (HD). The ML tumors frequency increased from 0.42% (1997) to 0.70% (2001) and 23.7% of tested sera from these patients were HIV positive. The mean age for all ML was 30, age-range 3-91 and peak age was 1-20 years. The male:female ratio was 1.8:1. Supra-diaphragmatic presentation was commonest and histological sub-types were mostly aggressive B-cell lymphomas however, no clear cases of primary effusion lymphoma (PEL) and primary central nervous system lymphoma (PCNSL) were diagnosed. Malignant lymphomas apparently, increased significantly among diagnosed tumors at MNH between 1996 and 2001, predominantly among the young, HIV infected and AIDS patients. The frequent aggressive clinical and histological presentation as well as the dominant B-immunophenotype and the HIV serology indicate a pathogenic association with AIDS. Therefore, routine HIV screening of all malignant lymphoma

  13. Focusing on first year assessment: Surface or deep approaches to learning?

    Directory of Open Access Journals (Sweden)

    Sharn Donnison

    2012-08-01

    Full Text Available This paper investigates the assessment and learning approaches that some first year students employ to assist them in their transition into their first year of study and extends our previous work on first year student engagement and timely academic support (Penn-Edwards & Donnison, 2011. It is situated within the First Year transition and student engagement literature and specifically speaks to concepts of learning within that body of literature. In this paper we argue that while students are in the transitional period of their studies, the use of assessment as a motivator for learning (surface approach is valid first year pedagogy and forms an initial learning stage in the student’s progress towards being lifelong learners. 

  14. Performance Analysis of Machine-Learning Approaches for Modeling the Charging/Discharging Profiles of Stationary Battery Systems with Non-Uniform Cell Aging

    Directory of Open Access Journals (Sweden)

    Nandha Kumar Kandasamy

    2017-06-01

    Full Text Available The number of Stationary Battery Systems (SBS connected to various power distribution networks across the world has increased drastically. The increase in the integration of renewable energy sources is one of the major contributors to the increase in the number of SBS. SBS are also used in other applications such as peak load management, load-shifting, voltage regulation and power quality improvement. Accurately modeling the charging/discharging characteristics of such SBS at various instances (charging/discharging profile is vital for many applications. Capacity loss due to the aging of the batteries is an important factor to be considered for estimating the charging/discharging profile of SBS more accurately. Empirical modeling is a common approach used in the literature for estimating capacity loss, which is further used for estimating the charging/discharging profiles of SBS. However, in the case of SBS used for renewable integration and other grid related applications, machine-learning (ML based models provide extreme flexibility and require minimal resources for implementation. The models can even leverage existing smart meter data to estimate the charging/discharging profile of SBS. In this paper, an analysis on the performance of different ML approaches that can be applied for lithium iron phosphate battery systems and vanadium redox flow battery systems used as SBS is presented for the scenarios where the aging of individual cells is non-uniform.

  15. A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing

    Science.gov (United States)

    Shao, Si-Yu; Sun, Wen-Jun; Yan, Ru-Qiang; Wang, Peng; Gao, Robert X.

    2017-11-01

    Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need expert knowledge and human intervention. In this paper, a deep learning approach based on deep belief networks (DBN) is developed to learn features from frequency distribution of vibration signals with the purpose of characterizing working status of induction motors. It combines feature extraction procedure with classification task together to achieve automated and intelligent fault diagnosis. The DBN model is built by stacking multiple-units of restricted Boltzmann machine (RBM), and is trained using layer-by-layer pre-training algorithm. Compared with traditional diagnostic approaches where feature extraction is needed, the presented approach has the ability of learning hierarchical representations, which are suitable for fault classification, directly from frequency distribution of the measurement data. The structure of the DBN model is investigated as the scale and depth of the DBN architecture directly affect its classification performance. Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors. This research proposes an intelligent diagnosis method for induction motor which utilizes deep learning model to automatically learn features from sensor data and realize working status recognition.

  16. Dyslexia, authorial identity, and approaches to learning and writing: a mixed methods study.

    Science.gov (United States)

    Kinder, Julianne; Elander, James

    2012-06-01

    Dyslexia may lead to difficulties with academic writing as well as reading. The authorial identity approach aims to help students improve their academic writing and avoid unintentional plagiarism, and could help to understand dyslexic students' approaches to writing. (1) To compare dyslexic and non-dyslexic students' authorial identity and approaches to learning and writing; (2) to compare correlations between approaches to writing and approaches to learning among dyslexic and non-dyslexic students; (3) to explore dyslexic students' understandings of authorship and beliefs about dyslexia, writing and plagiarism. Dyslexic (n= 31) and non-dyslexic (n= 31) university students. Questionnaire measures of self-rated confidence in writing, understanding of authorship, knowledge to avoid plagiarism, and top-down, bottom-up and pragmatic approaches to writing (Student Authorship Questionnaire; SAQ), and deep, surface and strategic approaches to learning (Approaches and Study Skills Inventory for Students; ASSIST), plus qualitative interviews with dyslexic students with high and low SAQ scores. Dyslexic students scored lower for confidence in writing, understanding authorship, and strategic approaches to learning, and higher for surface approaches to learning. Correlations among SAQ and ASSIST scores were larger and more frequently significant among non-dyslexic students. Self-rated knowledge to avoid plagiarism was associated with a top-down approach to writing among dyslexic students and with a bottom-up approach to writing among non-dyslexic students. All the dyslexic students interviewed described how dyslexia made writing more difficult and reduced their confidence in academic writing, but they had varying views about whether dyslexia increased the risk of plagiarism. Dyslexic students have less strong authorial identities, and less congruent approaches to learning and writing. Knowledge to avoid plagiarism may be more salient for dyslexic students, who may benefit from

  17. Post treatment PSA nadirs support continuing dose escalation study in patients with pretreatment PSA levels >10 ng/ml, but not in those with PSA <10 NG/ML

    International Nuclear Information System (INIS)

    Herold, D.H.; Hanlon, A.L.; Movsas, B.; Hanks, G.E.

    1996-01-01

    Purpose: We have recently shown that ICRU reporting point radiation doses above 71 Gy are not associated with improved bNED survival in prostate cancer patients with pretreatment PSA level 20 ng/ml we found a strong correlation between dose and nadir values < 1.0 ng/ml (p=.003) as well as for nadir's < 0.5 ng/ml (p=.04). This dose/nadir effect held at several dose levels, but 74 Gy for nadir values < 1.0 ng/ml and 72 Gy for nadir's < 0.5 ng/ml remained the most significant. 32% of these patients achieved a nadir < 1.0ng/ml and 15% < 0.5ng/ml. Conclusions: This analysis provides strong additional support that patients with pretreatment PSA values of < 10 ng/ml do not benefit from dose escalation beyond an ICRU reporting point dose of 71 Gy. For patients with pretreatment PSA's of 10-19.9 ng/ml there is no dose/nadir response evaluated at a nadir of 1.0 ng/ml; however, there is a borderline effect observed at a nadir of 0.5 ng/ml. Patients with pretreatment PSA's of 20 ng/ml or greater clearly benefit from higher doses as evaluated by PSA nadirs of 1.0 ng/ml, and 0.5 ng/ml. These studies support the continued investigation of dose escalation in treating patients with PSA levels over 10 ng/ml, they do not support continued investigation of dose escalation beyond 71 Gy in patients with pretreatment PSA levels < 10 ng/ml. The failure to demonstrate any dose response for the low PSA group and the finding of only a borderline effect for the intermediate PSA group may be influenced by the relatively small number of patients in our series treated to doses < 70 Gy and the fact that none of our patients were treated to doses below 65.98 Gy. The lower limit of acceptible dose has yet to be defined

  18. Factors Contributing to Changes in a Deep Approach to Learning in Different Learning Environments

    Science.gov (United States)

    Postareff, Liisa; Parpala, Anna; Lindblom-Ylänne, Sari

    2015-01-01

    The study explored factors explaining changes in a deep approach to learning. The data consisted of interviews with 12 students from four Bachelor-level courses representing different disciplines. We analysed and compared descriptions of students whose deep approach either increased, decreased or remained relatively unchanged during their courses.…

  19. Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

    Science.gov (United States)

    Howard, Rebecca; Rattray, Magnus; Prosperi, Mattia; Custovic, Adnan

    2015-07-01

    Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as 'asthma endotypes'. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies.

  20. Modeling the Relations among Students' Epistemological Beliefs, Motivation, Learning Approach, and Achievement

    Science.gov (United States)

    Kizilgunes, Berna; Tekkaya, Ceren; Sungur, Semra

    2009-01-01

    The authors proposed a model to explain how epistemological beliefs, achievement motivation, and learning approach related to achievement. The authors assumed that epistemological beliefs influence achievement indirectly through their effect on achievement motivation and learning approach. Participants were 1,041 6th-grade students. Results of the…

  1. Regulating approaches to learning: Testing learning strategy convergences across a year at university.

    Science.gov (United States)

    Fryer, Luke K; Vermunt, Jan D

    2018-03-01

    Contemporary models of student learning within higher education are often inclusive of processing and regulation strategies. Considerable research has examined their use over time and their (person-centred) convergence. The longitudinal stability/variability of learning strategy use, however, is poorly understood, but essential to supporting student learning across university experiences. Develop and test a person-centred longitudinal model of learning strategies across the first-year university experience. Japanese university students (n = 933) completed surveys (deep and surface approaches to learning; self, external, and lack of regulation) at the beginning and end of their first year. Following invariance and cross-sectional tests, latent profile transition analysis (LPTA) was undertaken. Initial difference testing supported small but significant differences for self-/external regulation. Fit indices supported a four-group model, consistent across both measurement points. These subgroups were labelled Low Quality (low deep approaches and self-regulation), Low Quantity (low strategy use generally), Average (moderate strategy use), and High Quantity (intense use of all strategies) strategies. The stability of these groups ranged from stable to variable: Average (93% stayers), Low Quality (90% stayers), High Quantity (72% stayers), and Low Quantity (40% stayers). The three largest transitions presented joint shifts in processing/regulation strategy preference across the year, from adaptive to maladaptive and vice versa. Person-centred longitudinal findings presented patterns of learning transitions that different students experience during their first year at university. Stability/variability of students' strategy use was linked to the nature of initial subgroup membership. Findings also indicated strong connections between processing and regulation strategy changes across first-year university experiences. Implications for theory and practice are discussed.

  2. Organizational Learning Supported by Machine Learning Models Coupled with General Explanation Methods: A Case of B2B Sales Forecasting

    Directory of Open Access Journals (Sweden)

    Bohanec Marko

    2017-08-01

    Full Text Available Background and Purpose: The process of business to business (B2B sales forecasting is a complex decision-making process. There are many approaches to support this process, but mainly it is still based on the subjective judgment of a decision-maker. The problem of B2B sales forecasting can be modeled as a classification problem. However, top performing machine learning (ML models are black boxes and do not support transparent reasoning. The purpose of this research is to develop an organizational model using ML model coupled with general explanation methods. The goal is to support the decision-maker in the process of B2B sales forecasting.

  3. Effect of Work-Based Learning Approach Genius Scientific Judging of the Physics Learning Achievement of Knowledge Early SMPN 13 Balikpapan in 2012

    Directory of Open Access Journals (Sweden)

    Suliyono Suliyono

    2014-06-01

    Full Text Available Pengaruh Pendekatan Genius Learning Berbasis Kerja Ilmiah terhadap Prestasi Belajar Fisika Ditinjau dari  Pengetahuan Awal Siswa SMPN 13 Balikpapan Tahun 2012 Abstract: student mastery of the concepts of physics would be better if teachers implement instructional strategies that can make students more active and motivated, but still maintain a constructivist. Work-Based Learning Approach Scientific Genius (GLBKI is believed to be able to answer the demands of the development of education and facilitate students in learning physics concepts. The purpose of this study was to examine student achievement studying the Work-Based Learning Approach Genius Scientific and conventional learning. GLBKI approach to the treatment of experimental classes randomly selected and control classes conducted conventional learning. Learning achievement data collected by physics learning achievement tests. Results of the study are:  (1 there is a significant difference between student achievement through conventional learning and work-based learning approach scientific genius, (2 students who studied with GLBKI approach has physics learning achievement higher than the students who studied with conventional learning, ( 3 learning by using the Work-Based Learning Approach Scientific Genius can deliver improved student achievement is higher than the students who studied with conventional learning. Key words: work-based learning strategies genius of scientific, academic achievement, prior knowledge Abstrak: Penguasaan siswa terhadap konsep-konsep fisika akan lebih baik apabila pendidik menerap-kan strategi pembelajaran yang dapat membuat siswa lebih aktif dan termotivasi, namun tetap memper-tahankan konstruktivis. Pendekatan Genius Learning Berbasis Kerja Ilmiah (GLBKI diyakini mampu menjawab tuntutan perkembangan pendidikan dan mempermudah siswa dalam mempelajari konsep-konsep fisika. Tujuan penelitian ini adalah untuk menguji  prestasi belajar siswa yang belajar

  4. A SysML-based Integration Framework for the Engineering of Mechatronic Systems

    OpenAIRE

    Chami, Muhammad; Seemüller, Holger; Voos, Holger

    2010-01-01

    The engineering discipline mechatronics is one of the main innovation leader in industry nowadays. With the need for an optimal synergetic integration of the involved disciplines, the engineering process of mechatronic systems is faced with an increasing complexity and the interdisciplinary nature of these systems. New methods and techniques have to be developed to deal with these challenges. This document presents an approach of a SysML-based integration framework that s...

  5. Facilitating long-term changes in student approaches to learning science.

    Science.gov (United States)

    Buchwitz, Brian J; Beyer, Catharine H; Peterson, Jon E; Pitre, Emile; Lalic, Nevena; Sampson, Paul D; Wakimoto, Barbara T

    2012-01-01

    Undergraduates entering science curricula differ greatly in individual starting points and learning needs. The fast pace, high enrollment, and high stakes of introductory science courses, however, limit students' opportunities to self-assess and modify learning strategies. The University of Washington's Biology Fellows Program (BFP) intervenes through a 20-session, premajors course that introduces students to the rigor expected of bioscience majors and assists their development as science learners. This study uses quantitative and qualitative approaches to assess whether the 2007-2009 BFP achieved its desired short- and long-term impacts on student learning. Adjusting for differences in students' high school grade point average and Scholastic Aptitude Test scores, we found that participation in the BFP was associated with higher grades in two subsequent gateway biology courses, across multiple quarters and instructors. Two to 4 yr after participating in the program, students attributed changes in how they approached learning science to BFP participation. They reported having learned to "think like a scientist" and to value active-learning strategies and learning communities. In addition, they reported having developed a sense of belonging in bioscience communities. The achievement of long-term impacts for a short-term instructional investment suggests a practical means to prepare diverse students for the rigors of science curricula.

  6. Educational environment and approaches to learning of undergraduate nursing students in an Indonesian school of nursing.

    Science.gov (United States)

    Rochmawati, Erna; Rahayu, Gandes Retno; Kumara, Amitya

    2014-11-01

    The aims of this study were to assess students' perceptions of their educational environment and approaches to learning, and determine if perceptions of learning environment associates with approaches to learning. A survey was conducted to collect data from a regional private university in Indonesia. A total of 232 nursing students completed two questionnaires that measured their perceptions of educational environment and approaches to learning. The measurement was based on Dundee Ready Education Environment Measurement (DREEM) and Approaches and Study Skills Inventory for Students (ASSIST). Five learning environments dimensions and three learning approaches dimensions from two measures were measured. The overall score of DREEM was 131.03/200 (SD 17.04), it was in the range considered to be favourable. The overall score is different significantly between years of study (p value = 0.01). This study indicated that the majority of undergraduate nursing students' adopt strategic approach (n = 139. 59.9%). The finding showed that perceived educational environment significantly associated with approaches to learning. This study implicated the need to maintain conducive learning environment. There is also a need to improve the management of learning activities that reflect the use of student-centered learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Examining the Roles of Blended Learning Approaches in Computer-Supported Collaborative Learning (CSCL) Environments: A Delphi Study

    Science.gov (United States)

    So, Hyo-Jeong; Bonk, Curtis J.

    2010-01-01

    In this study, a Delphi method was used to identify and predict the roles of blended learning approaches in computer-supported collaborative learning (CSCL) environments. The Delphi panel consisted of experts in online learning from different geographic regions of the world. This study discusses findings related to (a) pros and cons of blended…

  8. Mathematical beauty in service of deep approach to learning

    DEFF Research Database (Denmark)

    Karamehmedovic, Mirza

    2015-01-01

    was hands-on MATLAB programming, where the algorithms were tested and applied to solve physical modelbased problems. To encourage a deep approach, and discourage a surface approach to learning, I introduced into the lectures a basic but rigorous mathematical treatment of crucial theoretical points...

  9. Think Pair Share Using Realistic Mathematics Education Approach in Geometry Learning

    Science.gov (United States)

    Afthina, H.; Mardiyana; Pramudya, I.

    2017-09-01

    This research aims to determine the impact of mathematics learning applying Think Pair Share (TPS) using Realistic Mathematics Education (RME) viewed from mathematical-logical intelligence in geometry learning. Method that used in this research is quasi experimental research The result of this research shows that (1) mathematics achievement applying TPS using RME approach gives a better result than those applying direct learning model; (2) students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low one, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one; (3) there is no interaction between learning model and the level of students’ mathematical-logical intelligence in giving a mathematics achievement. The impact of this research is that TPS model using RME approach can be applied in mathematics learning so that students can learn more actively and understand the material more, and mathematics learning become more meaningful. On the other hand, internal factors of students must become a consideration toward the success of students’ mathematical achievement particularly in geometry material.

  10. Learning intervention and the approach to study of engineering undergraduates

    Science.gov (United States)

    Solomonides, Ian Paul

    The aim of the research was to: investigate the effect of a learning intervention on the Approach to Study of first year engineering degree students. The learning intervention was a local programme of learning to learn' workshops designed and facilitated by the author. The primary aim of these was to develop students' Approaches to Study. Fifty-three first year engineering undergraduates at The Nottingham Trent University participated in the workshops. Approaches to Study were quantified using data obtained from the Revised Approach to Study Inventory (RASI) which was also subjected to a validity and reliability study using local data. Quantitative outcomes were supplemented using a qualitative analysis of essays written by students during the workshops. These were analysed for detail regarding student Approach to Study. It was intended that any findings would inform the local system of Engineering Education, although more general findings also emerged, in particular in relation to the utility of the research instrument. It was concluded that the intervention did not promote the preferential Deep Approach and did not affect Approaches to Study generally as measured by the RASI. This concurred with previous attempts to change student Approaches to Study at the group level. It was also established that subsequent years of the Integrated Engineering degree course are associated with progressively deteriorating Approaches to Study. Students who were exposed to the intervention followed a similar pattern of deteriorating Approaches suggesting that the local course context and its demands had a greater influence over the Approach of students than the intervention did. It was found that academic outcomes were unrelated to the extent to which students took a Deep Approach to the local assessment demands. There appeared therefore to be a mis-match between the Approach students adopted to pass examinations and those that are required for high quality learning outcomes. It is

  11. Elementary Students' Generalization and Representation of Functional Relationships: A Learning Progressions Approach

    Science.gov (United States)

    Stephens, Ana; Fonger, Nicole L.; Blanton, Maria; Knuth, Eric

    2016-01-01

    In this paper, we describe our learning progressions approach to early algebra research that involves the coordination of a curricular framework, an instructional sequence, written assessments, and levels of sophistication describing the development of students' thinking. We focus in particular on what we have learning through this approach about…

  12. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

    Science.gov (United States)

    Guindon, Stéphane; Dufayard, Jean-François; Lefort, Vincent; Anisimova, Maria; Hordijk, Wim; Gascuel, Olivier

    2010-05-01

    PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.

  13. Superconducting magnet for 'ML-100'

    Energy Technology Data Exchange (ETDEWEB)

    Saito, R; Fujinaga, T; Tada, N; Kimura, H

    1974-07-01

    A magneticaly levitated experimental vehicle (Ml-100) was designed and constructed in commemoration of the centenary of the Japanese National Railways. For magnetic levitation the vehicle is provided with two superconducting magnets. In the test operation of the vehicle, these superconducting magnets showed stable performance in levitating vehicle body.

  14. The Relationship between Motivation, Learning Approaches, Academic Performance and Time Spent

    Science.gov (United States)

    Everaert, Patricia; Opdecam, Evelien; Maussen, Sophie

    2017-01-01

    Previous literature calls for further investigation in terms of precedents and consequences of learning approaches (deep learning and surface learning). Motivation as precedent and time spent and academic performance as consequences are addressed in this paper. The study is administered in a first-year undergraduate course. Results show that the…

  15. Localized Multiple Kernel Learning A Convex Approach

    Science.gov (United States)

    2016-11-22

    data. All the aforementioned approaches to localized MKL are formulated in terms of non-convex optimization problems, and deep the- oretical...learning. IEEE Transactions on Neural Networks, 22(3):433–446, 2011. Jingjing Yang, Yuanning Li, Yonghong Tian, Lingyu Duan, and Wen Gao. Group-sensitive

  16. ML-7 amplifies the quinocetone-induced cell death through akt and MAPK-mediated apoptosis on HepG2 cell line.

    Science.gov (United States)

    Zhou, Yan; Zhang, Shen; Deng, Sijun; Dai, Chongshan; Tang, Shusheng; Yang, Xiayun; Li, Daowen; Zhao, Kena; Xiao, Xilong

    2016-01-01

    The study aims at evaluating the combination of the quinocetone and the ML-7 in preclinical hepatocellular carcinoma models. To this end, the effect of quinocetone and ML-7 on apoptosis induction and signaling pathways was analyzed on HepG2 cell lines. Here, we report that ML-7, in a nontoxic concentration, sensitized the HepG2 cells to quinocetone-induced cytotoxicity. Also, ML-7 profoundly enhances quinocetone-induced apoptosis in HepG2 cell line. Mechanistic investigations revealed that ML-7 and quinocetone act in concert to trigger the cleavage of caspase-8 as well as Bax/Bcl-2 ratio up-regulation and subsequent cleavage of Bid, capsases-9 and -3. Importantly, ML-7 weakened the quinocetone-induced Akt pathway activation, but strengthened the phosphorylation of p-38, ERK and JNK. Further treatment of Akt activator and p-38 inhibitor almost completely abolished the ML-7/quinocetone-induced apoptosis. In contrast, the ERK and JNK inhibitor aggravated the ML-7/quinocetone-induced apoptosis, indicating that the synergism critically depended on p-38 phosphorylation and HepG2 cells provoke Akt, ERK and JNK signaling pathways to against apoptosis. In conclusion, the rational combination of quinocetone and ML-7 presents a promising approach to trigger apoptosis in hepatocellular carcinoma, which warrants further investigation.

  17. A practical guide to SysML the systems modeling language

    CERN Document Server

    Friendenthal,Sanford; Steiner, Rick

    2009-01-01

    This book is the bestselling, authoritative guide to SysML for systems and software engineers, providing a comprehensive and practical resource for modeling systems with SysML. Fully updated to cover newly released version 1.3, it includes a full description of the modeling language along with a quick reference guide, and shows how an organization or project can transition to model-based systems engineering using SysML, with considerations for processes, methods, tools, and training. Numerous examples help readers understand how SysML can be used in practice, while reference material facilitates studying for the OMG Systems Modeling Professional (OCSMP) Certification Program, designed to test candidates' knowledge of SysML and their ability to use models to represent real-world systems.

  18. Aggressiveness of powdery mildew on 'ml-o'- resistant barley

    International Nuclear Information System (INIS)

    Andersen, Lars

    1990-01-01

    The ml-o genes in barley are important sources in breeding for resistance against the barley powdery mildew fungus (Erysiphe graminis). The resistance mechanism is a rapid formation of a large callose containing cell wall apposition at the site of the pathogen's infection attempt. This reduces the chances of infection to almost nil in all epidermal cells, except in the small subsidiary cells, in which appositions are rarely formed. Small mildew colonies from infections in subsidiary cells may be seen on the otherwise resistant leaf. This is described by the infection type 0/(4). Mildew isolate HL 3 selected by SCHWARZBACH has increased aggressiveness. No ml-o-virulent isolates are known. However, ml-o-resistant varieties when grown extensively in Europe, will introduce field selection for mildew pathotypes with aggressiveness or virulence to ml-o resistance. Studies on increased aggressiveness require new methods. The material comprises two powdery mildew isolates: GE 3 without ml-o aggressiveness and the aggressive HL 3/5; and two near-isogenic barley lines in Carlsberg II: Riso 5678(R) with the recessive mutant resistance gene ml-o5 and Riso 5678(S) with the wild-type gene for susceptibility. Latent period and disease efficiency show no significant differences between the two isolates on the susceptible barley line (S) but the isolates differ from each other on the resistant barley line

  19. A Mobile Device Based Serious Gaming Approach for Teaching and Learning Java Programming

    Directory of Open Access Journals (Sweden)

    Tobias Jordine

    2015-01-01

    Full Text Available Most first year computer science students find that learning object-oriented programming is hard. Serious games have ever been used as one approach to handle this problem. But most of them cannot be played with mobile devices. This obviously does not suit the era of mobile computing that intends to allow students to learn programming skills in anytime anywhere. To enhance mobile teaching and learning, a research project started over a year ago and aims to create a mobile device based serious gaming approach along with a serious game for enhancing mobile teaching and learning for Java programming. So far the project has completed a literature review for understanding existing work and identifying problems in this area, conducted a survey for eliciting students’ requirements for mobile gaming approach, and then established a mobile-device based serious gaming approach with a developed prototype of the game. This paper introduces the project in details, and in particularly presents and discusses its current results. It is expected that the presented project will be helpful and useful to bring more efficient approaches with new mobile games into teaching object-oriented programming and to enhance students’ learning experiences.

  20. Modelling CRM implementation services with SysML

    OpenAIRE

    Bibiano, Luis H.; Pastor Collado, Juan Antonio; Mayol Sarroca, Enric

    2009-01-01

    CRM information systems are valuable tools for enterprises. But CRM implementation projects are risky and present a high failure rate. In this paper we regard CRM implementation projects as services that could be greatly improved by addressing them in a methodological way that can be designed with the help of tools such as SysML. Here we introduce and comment on our first experience on the use of SysML language, not very well known, for modelling the elements involved in the CRM implementatio...

  1. Leveraging knowledge engineering and machine learning for microbial bio-manufacturing.

    Science.gov (United States)

    Oyetunde, Tolutola; Bao, Forrest Sheng; Chen, Jiung-Wen; Martin, Hector Garcia; Tang, Yinjie J

    2018-05-03

    Genome scale modeling (GSM) predicts the performance of microbial workhorses and helps identify beneficial gene targets. GSM integrated with intracellular flux dynamics, omics, and thermodynamics have shown remarkable progress in both elucidating complex cellular phenomena and computational strain design (CSD). Nonetheless, these models still show high uncertainty due to a poor understanding of innate pathway regulations, metabolic burdens, and other factors (such as stress tolerance and metabolite channeling). Besides, the engineered hosts may have genetic mutations or non-genetic variations in bioreactor conditions and thus CSD rarely foresees fermentation rate and titer. Metabolic models play important role in design-build-test-learn cycles for strain improvement, and machine learning (ML) may provide a viable complementary approach for driving strain design and deciphering cellular processes. In order to develop quality ML models, knowledge engineering leverages and standardizes the wealth of information in literature (e.g., genomic/phenomic data, synthetic biology strategies, and bioprocess variables). Data driven frameworks can offer new constraints for mechanistic models to describe cellular regulations, to design pathways, to search gene targets, and to estimate fermentation titer/rate/yield under specified growth conditions (e.g., mixing, nutrients, and O 2 ). This review highlights the scope of information collections, database constructions, and machine learning techniques (such as deep learning and transfer learning), which may facilitate "Learn and Design" for strain development. Copyright © 2018. Published by Elsevier Inc.

  2. Relational Analysis of College Chemistry-Major Students' Conceptions of and Approaches to Learning Chemistry

    Science.gov (United States)

    Li, Wei-Ting; Liang, Jyh-Chong; Tsai, Chin-Chung

    2013-01-01

    The purpose of this research was to examine the relationships between conceptions of learning and approaches to learning in chemistry. Two questionnaires, conceptions of learning chemistry (COLC) and approaches to learning chemistry (ALC), were developed to identify 369 college chemistry-major students' (220 males and 149 females) conceptions of…

  3. First-Year Students' Approaches to Learning, and Factors Related to Change or Stability in Their Deep Approach during a Pharmacy Course

    Science.gov (United States)

    Varunki, Maaret; Katajavuori, Nina; Postareff, Liisa

    2017-01-01

    Research shows that a surface approach to learning is more common among students in the natural sciences, while students representing the "soft" sciences are more likely to apply a deep approach. However, findings conflict concerning the stability of approaches to learning in general. This study explores the variation in students'…

  4. Sequenced Integration and the Identification of a Problem-Solving Approach through a Learning Process

    Science.gov (United States)

    Cormas, Peter C.

    2016-01-01

    Preservice teachers (N = 27) in two sections of a sequenced, methodological and process integrated mathematics/science course solved a levers problem with three similar learning processes and a problem-solving approach, and identified a problem-solving approach through one different learning process. Similar learning processes used included:…

  5. A New Design Approach to game or play based learning

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    to ground the students sense of meaning. This paper proposes another approach: using visualization in immersive 3D-worlds as documentation of learning progress while at the same time constituting a reward system which motivate further learning. The overall design idea is to build a game based learning......Abstract: The present paper proposes a new design perspective for game based learning. The general idea is to abandon the long and sought after dream of designing a closed learning system, where students from elementary school to high school without teachers’ interference could learn whatever...... game based learning system, but also confront aspects of modern learning theory especially the notion of reference between content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way to tackle the common experience...

  6. Vocation, Motivation and Approaches to Learning: A Comparative Study

    Science.gov (United States)

    Arquero, Jose Luis; Fernández-Polvillo, Carmen; Hassall, Trevor; Joyce, John

    2015-01-01

    Purpose: The individual characteristics of students can have a strong influence on the success of the adopted innovations in terms of their transferability and sustainability. The purpose of this paper is to compare the motivations and approaches to learning on degrees with differing vocational components. Design/methodology/approach:…

  7. Specification and Design of Electrical Flight System Architectures with SysML

    Science.gov (United States)

    McKelvin, Mark L., Jr.; Jimenez, Alejandro

    2012-01-01

    Modern space flight systems are required to perform more complex functions than previous generations to support space missions. This demand is driving the trend to deploy more electronics to realize system functionality. The traditional approach for the specification, design, and deployment of electrical system architectures in space flight systems includes the use of informal definitions and descriptions that are often embedded within loosely coupled but highly interdependent design documents. Traditional methods become inefficient to cope with increasing system complexity, evolving requirements, and the ability to meet project budget and time constraints. Thus, there is a need for more rigorous methods to capture the relevant information about the electrical system architecture as the design evolves. In this work, we propose a model-centric approach to support the specification and design of electrical flight system architectures using the System Modeling Language (SysML). In our approach, we develop a domain specific language for specifying electrical system architectures, and we propose a design flow for the specification and design of electrical interfaces. Our approach is applied to a practical flight system.

  8. IrML – a gene encoding a new member of the ML protein family from the hard tick, Ixodes ricinus

    Czech Academy of Sciences Publication Activity Database

    Horáčková, J.; Rudenko, Natalia; Golovchenko, Maryna; Havlíková, S.; Grubhoffer, Libor

    2010-01-01

    Roč. 35, č. 2 (2010), s. 410-418 ISSN 1081-1710 R&D Projects: GA ČR(CZ) GA524/06/1479; GA MŠk(CZ) LC06009 Institutional research plan: CEZ:AV0Z60220518 Keywords : Ixodes ricinus * tick * ML-domain containing protein * in situ hybridization * gene expression * ML (MD-2-related lipid-recognition) domain Subject RIV: GJ - Animal Vermins ; Diseases, Veterinary Medicine Impact factor: 1.256, year: 2010

  9. Exploring the Behavioural Patterns of Entrepreneurial Learning: A Competency Approach

    Science.gov (United States)

    Man, Thomas Wing Yan

    2006-01-01

    Purpose: The purpose of this study is to empirically explore the behavioural patterns involved in entrepreneurial learning through a conceptualization of entrepreneurial learning as a "competency". Design/methodology/approach: Semi-structured interviews to 12 entrepreneurs were conducted with a focus on the critical incidents in which…

  10. Structure-based sampling and self-correcting machine learning for accurate calculations of potential energy surfaces and vibrational levels

    Science.gov (United States)

    Dral, Pavlo O.; Owens, Alec; Yurchenko, Sergei N.; Thiel, Walter

    2017-06-01

    We present an efficient approach for generating highly accurate molecular potential energy surfaces (PESs) using self-correcting, kernel ridge regression (KRR) based machine learning (ML). We introduce structure-based sampling to automatically assign nuclear configurations from a pre-defined grid to the training and prediction sets, respectively. Accurate high-level ab initio energies are required only for the points in the training set, while the energies for the remaining points are provided by the ML model with negligible computational cost. The proposed sampling procedure is shown to be superior to random sampling and also eliminates the need for training several ML models. Self-correcting machine learning has been implemented such that each additional layer corrects errors from the previous layer. The performance of our approach is demonstrated in a case study on a published high-level ab initio PES of methyl chloride with 44 819 points. The ML model is trained on sets of different sizes and then used to predict the energies for tens of thousands of nuclear configurations within seconds. The resulting datasets are utilized in variational calculations of the vibrational energy levels of CH3Cl. By using both structure-based sampling and self-correction, the size of the training set can be kept small (e.g., 10% of the points) without any significant loss of accuracy. In ab initio rovibrational spectroscopy, it is thus possible to reduce the number of computationally costly electronic structure calculations through structure-based sampling and self-correcting KRR-based machine learning by up to 90%.

  11. A Mixed Learning Approach in Mechatronics Education

    Science.gov (United States)

    Yilmaz, O.; Tuncalp, K.

    2011-01-01

    This study aims to investigate the effect of a Web-based mixed learning approach model on mechatronics education. The model combines different perception methods such as reading, listening, and speaking and practice methods developed in accordance with the vocational background of students enrolled in the course Electromechanical Systems in…

  12. A SOCIO-COGNITIVE APPROACH TO KNOWLEDGE CONSTRUCTION THROUGH BLENDED LEARNING

    Directory of Open Access Journals (Sweden)

    Tuba Kocaturk

    2017-01-01

    Full Text Available This paper results from an educational research project that was undertaken by the School of Architecture, at the University of Liverpool funded by the Higher Education Academy in UK. The research explored technology driven shifts in architectural design studio education, identified their cognitive effects on design learning and developed an innovative blended learning approach that was implemented at a masters level digital design studio. The contribution of the research and the proposed approach to the existing knowledge and practice are twofold. Firstly, it offers a new pedagogical framework which integrates social, technical and cognitive dimensions of knowledge construction. And secondly, it offers a unique operational model through the integration of both mediational and instrumental use of digital media. The proposed model provides a useful basis for the effective mobilization of next generation learning technologies which can effectively respond to the learning challenges specific to architectural design knowledge and its means of creation.

  13. The Effect of Integrated Learning-Teaching Approach on Reading Comprehension and Narration Skills

    Directory of Open Access Journals (Sweden)

    Ergün Hamzadayı

    2010-12-01

    Full Text Available This study investigated the effects of integrated learning-teaching approach on reading comprehension and narration skills. Considerations regarding how to overcome difficulties in the teaching of Turkish language through multi-theoretical perspectives have resulted in this approach to come into the existence. For the purpose of forming theoretical foundations of the research, behaviourist, cognitive and constructivist learning theories with their philosophical foundations were introduced, their principals and assumptions with regard to instructional design were compared, and their strengths and weakness were delineated. These considerations were then associated with the components of Turkish language program (content, objectives, teaching strategies and methods, assessment and that paved way for “integrative learning and teaching approach” to come into being. This study aimed to investigate whether there is a significant difference between the performance of the experimental group students who were exposed to integrative learning and teaching approach and that of control group students who were not exposed to integrative learning and teaching approach in terms of reading comprehension and written expression skills in Turkish language

  14. A Context-Aware Ubiquitous Learning Approach for Providing Instant Learning Support in Personal Computer Assembly Activities

    Science.gov (United States)

    Hsu, Ching-Kun; Hwang, Gwo-Jen

    2014-01-01

    Personal computer assembly courses have been recognized as being essential in helping students understand computer structure as well as the functionality of each computer component. In this study, a context-aware ubiquitous learning approach is proposed for providing instant assistance to individual students in the learning activity of a…

  15. ML Arvutite aktsiakapital suurenes / Anne Oja

    Index Scriptorium Estoniae

    Oja, Anne, 1970-

    2006-01-01

    ML Arvutid omanik Aivar Paalberg tõstis aktsiakapitali seniselt 10 miljonilt 24 miljonile eesmärgiga tugevdada oma positsioone Eesti turul ja kasvada kiiremas tempos kui kogu turg. Diagramm: Majandusnäitajad

  16. 3 Colleges' Different Approaches Shape Learning in Econ 101

    Science.gov (United States)

    Berrett, Dan

    2012-01-01

    No matter the college, a class in the principles of microeconomics is likely to cover the discipline's greatest hits. The author attends three economics courses at three colleges, and finds three very different approaches. In this article, the author discusses three colleges' different approaches that shape learning in Econ 101.

  17. Teaching Newton's 3rd law of motion using learning by design approach

    Science.gov (United States)

    Aquino, Jiezel G.; Caliguid, Mariel P.; Buan, Amelia T.; Magsayod, Joy R.; Lahoylahoy, Myrna E.

    2018-01-01

    This paper presents the process and implementation of Learning by Design Approach in teaching Newton's 3rd Law of Motion. A lesson activity from integrative STEM education was adapted, modified and enhanced through pilot testing. After revisions, the implementation was done to one class. The respondent's prior knowledge was first assessed by a pretest. PPIT (present the scenario, plan, implement and test) was the framework followed in the implementation of Learning by Design. Worksheets were then utilized to measure their conceptual understanding and perception. A score guide was also used to evaluate the student's output. Paired t-test analysis showed that there is a significant difference in the pretest and posttest achievement scores. This implies that the performance of the students have improved during the implementation of the Learning by Design. The Analysis of variance also depicts that the low, average and high benefited in the Learning by Design approach. The results of this study suggests that Learning by Design is an effective approach in teaching Newton's 3rd Law of Motion and thus be used in a Science classroom.

  18. Transformative Learning Approaches for Public Relations Pedagogy

    Science.gov (United States)

    Motion, Judy; Burgess, Lois

    2014-01-01

    Public relations educators are frequently challenged by students' flawed perceptions of public relations. Two contrasting case studies are presented in this paper to illustrate how socially-oriented paradigms may be applied to a real-client project to deliver a transformative learning experience. A discourse-analytic approach is applied within the…

  19. Designing e-learning solutions with a client centred approach

    DEFF Research Database (Denmark)

    Ørngreen, Rikke; Nielsen, Janni; Levinsen, Karin

    2008-01-01

      This paper claims that the strategies applied in designing e-learning solutions tend to focus on how to proceed after the precondition, e.g., learners requirements, pedagogical choice, etc., have been decided upon. Investigating the HCI research field, we find that the methodological approaches...... as the organisation that has initiated the e-learning project and needs to manage the e-learning system after its development. Through the Client Centred Design and in close collaboration with the client, three strategic issues are uncovered and strategic models are presented for each. These models are complementary...... perspectives in a Client Centred framework that is useable as the starting point for others in developing large scale e-learning projects....

  20. Restoring Proprioception via a Cortical Prosthesis: A Novel Learning-Based Approach

    Science.gov (United States)

    2015-10-01

    AWARD NUMBER: W81XWH-14-1-0510 TITLE: Restoring Proprioception via a Cortical Prosthesis : A Novel Learning-Based Approach PRINCIPAL INVESTIGATOR...Proprioception via a Cortical Prosthesis : A Novel Learning-Based Approach 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Philip Sabes, PhD 5d...component of this lost sensation is proprioception, the feeling of where the body is in space. The importance of proprioception is often not appreciated

  1. Evaluation of students' perception of their learning environment and approaches to learning

    Science.gov (United States)

    Valyrakis, Manousos; Cheng, Ming

    2015-04-01

    This work presents the results of two case studies designed to assess the various approaches undergraduate and postgraduate students undertake for their education. The first study describes the results and evaluation of an undergraduate course in Water Engineering which aims to develop the fundamental background knowledge of students on introductory practical applications relevant to the practice of water and hydraulic engineering. The study assesses the effectiveness of the course design and learning environment from the perception of students using a questionnaire addressing several aspects that may affect student learning, performance and satisfaction, such as students' motivation, factors to effective learning, and methods of communication and assessment. The second study investigates the effectiveness of supervisory arrangements based on the perceptions of engineering undergraduate and postgraduate students. Effective supervision requires leadership skills that are not taught in the University, yet there is rarely a chance to get feedback, evaluate this process and reflect. Even though the results are very encouraging there are significant lessons to learn in improving ones practice and develop an effective learning environment to student support and guidance. The findings from these studies suggest that students with high level of intrinsic motivation are deep learners and are also top performers in a student-centered learning environment. A supportive teaching environment with a plethora of resources and feedback made available over different platforms that address students need for direct communication and feedback has the potential to improve student satisfaction and their learning experience. Finally, incorporating a multitude of assessment methods is also important in promoting deep learning. These results have deep implications about student learning and can be used to further improve course design and delivery in the future.

  2. [Efficacy of the program "Testas's (mis)adventures" to promote the deep approach to learning].

    Science.gov (United States)

    Rosário, Pedro; González-Pienda, Julio Antonio; Cerezo, Rebeca; Pinto, Ricardo; Ferreira, Pedro; Abilio, Lourenço; Paiva, Olimpia

    2010-11-01

    This paper provides information about the efficacy of a tutorial training program intended to enhance elementary fifth graders' study processes and foster their deep approaches to learning. The program "Testas's (mis)adventures" consists of a set of books in which Testas, a typical student, reveals and reflects upon his life experiences during school years. These life stories are nothing but an opportunity to present and train a wide range of learning strategies and self-regulatory processes, designed to insure students' deeper preparation for present and future learning challenges. The program has been developed along a school year, in a one hour weekly tutorial sessions. The training program had a semi-experimental design, included an experimental group (n=50) and a control one (n=50), and used pre- and posttest measures (learning strategies' declarative knowledge, learning approaches and academic achievement). Data suggest that the students enrolled in the training program, comparing with students in the control group, showed a significant improvement in their declarative knowledge of learning strategies and in their deep approach to learning, consequently lowering their use of a surface approach. In spite of this, in what concerns to academic achievement, no statistically significant differences have been found.

  3. CytometryML and other data formats

    Science.gov (United States)

    Leif, Robert C.

    2006-02-01

    Cytology automation and research will be enhanced by the creation of a common data format. This data format would provide the pathology and research communities with a uniform way for annotating and exchanging images, flow cytometry, and associated data. This specification and/or standard will include descriptions of the acquisition device, staining, the binary representations of the image and list-mode data, the measurements derived from the image and/or the list-mode data, and descriptors for clinical/pathology and research. An international, vendor-supported, non-proprietary specification will allow pathologists, researchers, and companies to develop and use image capture/analysis software, as well as list-mode analysis software, without worrying about incompatibilities between proprietary vendor formats. Presently, efforts to create specifications and/or descriptions of these formats include the Laboratory Digital Imaging Project (LDIP) Data Exchange Specification; extensions to the Digital Imaging and Communications in Medicine (DICOM); Open Microscopy Environment (OME); Flowcyt, an extension to the present Flow Cytometry Standard (FCS); and CytometryML. The feasibility of creating a common data specification for digital microscopy and flow cytometry in a manner consistent with its use for medical devices and interoperability with both hospital information and picture archiving systems has been demonstrated by the creation of the CytometryML schemas. The feasibility of creating a software system for digital microscopy has been demonstrated by the OME. CytometryML consists of schemas that describe instruments and their measurements. These instruments include digital microscopes and flow cytometers. Optical components including the instruments' excitation and emission parts are described. The description of the measurements made by these instruments includes the tagged molecule, data acquisition subsystem, and the format of the list-mode and/or image data. Many

  4. A New Learning Approach: Flipped Classroom and Its Impacts

    Science.gov (United States)

    Yildirim, Gürkan

    2017-01-01

    The aim of this study is to present opinions of undergraduate students towards Flipped Classroom (FC) practices and to determine their different aspects then traditional learning approaches. The case study approach is preferred to conduct the study. In this context, 34 volunteered students were included in the study group by purposive sampling…

  5. Learning User Preferences in Ubiquitous Systems: A User Study and a Reinforcement Learning Approach

    OpenAIRE

    Zaidenberg , Sofia; Reignier , Patrick; Mandran , Nadine

    2010-01-01

    International audience; Our study concerns a virtual assistant, proposing services to the user based on its current perceived activity and situation (ambient intelligence). Instead of asking the user to define his preferences, we acquire them automatically using a reinforcement learning approach. Experiments showed that our system succeeded the learning of user preferences. In order to validate the relevance and usability of such a system, we have first conducted a user study. 26 non-expert s...

  6. Using the Blended Learning Approach in a Quantitative Literacy Course

    Science.gov (United States)

    Botts, Ryan T.; Carter, Lori; Crockett, Catherine

    2018-01-01

    The efforts to improve the quantitative reasoning (quantitative literacy) skills of college students in the United States have been gaining momentum in recent years. At the same time, the blended learning approach to course delivery has gained in popularity, promising better learning with flexible modalities and pace. This paper presents the…

  7. ML-MG: Multi-label Learning with Missing Labels Using a Mixed Graph

    KAUST Repository

    Wu, Baoyuan

    2015-12-07

    This work focuses on the problem of multi-label learning with missing labels (MLML), which aims to label each test instance with multiple class labels given training instances that have an incomplete/partial set of these labels (i.e. some of their labels are missing). To handle missing labels, we propose a unified model of label dependencies by constructing a mixed graph, which jointly incorporates (i) instance-level similarity and class co-occurrence as undirected edges and (ii) semantic label hierarchy as directed edges. Unlike most MLML methods, We formulate this learning problem transductively as a convex quadratic matrix optimization problem that encourages training label consistency and encodes both types of label dependencies (i.e. undirected and directed edges) using quadratic terms and hard linear constraints. The alternating direction method of multipliers (ADMM) can be used to exactly and efficiently solve this problem. To evaluate our proposed method, we consider two popular applications (image and video annotation), where the label hierarchy can be derived from Wordnet. Experimental results show that our method achieves a significant improvement over state-of-the-art methods in performance and robustness to missing labels.

  8. PENGEMBANGAN PENDIDIKAN KARAKTER DALAM MATA KULIAH EVALUASI PEMBELAJARAN MELALUI PENDEKATAN DEEP APPROACH TO LEARNING

    Directory of Open Access Journals (Sweden)

    Nanik Suryani

    2016-01-01

    Full Text Available The objectives of this study are to find and to test the model of characters education in Learning Evaluation Subject through deep approach to learning. The subject of the study is the class of Learning Evaluation of Office Administration Program, Economics Education Department, Economics Faculty, Semarang State University. The data are collected by a test, and then analyzed by qualitative descriptive. The result of this study showed that the model of characters education through deep approach to learning could improve students’ self awareness in learning the subject.

  9. PENGEMBANGAN PENDIDIKAN KARAKTER DALAM MATA KULIAH EVALUASI PEMBELAJARAN MELALUI PENDEKATAN DEEP APPROACH TO LEARNING

    Directory of Open Access Journals (Sweden)

    Nanik Suryani

    2012-12-01

    Full Text Available The objectives of this study are to find and to test the model of characters education in Learning Evaluation Subject through deep approach to learning. The subject of the study is the class of Learning Evaluation of Office Administration Program, Economics Education Department, Economics Faculty, Semarang State University. The data are collected by a test, and then analyzed by qualitative descriptive. The result of this study showed that the model of characters education through deep approach to learning could improve students’ self awareness in learning the subject.

  10. Student perceptions of independent versus facilitated small group learning approaches to compressed medical anatomy education.

    Science.gov (United States)

    Whelan, Alexander; Leddy, John J; Mindra, Sean; Matthew Hughes, J D; El-Bialy, Safaa; Ramnanan, Christopher J

    2016-01-01

    The purpose of this study was to compare student perceptions regarding two, small group learning approaches to compressed (46.5 prosection-based laboratory hours), integrated anatomy education at the University of Ottawa medical program. In the facilitated active learning (FAL) approach, tutors engage students and are expected to enable and balance both active learning and progression through laboratory objectives. In contrast, the emphasized independent learning (EIL) approach stresses elements from the "flipped classroom" educational model: prelaboratory preparation, independent laboratory learning, and limited tutor involvement. Quantitative (Likert-style questions) and qualitative data (independent thematic analysis of open-ended commentary) from a survey of students who had completed the preclerkship curriculum identified strengths from the EIL (promoting student collaboration and communication) and FAL (successful progression through objectives) approaches. However, EIL led to student frustration related to a lack of direction and impaired completion of objectives, whereas active learning opportunities in FAL were highly variable and dependent on tutor teaching style. A "hidden curriculum" was also identified, where students (particularly EIL and clerkship students) commonly compared their compressed anatomy education or their anatomy learning environment with other approaches. Finally, while both groups highly regarded the efficiency of prosection-based learning and expressed value for cadaveric-based learning, student commentary noted that the lack of grade value dedicated to anatomy assessment limited student accountability. This study revealed critical insights into small group learning in compressed anatomy education, including the need to balance student active learning opportunities with appropriate direction and feedback (including assessment). © 2015 American Association of Anatomists.

  11. PlayIt: Game Based Learning Approach for Teaching Programming Concepts

    Science.gov (United States)

    Mathrani, Anuradha; Christian, Shelly; Ponder-Sutton, Agate

    2016-01-01

    This study demonstrates a game-based learning (GBL) approach to engage students in learning and enhance their programming skills. The paper gives a detailed narrative of how an educational game was mapped with the curriculum of a prescribed programming course in a computing diploma study programme. Two separate student cohorts were invited to…

  12. Learner differences and learning outcomes in an introductory biochemistry class: attitude toward images, visual cognitive skills, and learning approach.

    Science.gov (United States)

    Milner, Rachel E

    2014-01-01

    The practice of using images in teaching is widespread, and in science education images are used so extensively that some have argued they are now the "main vehicle of communication" (C. Ferreira, A. Arroio Problems Educ. 21st Century 2009, 16, 48-53). Although this phenomenon is especially notable in the field of biochemistry, we know little about the role and importance of images in communicating concepts to students in the classroom. This study reports the development of a scale to assess students' attitude toward biochemical images, particularly their willingness and ability to use the images to support their learning. In addition, because it is argued that images are central in the communication of biochemical concepts, we investigated three "learner differences" which might impact learning outcomes in this kind of classroom environment: attitude toward images, visual cognitive skills, and learning approach. Overall, the students reported a positive attitude toward the images, the majority agreeing that they liked images and considered them useful. However, the participants also reported that verbal explanations were more important than images in helping them to understand the concepts. In keeping with this we found that there was no relationship between learning outcomes and the students' self-reported attitude toward images or visual cognitive skills. In contrast, learning outcomes were significantly correlated with the students' self-reported approach to learning. These findings suggest that images are not necessarily the main vehicle of communication in a biochemistry classroom and that verbal explanations and encouragement of a deep learning approach are important considerations in improving our pedagogical approach. © 2013 International Union of Biochemistry and Molecular Biology, Inc.

  13. Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems.

    Science.gov (United States)

    Kaya, Mehmet; Alhajj, Reda

    2005-04-01

    Multiagent systems and data mining have recently attracted considerable attention in the field of computing. Reinforcement learning is the most commonly used learning process for multiagent systems. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are experienced much less than others, or some state-action pairs are never visited during the learning phase. Further, before completing the learning process, an agent cannot exhibit a certain behavior in some states that may be experienced sufficiently. In this study, we propose a novel multiagent learning approach to handle these problems. Our approach is based on utilizing the mining process for modular cooperative learning systems. It incorporates fuzziness and online analytical processing (OLAP) based mining to effectively process the information reported by agents. First, we describe a fuzzy data cube OLAP architecture which facilitates effective storage and processing of the state information reported by agents. This way, the action of the other agent, not even in the visual environment. of the agent under consideration, can simply be predicted by extracting online association rules, a well-known data mining technique, from the constructed data cube. Second, we present a new action selection model, which is also based on association rules mining. Finally, we generalize not sufficiently experienced states, by mining multilevel association rules from the proposed fuzzy data cube. Experimental results obtained on two different versions of a well-known pursuit domain show the robustness and effectiveness of the proposed fuzzy OLAP mining based modular learning approach. Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning.

  14. Machine learning: novel bioinformatics approaches for combating antimicrobial resistance.

    Science.gov (United States)

    Macesic, Nenad; Polubriaginof, Fernanda; Tatonetti, Nicholas P

    2017-12-01

    Antimicrobial resistance (AMR) is a threat to global health and new approaches to combating AMR are needed. Use of machine learning in addressing AMR is in its infancy but has made promising steps. We reviewed the current literature on the use of machine learning for studying bacterial AMR. The advent of large-scale data sets provided by next-generation sequencing and electronic health records make applying machine learning to the study and treatment of AMR possible. To date, it has been used for antimicrobial susceptibility genotype/phenotype prediction, development of AMR clinical decision rules, novel antimicrobial agent discovery and antimicrobial therapy optimization. Application of machine learning to studying AMR is feasible but remains limited. Implementation of machine learning in clinical settings faces barriers to uptake with concerns regarding model interpretability and data quality.Future applications of machine learning to AMR are likely to be laboratory-based, such as antimicrobial susceptibility phenotype prediction.

  15. Learning morphological phenomena of modern Greek an exploratory approach

    Directory of Open Access Journals (Sweden)

    Y. Kotsanis

    1996-12-01

    Full Text Available Educational technology is influenced by and closely related to the fields of generative epistemology, Artificial Intelligence, and the learning sciences. Relevant research literature refers to the term constructionism (Papert, 1993 and exploratory learning (diSessa et al, 1995. Constructionism and exploratory learning are a synthesis of the constructivist theory of Piaget and the opportunities offered by technology to education on thinking concretely, on learning while constructing intelligible entities, and on interacting with multimedia objects, rather than the direct acquisition of knowledge and facts. These views are based on the approach that learners can take substantial control of their own learning in an appropriately designed physical and cultural environment (Harel, 1991. In parallel, most of the studies of the Vygotskian framework focus on the role of language in the learning procedure, considering conceptual thought to be impossible outside an articulated verbal thinking. Moreover, the specific use of words is considered to be the most relevant cause for childhood and adolescent differentiation (Vygotsky, 1962.

  16. Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization.

    Science.gov (United States)

    Turk, Samo; Merget, Benjamin; Rippmann, Friedrich; Fulle, Simone

    2017-12-26

    Matched molecular pair (MMP) analyses are widely used in compound optimization projects to gain insights into structure-activity relationships (SAR). The analysis is traditionally done via statistical methods but can also be employed together with machine learning (ML) approaches to extrapolate to novel compounds. The here introduced MMP/ML method combines a fragment-based MMP implementation with different machine learning methods to obtain automated SAR decomposition and prediction. To test the prediction capabilities and model transferability, two different compound optimization scenarios were designed: (1) "new fragments" which occurs when exploring new fragments for a defined compound series and (2) "new static core and transformations" which resembles for instance the identification of a new compound series. Very good results were achieved by all employed machine learning methods especially for the new fragments case, but overall deep neural network models performed best, allowing reliable predictions also for the new static core and transformations scenario, where comprehensive SAR knowledge of the compound series is missing. Furthermore, we show that models trained on all available data have a higher generalizability compared to models trained on focused series and can extend beyond chemical space covered in the training data. Thus, coupling MMP with deep neural networks provides a promising approach to make high quality predictions on various data sets and in different compound optimization scenarios.

  17. Suppression of phase separation in $(AlAs)_{2ML} (InAs)_{2ML}$ superlattices using $Al_{0.48}In_{0.52}$ As monolayer insertions

    CERN Document Server

    Lee, S R; Follstaedt, D M

    2001-01-01

    Al/sub 0.48/In/sub 0.52/As monolayers (ML) are inserted at the binary-compound interfaces of (AlAs)/sub 2/ /sub ML/(InAs)/sub 2/ /sub ML/ short-period superlattices (SPSs) during growth on (001) In P. The insertion of Al/sub 0.48/In/sub 0.52/As interlayers greater than 2 ML thick tends to suppress the phase separation that normally occurs during molecular beam epitaxy of the SPS. The degree of suppression is a sensitive function of both the monolayer-scale thickness, and the intraperiod growth sequence, of the interlayers in the SPS. Given this sensitivity to monolayer-scale variations in the surface-region composition, we propose that cyclical phase transition of the reconstructed surface initiates SPS decomposition. (21 refs).

  18. Evaluating Approaches to Teaching and Learning Chinese Vocabulary from the Learning Theories Perspective: An Experimental Case Study

    Directory of Open Access Journals (Sweden)

    Katja SIMONČIČ

    2015-06-01

    Full Text Available With Chinese language gaining more and more popularity among Slovenian students and with the growing numbers of learners of Chinese as a foreign language in Slovenia and elsewhere it is crucial to find an approach that will lead to high quality and long-term knowledge of Chinese and that will motivate learners to continue learning. We can speak of two basic approaches to teaching Chinese vocabulary: the approach that first introduces pronunciation and the approach that simultaneously introduces pronunciation and character. The key question that arises is which of the two approaches leads to high quality and long-term knowledge? To answer the question an experimental case study was carried out at Ljubljana’s Faculty of Arts in the academic year 2011/2012. The case study showed that the approach that simultaneously introduces pronunciation and character and is based on the key principles of constructivist learning theory had beneficial effects on the students in terms of motivation and quality of knowledge of Chinese vocabulary.

  19. SED-ML web tools: generate, modify and export standard-compliant simulation studies.

    Science.gov (United States)

    Bergmann, Frank T; Nickerson, David; Waltemath, Dagmar; Scharm, Martin

    2017-04-15

    The Simulation Experiment Description Markup Language (SED-ML) is a standardized format for exchanging simulation studies independently of software tools. We present the SED-ML Web Tools, an online application for creating, editing, simulating and validating SED-ML documents. The Web Tools implement all current SED-ML specifications and, thus, support complex modifications and co-simulation of models in SBML and CellML formats. Ultimately, the Web Tools lower the bar on working with SED-ML documents and help users create valid simulation descriptions. http://sysbioapps.dyndns.org/SED-ML_Web_Tools/ . fbergman@caltech.edu . © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  20. Strategy approach for eLearning 2.0 deployment in Universities

    Directory of Open Access Journals (Sweden)

    Oskar Casquero

    2010-12-01

    Full Text Available The institutionally powered Personal Learning Environment (iPLE constitutes our vision of how Web 2.0 technologies, people arrangement and data sharing could be applied for delivering open, flexible, distributed and learner-centred learning environments to university members. Based on the iPLE, this paper explores a strategy approach that universities could follow in order to deploy eLearning 2.0 tools and services. With that aim in mind, we review the patterns that Web 2.0 has successfully applied, and have been proved to encourage people to interact and to share information. Then, we present an eLearning 2.0 provisioning strategy based on iPLEs. Finally, we explain how this strategy can help translating Web 2.0 patterns to learning, and positioning universities as eLearning 2.0 providers.

  1. Quantitative forecasting of PTSD from early trauma responses: A Machine Learning application

    DEFF Research Database (Denmark)

    Galatzer-Levy, I. R.; Karstoft, K. I.; Statnikov, A.

    2014-01-01

    -traumatic stress disorder (PTSD) is plausible given the disorder's salient onset and the abundance of putative biological and clinical risk indicators. This work evaluates the ability of Machine Learning (ML) forecasting approaches to identify and integrate a panel of unique predictive characteristics...... algorithm identified a set of predictors that rendered all others redundant. Support Vector Machines (SVMs) as well as other ML classification algorithms were used to evaluate the forecasting accuracy of i) ML selected features, ii) all available features without selection, and iii) Acute Stress Disorder......). The feature selection algorithm identified 16 predictors, present in >= 95% cross-validation trials. The accuracy of predicting non-remitting PTSD from that set (AUC = .77) did not differ from predicting from all available information (AUC = .78). Predicting from ASD symptoms was not better then chance (AUC...

  2. QuakeML: Status of the XML-based Seismological Data Exchange Format

    Science.gov (United States)

    Euchner, Fabian; Schorlemmer, Danijel; Kästli, Philipp; Quakeml Working Group

    2010-05-01

    QuakeML is an XML-based data exchange standard for seismology that is in its fourth year of active community-driven development. The current release (version 1.2) is based on a public Request for Comments process that included contributions from ETH, GFZ, USC, SCEC, USGS, IRIS DMC, EMSC, ORFEUS, GNS, ZAMG, BRGM, Nanometrics, and ISTI. QuakeML has mainly been funded through the EC FP6 infrastructure project NERIES, in which it was endorsed as the preferred data exchange format. Currently, QuakeML services are being installed at several institutions around the globe, including EMSC, ORFEUS, ETH, Geoazur (Europe), NEIC, ANSS, SCEC/SCSN (USA), and GNS Science (New Zealand). Some of these institutions already provide QuakeML earthquake catalog web services. Several implementations of the QuakeML data model have been made. QuakePy, an open-source Python-based seismicity analysis toolkit using the QuakeML data model, is being developed at ETH. QuakePy is part of the software stack used in the Collaboratory for the Study of Earthquake Predictability (CSEP) testing center installations, developed by SCEC. Furthermore, the QuakeML data model is part of the SeisComP3 package from GFZ Potsdam. QuakeML is designed as an umbrella schema under which several sub-packages are collected. The present scope of QuakeML 1.2 covers a basic description of seismic events including picks, arrivals, amplitudes, magnitudes, origins, focal mechanisms, and moment tensors. Work on additional packages (macroseismic information, seismic inventory, and resource metadata) has been started, but is at an early stage. Contributions from the community that help to widen the thematic coverage of QuakeML are highly welcome. Online resources: http://www.quakeml.org, http://www.quakepy.org

  3. Blended learning approach improves teaching in a problem-based learning environment in orthopedics - a pilot study

    Science.gov (United States)

    2014-01-01

    Background While e-learning is enjoying increasing popularity as adjunct in modern teaching, studies on this topic should shift from mere evaluation of students’ satisfaction towards assessing its benefits on enhancement of knowledge and skills. This pilot study aimed to detect the teaching effects of a blended learning program on students of orthopedics and traumatology in the context of a problem-based learning environment. Methods The project NESTOR (network for students in traumatology and orthopedics) was offered to students in a problem-based learning course. Participants completed written tests before and directly after the course, followed by a final written test and an objective structured clinical examination (OSCE) as well as an evaluation questionnaire at the end of the semester. Results were compared within the group of NESTOR users and non-users and between these two groups. Results Participants (n = 53) rated their experiences very positively. An enhancement in knowledge was found directly after the course and at the final written test for both groups (p blended learning approach on knowledge enhancement and satisfaction of participating students. However, it will be an aim for the future to further explore the chances of this approach and internet-based technologies for possibilities to improve also practical examination skills. PMID:24690365

  4. Motivations, Learning, Approaches, and Strategies in Biochemistry Students at a Public University in Argentina

    Directory of Open Access Journals (Sweden)

    Silvia Raquel Salim

    2006-05-01

    Full Text Available The aim of the present paper is to understand how university students learn, and to comprehend the motivations and learning strategies they use when deciding in what field to major. We chose a combined research design: qualitative and quantitative. We applied the Questionnaire for the Evaluation of Learning and Studying Processes (CEPEA to Biochemistry students attending the National University of Tucumán (Argentina, and performed individual semi-structured interviews. Cluster analysis allowed us to identify three groups of students having who use different learning approaches: deep, superficial and ambivalent. We found that learning approaches are closely related with some teaching practices that encourage or inhibit them; among these are the types of learning evaluation.

  5. Edutourism Taka Bonerate National Park through Scientific Approach to Improve Student Learning Outcomes

    Science.gov (United States)

    Hayati, R. S.

    2017-02-01

    This research aim is develop the potential of Taka Bonerate National Park as learning resources through edutourism with scientific approach to improve student learning outcomes. Focus of student learning outcomes are students psychomotor abilities and comprehension on Biodiversity of Marine Biota, Corals Ecosystem, and Conservation topics. The edutourism development products are teacher manual, edutourism worksheet, material booklet, guide’s manual, and Taka Bonerate National Park governor manual. The method to develop edutourism products is ADDIE research and development model that consist of analysis, design, development and production, implementation, and evaluation step. The subjects in the implementation step were given a pretest and posttest and observation sheet to see the effect of edutourism Taka Bonerate National Park through scientific approach to student learning outcomes on Biodiversity of Marine Biota, Corals Ecosystem, and Conservation topics. The data were analyzed qualitative descriptively. The research result is edutourism Taka Bonerate National Park through scientific approach can improve students learning outcomes on Biodiversity of Marine Biota, Corals Ecosystem, and Conservation topics. Edutourism Taka Bonerate National Park can be an alternative of learning method on Biodiversity of Marine Biota, Corals Ecosystem, and Conservation topics.

  6. The Role of Social Identification as University Student in Learning: Relationships between Students' Social Identity, Approaches to Learning, and Academic Achievement

    Science.gov (United States)

    Bliuc, Ana-Maria; Ellis, Robert A.; Goodyear, Peter; Hendres, Daniela Muntele

    2011-01-01

    This article describes research exploring the relationship between students' self-perceptions in the context of university learning (i.e. student social identity), their approaches to learning, and academic achievement. The exploration of these inter-related aspects requires a mix of theoretical approaches, that is, in this research both social…

  7. A blended learning approach to teaching CVAD care and maintenance.

    Science.gov (United States)

    Hainey, Karen; Kelly, Linda J; Green, Audrey

    2017-01-26

    Nurses working within both acute and primary care settings are required to care for and maintain central venous access devices (CVADs). To support these nurses in practice, a higher education institution and local health board developed and delivered CVAD workshops, which were supported by a workbook and competency portfolio. Following positive evaluation of the workshops, an electronic learning (e-learning) package was also introduced to further support this clinical skill in practice. To ascertain whether this blended learning approach to teaching CVAD care and maintenance prepared nurses for practice, the learning package was evaluated through the use of electronic questionnaires. Results highlighted that the introduction of the e-learning package supported nurses' practice, and increased their confidence around correct clinical procedures.

  8. Impact of Cooperative Learning Approach on Senior Secondary ...

    African Journals Online (AJOL)

    This research work investigated the impact of cooperative learning approach on the performance of secondary school students in mathematics using some selected secondary schools. It employed one hundred and twenty students selected from the entire population of students offering mathematics at the senior secondary ...

  9. A Communicative Approach to College English Grammar Teaching and Learning

    Institute of Scientific and Technical Information of China (English)

    LI Yong-xian

    2016-01-01

    In response to the misconception that Communicative Language Teaching means no teaching of grammar, it is argued that grammar is as important as traffic rules for safe and smooth traffic on the road. To achieve appropriate and effective commu-nication, a communicative approach to college grammar teaching and learning is proposed. Both teachers and learners should change their attitudes toward and conceptions about grammar teaching and learning;additionally, teaching grammar in the com-pany of reading and writing helps learners learn and acquire grammar in meaningful contexts.

  10. Preparing for the future: opportunities for ML in ATLAS & CMS

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    ML is an established tool in HEP and there are many examples which demonstrate its importance for the kind of classification and regression problem we have in our field. However, there is also a big potential for future applications in yet untapped areas. I will summarise these opportunities and highlight recent, ongoing and planned studies of novel ML applications in HEP. Certain aspects of the problems we are faced with in HEP are quite unique and represent interesting benchmark problems for the ML community as a whole. Hence, efficient communication and close interaction between the ML and HEP community is expected to lead to promising cross-fertilisation. This talk attempts to serve as a starting point for such a prospective collaboration.

  11. Behavioral and functional neuroanatomical correlates of anterograde autobiographical memory in isolated retrograde amnesic patient M.L.

    Science.gov (United States)

    Levine, Brian; Svoboda, Eva; Turner, Gary R; Mandic, Marina; Mackey, Allison

    2009-09-01

    Patient M.L. [Levine, B., Black, S. E., Cabeza, R., Sinden, M., Mcintosh, A. R., Toth, J. P., et al. (1998). Episodic memory and the self in a case of isolated retrograde amnesia. Brain, 121, 1951-1973], lost memory for events occurring before his severe traumatic brain injury, yet his anterograde (post-injury) learning and memory appeared intact, a syndrome known as isolated or focal retrograde amnesia. Studies with M.L. demonstrated a dissociation between episodic and semantic memory. His retrograde amnesia was specific to episodic autobiographical memory. Convergent behavioral and functional imaging data suggested that his anterograde memory, while appearing normal, was accomplished with reduced autonoetic awareness (awareness of the self as a continuous entity across time that is a crucial element of episodic memory). While previous research on M.L. focused on anterograde memory of laboratory stimuli, in this study, M.L.'s autobiographical memory for post-injury events or anterograde autobiographical memory was examined using prospective collection of autobiographical events via audio diary with detailed behavioral and functional neuroanatomical analysis. Consistent with his reports of subjective disconnection from post-injury autobiographical events, M.L. assigned fewer "remember" ratings to his autobiographical events than comparison subjects. His generation of event-specific details using the Autobiographical Interview [Levine, B., Svoboda, E., Hay, J., Winocur, G., & Moscovitch, M. (2002). Aging and autobiographical memory: dissociating episodic from semantic retrieval. Psychology and Aging, 17, 677-689] was low, but not significantly so, suggesting that it is possible to generate episodic-like details even when re-experiencing of those details is compromised. While listening to the autobiographical audio diary segments, M.L. showed reduced activation relative to comparison subjects in midline frontal and posterior nodes previously identified as part of the

  12. A MuDDy Experience-ML Bindings to a BDD Library

    DEFF Research Database (Denmark)

    Larsen, Ken Friis

    2009-01-01

    . This combination of an ML interface to a high-performance C library is surprisingly fruitful. ML allows you to quickly experiment with high-level symbolic algorithms before handing over the grunt work to the C library. I show how, with a relatively little effort, you can make a domain specific language...... for concurrent finite state-machines embedded in Standard ML and then write various custom model-checking algorithms for this domain specific embedded language (DSEL)....

  13. ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings

    NARCIS (Netherlands)

    Drachsler, Hendrik; Pecceu, Dries; Arts, Tanja; Hutten, Edwin; Rutledge, Lloyd; Van Rosmalen, Peter; Hummel, Hans; Koper, Rob

    2009-01-01

    Drachsler, H., Peccau, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (2009). ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings. In F. Wild, M. Kalz, M. Palmér & D. Müller (Eds.),

  14. Microsoft Azure machine learning

    CERN Document Server

    Mund, Sumit

    2015-01-01

    The book is intended for those who want to learn how to use Azure Machine Learning. Perhaps you already know a bit about Machine Learning, but have never used ML Studio in Azure; or perhaps you are an absolute newbie. In either case, this book will get you up-and-running quickly.

  15. The relationship between students’ perceptions of portfolio assessment practice and their approaches to learning

    NARCIS (Netherlands)

    Segers, M.S.R.; Gijbels, D.; Thurlings, M.C.G.

    2008-01-01

    This study focuses on students’ learning approaches in the context of a competency-based program on Applied Sciences, with portfolio assessment as its core mode of assessment. The study examines students’ perceptions of these assessment practices and the relationships to their learning approaches.

  16. International Students' Motivation and Learning Approach: A Comparison with Local Students

    Science.gov (United States)

    Chue, Kah Loong; Nie, Youyan

    2016-01-01

    Psychological factors contribute to motivation and learning for international students as much as teaching strategies. 254 international students and 144 local students enrolled in a private education institute were surveyed regarding their perception of psychological needs support, their motivation and learning approach. The results from this…

  17. Approaches to e-learning

    DEFF Research Database (Denmark)

    Hartvig, Susanne Akrawi; Petersson, Eva

    2013-01-01

    E-learning has made its entrance into educational institutions. Compared to traditional learning methods, e-learning has the benefit of enabling educational institutions to attract more students. E-learning not only opens up for an increased enrollment, it also gives students who would otherwise...... not be able to take the education to now get the possibility to do so. This paper introduces Axel Honneth’s theory on the need for recognition as a framework to understand the role and function of interaction in relation to e-learning. The paper argues that an increased focus on the dialectic relationship...... between recognition and learning will enable an optimization of the learning conditions and the interactive affordances targeting students under e-learning programs. The paper concludes that the engagement and motivation to learn are not only influenced by but depending on recognition....

  18. The evolution of the CUAHSI Water Markup Language (WaterML)

    Science.gov (United States)

    Zaslavsky, I.; Valentine, D.; Maidment, D.; Tarboton, D. G.; Whiteaker, T.; Hooper, R.; Kirschtel, D.; Rodriguez, M.

    2009-04-01

    The CUAHSI Hydrologic Information System (HIS, his.cuahsi.org) uses web services as the core data exchange mechanism which provides programmatic connection between many heterogeneous sources of hydrologic data and a variety of online and desktop client applications. The service message schema follows the CUAHSI Water Markup Language (WaterML) 1.x specification (see OGC Discussion Paper 07-041r1). Data sources that can be queried via WaterML-compliant water data services include national and international repositories such as USGS NWIS (National Water Information System), USEPA STORET (Storage & Retrieval), USDA SNOTEL (Snowpack Telemetry), NCDC ISH and ISD(Integrated Surface Hourly and Daily Data), MODIS (Moderate Resolution Imaging Spectroradiometer), and DAYMET (Daily Surface Weather Data and Climatological Summaries). Besides government data sources, CUAHSI HIS provides access to a growing number of academic hydrologic observation networks. These networks are registered by researchers associated with 11 hydrologic observatory testbeds around the US, and other research, government and commercial groups wishing to join the emerging CUAHSI Water Data Federation. The Hydrologic Information Server (HIS Server) software stack deployed at NSF-supported hydrologic observatory sites and other universities around the country, supports a hydrologic data publication workflow which includes the following steps: (1) observational data are loaded from static files or streamed from sensors into a local instance of an Observations Data Model (ODM) database; (2) a generic web service template is configured for the new ODM instance to expose the data as a WaterML-compliant water data service, and (3) the new water data service is registered at the HISCentral registry (hiscentral.cuahsi.org), its metadata are harvested and semantically tagged using concepts from a hydrologic ontology. As a result, the new service is indexed in the CUAHSI central metadata catalog, and becomes

  19. Promoting learning transfer in post registration education: a collaborative approach.

    Science.gov (United States)

    Finn, Frances L; Fensom, Sue A; Chesser-Smyth, Patricia

    2010-01-01

    Pre-registration nurse education in Ireland became a four year undergraduate honors degree programme in 2002 (Government of Ireland, 2000. The Nursing Education Forum Report. Dublin, Dublin Stationary Office.). Consequently, the Irish Government invested significant resources in post registration nursing education in order to align certificate and diploma trained nurses with the qualification levels of new graduates. However, a general concern amongst academic and clinical staff in the South East of Ireland was that there was limited impact of this initiative on practice. These concerns were addressed through a collaborative approach to the development and implementation of a new part-time post registration degree that incorporated an enquiry and practice based learning philosophy. The principles of learning transfer (Ford, K., 1994. Defining transfer of learning the meaning is in the answers. Adult Learning 5 (4), p. 2214.) underpinned the curriculum development and implementation process with the goal of reducing the theory practice gap. This paper reports on all four stages of the curriculum development process: exploration, design, implementation and evaluation (Quinn, F.M., 2002. Principles and Practices of Nurse Education, fourth ed. Nelson Thornes, Cheltenham), and the subsequent impact of learning transfer on practice development. Eclectic approaches of quantitative and qualitative data collection techniques were utilised in the evaluation. The evaluation of this project to date supports our view that this practice based enquiry curriculum promotes the transfer of learning in the application of knowledge to practice, impacting both student and service development.

  20. Work Transitions as Told: A Narrative Approach to Biographical Learning

    Science.gov (United States)

    Hallqvist, Anders; Hyden, Lars-Christer

    2013-01-01

    In this article, we introduce a narrative approach to biographical learning; that is, an approach that considers autobiographical storytelling as a practice through which claims about life history are performed and negotiated. Using insights from narrative theory, we highlight evaluations in those narratives and suggest their crucial role in…

  1. Measuring University Students' Approaches to Learning Statistics: An Invariance Study

    Science.gov (United States)

    Chiesi, Francesca; Primi, Caterina; Bilgin, Ayse Aysin; Lopez, Maria Virginia; del Carmen Fabrizio, Maria; Gozlu, Sitki; Tuan, Nguyen Minh

    2016-01-01

    The aim of the current study was to provide evidence that an abbreviated version of the Approaches and Study Skills Inventory for Students (ASSIST) was invariant across different languages and educational contexts in measuring university students' learning approaches to statistics. Data were collected on samples of university students attending…

  2. Towards Optimality in Online Learning – The OLeCenT Approach

    Directory of Open Access Journals (Sweden)

    Carl Beckford

    2017-06-01

    Full Text Available Higher Education Institutions (HEIs employ Learning Management Systems (LMSs primarily for greater efficiency, profitability, technological advancement or survival. The predominantly used LMSs, Moodle and Blackboard account for in excess of 60% usage by the top HEIs. However, the individual international regions do not necessarily bear the percentages of the overall total. Gaps are identified in optimality in course delivery within online learning when one studies LMSs and their functionalities. Advanced Distributed Learning (ADL Initiative which was established to standardize and modernize training and education management and delivery, developed and recommended usage of Sharable Content Object Reference Model (SCORM 2004 and later versions. SCORM 2004 which provides for flexibility in sequencing and navigation for learner-centric course delivery is not supported in any version of the more prevalently used LMSs. It is believed that most people have a preferred way in processing information. We propose codifying one or more Learning Style Instruments (LSIs, diagnosing the preferred teaching approach(es and dominant/existing learning styles within a batch of learners, then providing course delivery as a best-fit per learner. As a proof of concept, OLeCenT allows the input of one or more course learning paths with real-time learning and automatic reconfiguration of the course path where a new trend or pattern is identified. OLeCenT identified disparity in teaching-learning and provided a mechanism towards improving online learner-centric course delivery. OLeCenT also identified comparative levels of similarities among learners and instructors even where they are deemed to be of different teaching-learning styles/mechanisms.

  3. Path to Stochastic Stability: Comparative Analysis of Stochastic Learning Dynamics in Games

    KAUST Repository

    Jaleel, Hassan; Shamma, Jeff S.

    2018-01-01

    dynamics: Log-Linear Learning (LLL) and Metropolis Learning (ML). Although both of these dynamics have the same stochastically stable states, LLL and ML correspond to different behavioral models for decision making. Moreover, we demonstrate through

  4. Machine learning for medical ultrasound: status, methods, and future opportunities.

    Science.gov (United States)

    Brattain, Laura J; Telfer, Brian A; Dhyani, Manish; Grajo, Joseph R; Samir, Anthony E

    2018-04-01

    Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and capable of real-time image acquisition and display. US is a rapidly evolving technology with significant challenges and opportunities. Challenges include high inter- and intra-operator variability and limited image quality control. Tremendous opportunities have arisen in the last decade as a result of exponential growth in available computational power coupled with progressive miniaturization of US devices. As US devices become smaller, enhanced computational capability can contribute significantly to decreasing variability through advanced image processing. In this paper, we review leading machine learning (ML) approaches and research directions in US, with an emphasis on recent ML advances. We also present our outlook on future opportunities for ML techniques to further improve clinical workflow and US-based disease diagnosis and characterization.

  5. PHENOMENOLOGICAL APPROACHES TO STUDY LEARNING IN THE TERTIARY LEVEL CHEMISTRY LABORATORY

    Directory of Open Access Journals (Sweden)

    Santiago Sandi-Urena

    Full Text Available Despite the widespread notion amongst chemistry educators that the laboratory is essential to learn chemistry, it is often a neglected area of teaching and, arguably, of educational research. Research has typically focused on secondary education, single institutions, and isolated interventions that are mostly assessed quantitatively. It has also honed in on compartmentalised features instead of searching understanding of broader aspects of learning through experimentation. This paper contends there is a gap in subject specific, tertiary level research that is comprehensive and learning-centred instead of fragmented and instruction-based. A shift in focus requires consideration of methodological approaches that can effectively tackle the challenges of researching complex learning environments. This paper reckons qualitative approaches, specifically phenomenology, are better suited for this purpose. To illustrate this potential, it summarises an exemplar phenomenological study that investigated students’ experience of change in instructional style from an expository (traditional laboratory program to one that was cooperative and project-based (reformed. The study suggests the experience was characterised by a transition from a learning environment that promoted mindless behaviour to one in which students were mindfully engaged in their learning. Thus, this work puts forth the use of Mindfulness Theory to investigate and support design of laboratory experiences.

  6. An Interactive Approach to Learning and Teaching in Visual Arts Education

    Directory of Open Access Journals (Sweden)

    Zlata Tomljenović

    2015-09-01

    Full Text Available The present research focuses on modernising the approach to learning and teaching the visual arts in teaching practice, as well as examining the performance of an interactive approach to learning and teaching in visual arts classes with the use of a combination of general and specific (visual arts teaching methods. The study uses quantitative analysis of data on the basis of results obtained from a pedagogical experiment. The subjects of the research were 285 second- and fourth-grade students from four primary schools in the city of Rijeka, Croatia. Paintings made by the students in the initial and final stage of the pedagogical experiment were evaluated. The research results confirmed the hypotheses about the positive effect of interactive approaches to learning and teaching on the following variables: (1 knowledge and understanding of visual arts terms, (2 abilities and skills in the use of art materials and techniques within the framework of planned painting tasks, and (3 creativity in solving visual arts problems. The research results can help shape an optimised model for the planning and performance of visual arts education, and provide guidelines for planning professional development and the further professional education of teachers, with the aim of establishing more efficient learning and teaching of the visual arts in primary school.

  7. Problematic Smartphone Use, Deep and Surface Approaches to Learning, and Social Media Use in Lectures

    Directory of Open Access Journals (Sweden)

    Dmitri Rozgonjuk

    2018-01-01

    Full Text Available Several studies have shown that problematic smartphone use (PSU is related to detrimental outcomes, such as worse psychological well-being, higher cognitive distraction, and poorer academic outcomes. In addition, many studies have shown that PSU is strongly related to social media use. Despite this, the relationships between PSU, as well as the frequency of social media use in lectures, and different approaches to learning have not been previously studied. In our study, we hypothesized that both PSU and the frequency of social media use in lectures are negatively correlated with a deep approach to learning (defined as learning for understanding and positively correlated with a surface approach to learning (defined as superficial learning. The study participants were 415 Estonian university students aged 19–46 years (78.8% females; age M = 23.37, SD = 4.19; the effective sample comprised 405 participants aged 19–46 years (79.0% females; age M = 23.33, SD = 4.21. In addition to basic socio-demographics, participants were asked about the frequency of their social media use in lectures, and they filled out the Estonian Smartphone Addiction Proneness Scale and the Estonian Revised Study Process Questionnaire. Bivariate correlation analysis showed that PSU and the frequency of social media use in lectures were negatively correlated with a deep approach to learning and positively correlated with a surface approach to learning. Mediation analysis showed that social media use in lectures completely mediates the relationship between PSU and approaches to learning. These results indicate that the frequency of social media use in lectures might explain the relationships between poorer academic outcomes and PSU.

  8. Problematic Smartphone Use, Deep and Surface Approaches to Learning, and Social Media Use in Lectures.

    Science.gov (United States)

    Rozgonjuk, Dmitri; Saal, Kristiina; Täht, Karin

    2018-01-08

    Several studies have shown that problematic smartphone use (PSU) is related to detrimental outcomes, such as worse psychological well-being, higher cognitive distraction, and poorer academic outcomes. In addition, many studies have shown that PSU is strongly related to social media use. Despite this, the relationships between PSU, as well as the frequency of social media use in lectures, and different approaches to learning have not been previously studied. In our study, we hypothesized that both PSU and the frequency of social media use in lectures are negatively correlated with a deep approach to learning (defined as learning for understanding) and positively correlated with a surface approach to learning (defined as superficial learning). The study participants were 415 Estonian university students aged 19-46 years (78.8% females; age M = 23.37, SD = 4.19); the effective sample comprised 405 participants aged 19-46 years (79.0% females; age M = 23.33, SD = 4.21). In addition to basic socio-demographics, participants were asked about the frequency of their social media use in lectures, and they filled out the Estonian Smartphone Addiction Proneness Scale and the Estonian Revised Study Process Questionnaire. Bivariate correlation analysis showed that PSU and the frequency of social media use in lectures were negatively correlated with a deep approach to learning and positively correlated with a surface approach to learning. Mediation analysis showed that social media use in lectures completely mediates the relationship between PSU and approaches to learning. These results indicate that the frequency of social media use in lectures might explain the relationships between poorer academic outcomes and PSU.

  9. An Outcome Evaluation of a Problem-Based Learning Approach with MSW Students

    Science.gov (United States)

    Westhues, Anne; Barsen, Chia; Freymond, Nancy; Train, Patricia

    2014-01-01

    In this article, we report the findings from a study exploring the effects of a problem-based learning (PBL) approach to teaching and learning on learning outcomes for master's of social work (MSW) students. Students who participated in a PBL pilot project were compared with students who did not participate in 5 outcome areas: social work…

  10. High School Students' Approaches to Learning Physics with Relationship to Epistemic Views on Physics and Conceptions of Learning Physics

    Science.gov (United States)

    Chiou, Guo-Li; Lee, Min-Hsien; Tsai, Chin-Chung

    2013-01-01

    Background and purpose: Knowing how students learn physics is a central goal of physics education. The major purpose of this study is to examine the strength of the predictive power of students' epistemic views and conceptions of learning in terms of their approaches to learning in physics. Sample, design and method: A total of 279 Taiwanese high…

  11. A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

    Science.gov (United States)

    Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

    2016-01-01

    Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

  12. THE USE OF NUMBERED HEADS TOGETHER (NHT LEARNING MODEL WITH SCIENCE, ENVIRONMENT, TECHNOLOGY, SOCIETY (SETS APPROACH TO IMPROVE STUDENT LEARNING MOTIVATION OF SENIOR HIGH SCHOOL

    Directory of Open Access Journals (Sweden)

    B. Sutipnyo

    2018-01-01

    Full Text Available This research was aimed to determine the increasing of students' motivation that has been applied by Numbered Heads Together (NHT learning model with Science, Environment, Technology, Society (SETS approach. The design of this study was quasi experiment with One Group Pretest-Posttest Design. The data of students’ learning motivation obtained through questionnaire administered before and after NHT learning model with SETS approach. In this research, the indicators of learning-motivation were facing tasks diligently, showing interest in variety of problems, prefering to work independently, keeping students’ opinions, and feeling happy to find and solve problems. Increasing of the students’ learning motivation was analyzed by using a gain test. The results showed that applying NHT learning model with SETS approach could increase the students’ learning motivation in medium categories.

  13. Towards a team-based, collaborative approach to embedding e-learning within undergraduate nursing programmes.

    Science.gov (United States)

    Kiteley, Robin J; Ormrod, Graham

    2009-08-01

    E-learning approaches are incorporated in many undergraduate nursing programmes but there is evidence to suggest that these are often piecemeal and have little impact on the wider, nurse education curriculum. This is consistent with a broader view of e-learning within the higher education (HE) sector, which suggests that higher education institutions (HEIs) are struggling to make e-learning a part of their mainstream delivery [HEFCE, 2005. HEFCE Strategy for E-Learning 2005/12. Bristol, UK, Higher Education Funding Council for England (HEFCE). [online] Available at: Accessed: 30 May 07]. This article discusses some of the challenges that face contemporary nurse education and seeks to account for reasons as to why e-learning may not be fully embedded within the undergraduate curriculum. These issues are considered within a wider debate about the need to align e-learning approaches with a shift towards a more student focused learning and teaching paradigm. The article goes on to consider broader issues in the literature on the adoption, embedding and diffusion of innovations, particularly in relation to the value of collaboration. A collaborative, team-based approach to e-learning development is considered as a way of facilitating sustainable, responsive and multidisciplinary developments within a field which is constantly changing and evolving.

  14. A Blended Learning Approach to Teaching Project Management: A Model for Active Participation and Involvement: Insights from Norway

    Directory of Open Access Journals (Sweden)

    Bassam A. Hussein

    2015-04-01

    Full Text Available The paper demonstrates and evaluates the effectiveness of a blended learning approach to create a meaningful learning environment. We use the term blended learning approach in this paper to refer to the use of multiple or hybrid instructional methods that emphasize the role of learners as contributors to the learning process rather than recipients of learning. Contribution to learning is attained by using in class gaming as pathways that ensure active involvement of learners. Using a blended learning approach is important in order to be able to address different learning styles of the target group. The approach was also important in order to be able to demonstrate different types of challenges, issues and competences needed in project management. Student evaluations of the course confirmed that the use of multiple learning methods and, in particular, in class gaming was beneficial and contributed to a meaningful learning experience.

  15. The Formation of Conservation-Based Behaviour of Mechanical Engineering Students through Contextual Learning Approach

    Science.gov (United States)

    Sudarman; Djuniadi; Sutopo, Yeri

    2017-01-01

    This study was aimed to figure out: (1) the implementation of contextual learning approaches; (2) the learning outcome of conservation education using contextual approach on the internship program preparation class; (3) the conservation-based behaviour of the internship program participants; (4) the contribution of conservation education results…

  16. Workforce Optimization for Bank Operation Centers: A Machine Learning Approach

    Directory of Open Access Journals (Sweden)

    Sefik Ilkin Serengil

    2017-12-01

    Full Text Available Online Banking Systems evolved and improved in recent years with the use of mobile and online technologies, performing money transfer transactions on these channels can be done without delay and human interaction, however commercial customers still tend to transfer money on bank branches due to several concerns. Bank Operation Centers serve to reduce the operational workload of branches. Centralized management also offers personalized service by appointed expert employees in these centers. Inherently, workload volume of money transfer transactions changes dramatically in hours. Therefore, work-force should be planned instantly or early to save labor force and increase operational efficiency. This paper introduces a hybrid multi stage approach for workforce planning in bank operation centers by the application of supervised and unsu-pervised learning algorithms. Expected workload would be predicted as supervised learning whereas employees are clus-tered into different skill groups as unsupervised learning to match transactions and proper employees. Finally, workforce optimization is analyzed for proposed approach on production data.

  17. Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

    Science.gov (United States)

    Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

    2017-01-01

    Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  18. Case-based approaches for knowledge application and organisational learning

    DEFF Research Database (Denmark)

    Wang, Chengbo; Johansen, John; Luxhøj, James T.

    2005-01-01

    In dealing with the strategic issues within a manufacturing system, it is necessary to facilitate formulating the composing elements of a set of strategic manufacturing practices and activity patterns that will support an enterprise to reinforce and increase its competitive advantage....... These practices and activity patterns are based on learning and applying the knowledge internal and external to an organisation. To ensure their smooth formulation process, there are two important techniques designed – an expert adaptation approach and an expert evaluation approach. These two approaches provide...

  19. Approaches to Learning to Control Dynamic Uncertainty

    Directory of Open Access Journals (Sweden)

    Magda Osman

    2015-10-01

    Full Text Available In dynamic environments, when faced with a choice of which learning strategy to adopt, do people choose to mostly explore (maximizing their long term gains or exploit (maximizing their short term gains? More to the point, how does this choice of learning strategy influence one’s later ability to control the environment? In the present study, we explore whether people’s self-reported learning strategies and levels of arousal (i.e., surprise, stress correspond to performance measures of controlling a Highly Uncertain or Moderately Uncertain dynamic environment. Generally, self-reports suggest a preference for exploring the environment to begin with. After which, those in the Highly Uncertain environment generally indicated they exploited more than those in the Moderately Uncertain environment; this difference did not impact on performance on later tests of people’s ability to control the dynamic environment. Levels of arousal were also differentially associated with the uncertainty of the environment. Going beyond behavioral data, our model of dynamic decision-making revealed that, in actual fact, there was no difference in exploitation levels between those in the highly uncertain or moderately uncertain environments, but there were differences based on sensitivity to negative reinforcement. We consider the implications of our findings with respect to learning and strategic approaches to controlling dynamic uncertainty.

  20. Incorporating Wiki Technology in a Traditional Biostatistics Course: Effects on University Students’ Collaborative Learning, Approaches to Learning and Course Performance

    Directory of Open Access Journals (Sweden)

    Shirley S.M. Fong

    2017-08-01

    Full Text Available Aim/Purpose: To investigate the effectiveness of incorporating wiki technology in an under-graduate biostatistics course for improving university students’ collaborative learning, approaches to learning, and course performance. Methodology: During a three year longitudinal study, twenty-one and twenty-four undergraduate students were recruited by convenience sampling and assigned to a wiki group (2014-2015 and a control group (2013-2014 and 2015-2016, respectively. The students in the wiki group attended face-to-face lectures and used a wiki (PBworks weekly for online- group discussion, and the students in the control group had no access to the wiki and interacted face-to-face only. The students’ collaborative learning, approaches to learning, and course performance were evaluated using the Group Process Questionnaire (GPQ, Revised Study Process Questionnaire (R-SPQ-2F and course results, respectively, after testing. Findings: Multivariate analysis of variance results revealed that the R-SPQ-2F surface approach score, surface motive and strategy subscores were lower in the wiki group than in the control group (p < 0.05. The GPQ individual accountability and equal opportunity scores (components of collaboration were higher in the wiki group than in the control group (p < 0.001. No significant between-groups differences were found in any of the other outcome variables (i.e., overall course result, R-SPQ-2F deep approach score and subscores, GPQ positive interdependence score, social skills score, and composite score. Looking at the Wiki Questionnaire results, the subscale and composite scores we obtained were 31.5% to 37.7% lower than the norm. The wiki was used at a frequency of about 0.7 times per week per student. Recommendations for Practitioners: Using wiki technology in conjunction with the traditional face-to-face teaching method in a biostatistics course can enhance some aspects of undergraduate students’ collaborative learning

  1. A Critical Comparison of Transformation and Deep Approach Theories of Learning

    Science.gov (United States)

    Howie, Peter; Bagnall, Richard

    2015-01-01

    This paper reports a critical comparative analysis of two popular and significant theories of adult learning: the transformation and the deep approach theories of learning. These theories are operative in different educational sectors, are significant, respectively, in each, and they may be seen as both touching on similar concerns with learning…

  2. A FIRST LOOK AT CREATING MOCK CATALOGS WITH MACHINE LEARNING TECHNIQUES

    International Nuclear Information System (INIS)

    Xu Xiaoying; Ho, Shirley; Trac, Hy; Schneider, Jeff; Ntampaka, Michelle; Poczos, Barnabas

    2013-01-01

    We investigate machine learning (ML) techniques for predicting the number of galaxies (N gal ) that occupy a halo, given the halo's properties. These types of mappings are crucial for constructing the mock galaxy catalogs necessary for analyses of large-scale structure. The ML techniques proposed here distinguish themselves from traditional halo occupation distribution (HOD) modeling as they do not assume a prescribed relationship between halo properties and N gal . In addition, our ML approaches are only dependent on parent halo properties (like HOD methods), which are advantageous over subhalo-based approaches as identifying subhalos correctly is difficult. We test two algorithms: support vector machines (SVM) and k-nearest-neighbor (kNN) regression. We take galaxies and halos from the Millennium simulation and predict N gal by training our algorithms on the following six halo properties: number of particles, M 200 , σ v , v max , half-mass radius, and spin. For Millennium, our predicted N gal values have a mean-squared error (MSE) of ∼0.16 for both SVM and kNN. Our predictions match the overall distribution of halos reasonably well and the galaxy correlation function at large scales to ∼5%-10%. In addition, we demonstrate a feature selection algorithm to isolate the halo parameters that are most predictive, a useful technique for understanding the mapping between halo properties and N gal . Lastly, we investigate these ML-based approaches in making mock catalogs for different galaxy subpopulations (e.g., blue, red, high M star , low M star ). Given its non-parametric nature as well as its powerful predictive and feature selection capabilities, ML offers an interesting alternative for creating mock catalogs

  3. CytometryML: a markup language for analytical cytology

    Science.gov (United States)

    Leif, Robert C.; Leif, Stephanie H.; Leif, Suzanne B.

    2003-06-01

    Cytometry Markup Language, CytometryML, is a proposed new analytical cytology data standard. CytometryML is a set of XML schemas for encoding both flow cytometry and digital microscopy text based data types. CytometryML schemas reference both DICOM (Digital Imaging and Communications in Medicine) codes and FCS keywords. These schemas provide representations for the keywords in FCS 3.0 and will soon include DICOM microscopic image data. Flow Cytometry Standard (FCS) list-mode has been mapped to the DICOM Waveform Information Object. A preliminary version of a list mode binary data type, which does not presently exist in DICOM, has been designed. This binary type is required to enhance the storage and transmission of flow cytometry and digital microscopy data. Index files based on Waveform indices will be used to rapidly locate the cells present in individual subsets. DICOM has the advantage of employing standard file types, TIF and JPEG, for Digital Microscopy. Using an XML schema based representation means that standard commercial software packages such as Excel and MathCad can be used to analyze, display, and store analytical cytometry data. Furthermore, by providing one standard for both DICOM data and analytical cytology data, it eliminates the need to create and maintain special purpose interfaces for analytical cytology data thereby integrating the data into the larger DICOM and other clinical communities. A draft version of CytometryML is available at www.newportinstruments.com.

  4. A new model in teaching undergraduate research: A collaborative approach and learning cooperatives.

    Science.gov (United States)

    O'Neal, Pamela V; McClellan, Lynx Carlton; Jarosinski, Judith M

    2016-05-01

    Forming new, innovative collaborative approaches and cooperative learning methods between universities and hospitals maximize learning for undergraduate nursing students in a research course and provide professional development for nurses on the unit. The purpose of this Collaborative Approach and Learning Cooperatives (CALC) Model is to foster working relations between faculty and hospital administrators, maximize small group learning of undergraduate nursing students, and promote onsite knowledge of evidence based care for unit nurses. A quality improvement study using the CALC Model was implemented in an undergraduate nursing research course at a southern university. Hospital administrators provided a list of clinical concerns based on national performance outcome measures. Undergraduate junior nursing student teams chose a clinical question, gathered evidence from the literature, synthesized results, demonstrated practice application, and developed practice recommendations. The student teams developed posters, which were evaluated by hospital administrators. The administrators selected several posters to display on hospital units for continuing education opportunity. This CALC Model is a systematic, calculated approach and an economically feasible plan to maximize personnel and financial resources to optimize collaboration and cooperative learning. Universities and hospital administrators, nurses, and students benefit from working together and learning from each other. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. VarioML framework for comprehensive variation data representation and exchange.

    Science.gov (United States)

    Byrne, Myles; Fokkema, Ivo Fac; Lancaster, Owen; Adamusiak, Tomasz; Ahonen-Bishopp, Anni; Atlan, David; Béroud, Christophe; Cornell, Michael; Dalgleish, Raymond; Devereau, Andrew; Patrinos, George P; Swertz, Morris A; Taschner, Peter Em; Thorisson, Gudmundur A; Vihinen, Mauno; Brookes, Anthony J; Muilu, Juha

    2012-10-03

    Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement. The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components. VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.

  6. Analysis student self efficacy in terms of using Discovery Learning model with SAVI approach

    Science.gov (United States)

    Sahara, Rifki; Mardiyana, S., Dewi Retno Sari

    2017-12-01

    Often students are unable to prove their academic achievement optimally according to their abilities. One reason is that they often feel unsure that they are capable of completing the tasks assigned to them. For students, such beliefs are necessary. The term belief has called self efficacy. Self efficacy is not something that has brought about by birth or something with permanent quality of an individual, but is the result of cognitive processes, the meaning one's self efficacy will be stimulated through learning activities. Self efficacy has developed and enhanced by a learning model that can stimulate students to foster confidence in their capabilities. One of them is by using Discovery Learning model with SAVI approach. Discovery Learning model with SAVI approach is one of learning models that involves the active participation of students in exploring and discovering their own knowledge and using it in problem solving by utilizing all the sensory devices they have. This naturalistic qualitative research aims to analyze student self efficacy in terms of use the Discovery Learning model with SAVI approach. The subjects of this study are 30 students focused on eight students who have high, medium, and low self efficacy obtained through purposive sampling technique. The data analysis of this research used three stages, that were reducing, displaying, and getting conclusion of the data. Based on the results of data analysis, it was concluded that the self efficacy appeared dominantly on the learning by using Discovery Learning model with SAVI approach is magnitude dimension.

  7. Reactive Programming in Standard ML

    OpenAIRE

    Pucella, Riccardo

    2004-01-01

    Reactive systems are systems that maintain an ongoing interaction with their environment, activated by receiving input events from the environment and producing output events in response. Modern programming languages designed to program such systems use a paradigm based on the notions of instants and activations. We describe a library for Standard ML that provides basic primitives for programming reactive systems. The library is a low-level system upon which more sophisticated reactive behavi...

  8. A strategic approach to developing e-learning capability for healthcare.

    Science.gov (United States)

    Clarke, Angie; Lewis, Dina; Cole, Ian; Ringrose, Liz

    2005-12-01

    This article examines a strategic approach to developing e-learning capability to enhance learning opportunities for the workforce of a healthcare organization. Emphasis is given to the procurement of a bespoke Managed Learning Environment (MLE). Strategic organizational issues impacting on future e-learning developments are considered. The 2-year implementation plan was evaluated through a two phase external research project. The first phase focused on the effectiveness of a training programme designed to build capacity for e-learning within the Northern area and also included a virtual learning environment usability study which informed the MLE specification. The second phase evaluation is ongoing during 2005 and interim findings are presented. The MLE has been piloted and on-line learning packages have been acquired. There has been a phased take-up of e-learning opportunities and e-tutor training. Some virtual Communities of Practice have been established. Key organizational issues have been identified and ongoing findings are informing strategic planning. The healthcare MLE is offering enhanced learning opportunities and assisting area healthcare providers in training their dispersed workforces. Blended learning strategies are most successful. The need for protected time for e-learning is a key issue, financial savings are available. Progress has been slowed by identified organizational constraints-the MLE's benefits are widely recognized.

  9. The Effects of Learning Activities Corresponding with Students’ Learning Styles on Academic Success and Attitude within the Scope of Constructivist Learning Approach: The Case of the Concepts of Function and Derivative

    Directory of Open Access Journals (Sweden)

    Kemal Özgen

    2014-04-01

    Full Text Available The aim of this study was to identify the effects of learning activities according to students’ learning styles on students’ academic success and attitude towards mathematics within a scope of constructivist learning approach. The study had a semi-experimental research design based on the pre test-post test model with a control group. The participants of the study were students studying at a state high school in the 2010-2011 academic year. As part of the study, activities which were suitable to the students’ learning styles were developed within the scope of constructivist learning approach in line with McCarthy’s 4MAT system with 8 steps of learning and used for the learning of the concepts of function and derivative. Data were collected using data collection tools such as a personal information form, non-routine problems, and a mathematics attitude scale. Descriptive and non-parametric statistics were used for the analysis of quantitative data. Data analysis indicated that, the learning process in which activities appropriate for students’ learning styles were used to contribute to an increase in the students’ academic success and problem solving skills. Yet, there was no statistically significant difference in students’ attitudes towards mathematics.Key Words:    Constructivist learning approach, learning style, learning activity, success, attitude

  10. Approaches to Learning Information Literacy: A Phenomenographic Study

    Science.gov (United States)

    Diehm, Rae-Anne; Lupton, Mandy

    2012-01-01

    This paper reports on an empirical study that explores the ways students approach learning to find and use information. Based on interviews with 15 education students in an Australian university, this study uses phenomenography as its methodological and theoretical basis. The study reveals that students use three main strategies for learning…

  11. Co-operative Learning Approach and Students' Achievement in ...

    African Journals Online (AJOL)

    This study set out to investigate cooperative learning approach and students' achievement in Sociology. One research question and one hypothesis tested at 0.05 level of significance were formulated to guide the study. The study adopted a quasi-experimental design. One hundred and one (101) students of the schools of ...

  12. Introducing a technology-enabled problem-based learning approach into a health informatics curriculum.

    Science.gov (United States)

    Green, Carolyn J; van Gyn, Geraldine H; Moehr, Jochen R; Lau, Francis Y; Coward, Patricia M

    2004-03-18

    To investigate the effect on learner satisfaction of introducing a technology-enabled problem-based learning (PBL) approach into a health informatics curriculum. Course redesign was undertaken to prepare students for three 4-month work terms and a rapidly changing professional environment upon graduation. Twenty-six Canadian undergraduate students of a redesigned course in biomedical fundamentals completed a midterm questionnaire in 2002. Eight of these students participated in a focus group. Students agreed that seven of nine functions provided by the web-based online course management system enhanced their learning: private email (92.3%), calendaring (88.5%), course notes (88.5%), discussion forums (84.5%), online grades (84.5%) assignment descriptions (80.8%) and online quizzes (80.8%). Although students agreed that two PBL activities enhanced learning (learning to present information) (84.5%) and learning to identify information needed (73.1%), the majority of students (69.2%) expressed a preference for the traditional lecture approach over the PBL approach. Students reported feeling uncertain of what was required of them and related anxiety accounted for most of the negative feedback. These findings give us clear goals for improvement in the course beginning with a comprehensive, carefully guided introduction to the processes of PBL. The positive trends are encouraging for the use of web-enabled courseware and for the further development of the PBL approach.

  13. Scientific Approach and Inquiry Learning Model in the Topic of Buffer Solution: A Content Analysis

    Science.gov (United States)

    Kusumaningrum, I. A.; Ashadi, A.; Indriyanti, N. Y.

    2017-09-01

    Many concepts in buffer solution cause student’s misconception. Understanding science concepts should apply the scientific approach. One of learning models which is suitable with this approach is inquiry. Content analysis was used to determine textbook compatibility with scientific approach and inquiry learning model in the concept of buffer solution. By using scientific indicator tools (SIT) and Inquiry indicator tools (IIT), we analyzed three chemistry textbooks grade 11 of senior high school labeled as P, Q, and R. We described how textbook compatibility with scientific approach and inquiry learning model in the concept of buffer solution. The results show that textbook P and Q were very poor and book R was sufficient because the textbook still in procedural level. Chemistry textbooks used at school are needed to be improved in term of scientific approach and inquiry learning model. The result of these analyses might be of interest in order to write future potential textbooks.

  14. A Practice-Based Approach to Student Reflection in the Workplace during a Work-Integrated Learning Placement

    Science.gov (United States)

    Sykes, Christopher; Dean, Bonnie Amelia

    2013-01-01

    In the Work-Integrated Learning (WIL) curriculum, reflection on workplace activities is widely used to support student learning. Recent critiques have demonstrated the limitations of current approaches to support students' reflective learning of workplace practices. By employing a practice-based approach, we seek to refocus WIL reflection on…

  15. The systemic approach to teaching and learning chemistry [SATLC ...

    African Journals Online (AJOL)

    The systemic approach to teaching and learning chemistry [SATLC]: a 20-years review. ... in activities such as tourism, commerce, economy, security, education etc.., ... that we live in and survive with its positive and negative impacts on our life.

  16. Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach

    NARCIS (Netherlands)

    Miao, Yongwu; Sloep, Peter; Koper, Rob

    2009-01-01

    Miao, Y., Sloep, P. B., & Koper, R. (2009). Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach. Presented at the 'Open workshop of TENCompetence - Rethinking Learning and Employment at a Time of Economic Uncertainty-event'. November, 19, 2009,

  17. Impact of a Differential Learning Approach on Practical Exam Performance: A Controlled Study in a Preclinical Dental Course.

    Science.gov (United States)

    Pabel, Sven-Olav; Pabel, Anne-Kathrin; Schmickler, Jan; Schulz, Xenia; Wiegand, Annette

    2017-09-01

    The aim of this study was to evaluate if differential learning in a preclinical dental course impacted the performance of dental students in a practical exam (preparation of a gold partial crown) immediately after the training session and 20 weeks later compared to conventional learning. This controlled study was performed in a preclinical course in operative dentistry at a dental school in Germany. Third-year students were trained in preparing gold partial crowns by using either the conventional learning (n=41) or the differential learning approach (n=32). The differential learning approach consisted of 20 movement exercises with a continuous change of movement execution during the learning session, while the conventional learning approach was mainly based on repetition, a methodological series of exercises, and correction of preparations during the training phase. Practical exams were performed immediately after the training session (T1) and 20 weeks later (T2, retention test). Preparations were rated by four independent and blinded examiners. At T1, no significant difference between the performance (exam passed) of the two groups was detected (conventional learning: 54.3%, differential learning: 68.0%). At T2, significantly more students passed the exam when trained by the differential learning approach (68.8%) than by the conventional learning approach (18.9%). Interrater reliability was moderate (Kappa: 0.57, T1) or substantial (Kappa: 0.67, T2), respectively. These results suggest that a differential learning approach can increase the manual skills of dental students.

  18. Differences in Perceived Approaches to Learning and Teaching English in Hong Kong Secondary Schools

    Science.gov (United States)

    Mak, Barley; Chik, Pakey

    2011-01-01

    This paper investigates differences in approaches to learning and teaching English as a second language (ESL) as reported by 324 mixed-ability Grade 7 Hong Kong ESL students and 37 ESL secondary school teachers with different backgrounds. Information about participants' perceived approaches to learning/teaching English were collected through a…

  19. Assembling Components using SysML with Non-Functional Requirements

    OpenAIRE

    Chouali , Samir; Hammad , Ahmed; Mountassir , Hassan

    2013-01-01

    International audience; Non-functional requirements of component based systems are important as their functional requirements, therefore they must be considered in components assembly. These properties are beforehand specified with SysML requirement diagram. We specify component based system architecture with SysML block definition diagram, and component behaviors with sequence diagrams. We propose to specify formally component interfaces with interface automata, obtained from requirement and...

  20. School health approach to teaching and learning of students

    Directory of Open Access Journals (Sweden)

    Yu.S. Lukianova

    2015-01-01

    Full Text Available Purpose: disclosure of health-ways for teaching and learning of students. Material: analysis of the publications of domestic and foreign authors. Results: The article is devoted to the implementation of healthy way approach to the educational process, namely, the rational organization of training aimed at keeping the dynamics of human health, the prevention of mental fatigue and overload, increase adaptive reserves of the body of the person; intensification of teaching and learning of students (application-is controversial dialogue, training, game forms and methods of training, participation in project activities, the work of pedagogical workshops that stimulates emotional accommodation and understanding of knowledge, helps students acquire personal-relevant knowledge and experience; use of health effect of artistic and practical (music, painting activities of students. Conclusions: highlights the key towards the implementation of health-promoting approach to the educational process.

  1. Detection of eardrum abnormalities using ensemble deep learning approaches

    Science.gov (United States)

    Senaras, Caglar; Moberly, Aaron C.; Teknos, Theodoros; Essig, Garth; Elmaraghy, Charles; Taj-Schaal, Nazhat; Yua, Lianbo; Gurcan, Metin N.

    2018-02-01

    In this study, we proposed an approach to report the condition of the eardrum as "normal" or "abnormal" by ensembling two different deep learning architectures. In the first network (Network 1), we applied transfer learning to the Inception V3 network by using 409 labeled samples. As a second network (Network 2), we designed a convolutional neural network to take advantage of auto-encoders by using additional 673 unlabeled eardrum samples. The individual classification accuracies of the Network 1 and Network 2 were calculated as 84.4%(+/- 12.1%) and 82.6% (+/- 11.3%), respectively. Only 32% of the errors of the two networks were the same, making it possible to combine two approaches to achieve better classification accuracy. The proposed ensemble method allows us to achieve robust classification because it has high accuracy (84.4%) with the lowest standard deviation (+/- 10.3%).

  2. Design of dialogic eLearning-to-learn: metalearning as pedagogical methodology

    DEFF Research Database (Denmark)

    Sorensen, Elsebeth Korsgaard

    2008-01-01

    This paper presents a perspective emphasising Meta learning (ML) as the most significant and pertinent feature for promoting a democratic, collaborative eLearning-to-Learn (eL2L) phenomenon in a global context. Through attempting to understand and clarify the powers of pedagogical design of global...... networked e Learning based on Learning-to-Learn (L2L), it makes a plea for L2L in a dialogic global learning context, offering a vision of global democratic citizens able to engage in critical dialogue with fellow learners. http://www.inderscience.com/search/index.php?action=record&rec_id=17675&prev...

  3. A novel deep learning approach for classification of EEG motor imagery signals.

    Science.gov (United States)

    Tabar, Yousef Rezaei; Halici, Ugur

    2017-02-01

    Signal classification is an important issue in brain computer interface (BCI) systems. Deep learning approaches have been used successfully in many recent studies to learn features and classify different types of data. However, the number of studies that employ these approaches on BCI applications is very limited. In this study we aim to use deep learning methods to improve classification performance of EEG motor imagery signals. In this study we investigate convolutional neural networks (CNN) and stacked autoencoders (SAE) to classify EEG Motor Imagery signals. A new form of input is introduced to combine time, frequency and location information extracted from EEG signal and it is used in CNN having one 1D convolutional and one max-pooling layers. We also proposed a new deep network by combining CNN and SAE. In this network, the features that are extracted in CNN are classified through the deep network SAE. The classification performance obtained by the proposed method on BCI competition IV dataset 2b in terms of kappa value is 0.547. Our approach yields 9% improvement over the winner algorithm of the competition. Our results show that deep learning methods provide better classification performance compared to other state of art approaches. These methods can be applied successfully to BCI systems where the amount of data is large due to daily recording.

  4. An Investigation on Individual Students' Perceptions of Interest Utilizing a Blended Learning Approach

    Science.gov (United States)

    Shroff, Ronnie H.; Vogel, Douglas R.

    2010-01-01

    Research has established that individual student interest has a positive effect on learning and academic achievement. However, little is known about the impact of a blended learning approach on individual student interest and whether combinations of online and face-to-face learning activities significantly enhance student interest. This paper…

  5. Learning through role-playing games: an approach for active learning and teaching

    Directory of Open Access Journals (Sweden)

    Marco Antonio Ferreira Randi

    Full Text Available This study evaluates the use of role-playing games (RPGs as a methodological approach for teaching cellular biology, assessing student satisfaction, learning outcomes, and retention of acquired knowledge. First-year undergraduate medical students at two Brazilian public universities attended either an RPG-based class (RPG group or a lecture (lecture-based group on topics related to cellular biology. Pre- and post-RPG-based class questionnaires were compared to scores in regular exams and in an unannounced test one year later to assess students' attitudes and learning. From the 230 students that attended the RPG classes, 78.4% responded that the RPG-based classes were an effective tool for learning; 55.4% thought that such classes were better than lectures but did not replace them; and 81% responded that they would use this method. The lecture-based group achieved a higher grade in 1 of 14 regular exam questions. In the medium-term evaluation (one year later, the RPG group scored higher in 2 of 12 questions. RPG classes are thus quantitatively as effective as formal lectures, are well accepted by students, and may serve as educational tools, giving students the chance to learn actively and potentially retain the acquired knowledge more efficiently.

  6. Can Task-based Learning Approach Help Attract Students with Diverse Backgrounds Learn Chinese at A Danish University?

    DEFF Research Database (Denmark)

    Ruan, Youjin; Duan, Xiaoju; Wang, Li

    2013-01-01

    Task-based method is regarded as a meaningful approach for promoting interaction and collaboration in language learning. In an elective Chinese language beginner course at Aalborg University, Denmark, a selection of tasks are designed and used to attract the students’ interests in learning a new...... and study programs showed good interests in this method and the course itself. Nevertheless, it is necessary to study the concrete effect of various types of tasks to maximize the learning outcome....... foreign language. Chinese culture elements are also integrated into the tasks and the learning process. By analyzing seven items of a post-course survey, this paper investigates the learners’ opinions towards the Task-based language teaching and learning method and toward the method of integrating culture...

  7. Curriculum as a support to investigative approach in learning chemistry

    Directory of Open Access Journals (Sweden)

    Tomašević Biljana

    2009-01-01

    Full Text Available One of the main reasons for low achievement of our students in international tests is the lack of functional, applicable knowledge. Formation of such knowledge demands changing the usual way of implementation of instruction (transfer of ready-made knowledge to learning through performing simple research and practical work. Considering the fact that instruction, as an organised process, takes place in frameworks determined in advance, which are arranged and regulated on the national level by curricula, it is assumed that this kind of approach must originate precisely from curricula, which is not the case in our educational practice. The goal of this paper was to determine the way in which this kind of approach in instruction and learning of chemistry can be supported by the curriculum, in order for it to become a part of regular teaching practice on the national level. The paper presents how different structural components of curricula from eight different educational systems (four European countries, one Asian country, two American federal states and one Canadian province are used to promote and support the importance of research work in instruction and learning of chemistry. The curricula from Slovenia, England, Denmark, Malta, Singapore, North Carolina, Utah and Ontario were analyzed in order to determine the kind of information they offer within structural components and accordingly, the way in which each component promotes research approach to learning chemistry, how it guides the teacher in planning such activities in the classroom, organization and performing instruction, monitoring and evaluating students' achievements.

  8. High Touch Approach and Its Relationship with Students’ Learning Outcomes at IAIN Bukittinggi

    Directory of Open Access Journals (Sweden)

    Darul Ilmi

    2017-07-01

    Full Text Available Learning without students’ center tends to create less passionate students in following the lecture. They tend to ignore their lecturer. They have less attention, and try to create ineffective conditions, therefore, the learning atmosphere will become less effective to achieve the intended goals.  The purpose of the research is to determine the process of learning, the implementation of High Touch approach, and factors that influence its implementation. Classroom action research approach was used at  department of mathematics which involve students who enroll at academic year 2016/2017 IAIN Bukittinggi. The research was done in two cycles in which one cycle conducted three meetings. The instruments used were observation, essay questions, and tasks given to students. The results show that there is an improvement in students’ participation and activeness in learning when their lecturer builds learning experience through reinforcement, affection, guide, directive action, and good modeling by student–center andself-learning activities, and independent learning skill orientations showed in cycle I and II. It implies that implementing high touch may lead students to be more active, creative, and fun in learning

  9. A Project-Based Learning Approach to Teaching Physics for Pre-Service Elementary School Teacher Education Students

    Science.gov (United States)

    Goldstein, Olzan

    2016-01-01

    This paper describes the impact of the project-based learning (PBL) approach on learning and teaching physics from the perspective of pre-service elementary school teacher education students and an instructor. This approach promoted meaningful learning (mainly in the scope of projects), higher motivation, and active involvement of students in…

  10. Test Preparation in the Accountability Era: Toward a Learning-Oriented Approach

    Science.gov (United States)

    Gebril, Atta

    2018-01-01

    The article introduces a learning-oriented approach to test preparation that could help in easing the tension between learning and assessment. The first part of the article discusses the different concepts that are usually used in the context of test preparation. The second section reports on the literature pertaining to the effects of test…

  11. VarioML framework for comprehensive variation data representation and exchange

    Directory of Open Access Journals (Sweden)

    Byrne Myles

    2012-10-01

    Full Text Available Abstract Background Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement. Results The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components. Conclusions VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.

  12. Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach

    NARCIS (Netherlands)

    Miao, Yongwu; Sloep, Peter; Koper, Rob

    2009-01-01

    Miao, Y., Sloep, P. B., & Koper, R. (2010). Facilitating Work Based Learning Projects: A Business Process Oriented Knowledge Management Approach. In D. Griffiths & R. Koper (Eds.), Rethinking Learning and Employment at a Time of Economic Uncertainty. Proceedings of the 6th TENCompetence Open

  13. A design-based approach with vocational teachers to promote self-regulated learning

    NARCIS (Netherlands)

    Jossberger, Helen; Brand-Gruwel, Saskia; Van de Wiel, Margje; Boshuizen, Els

    2011-01-01

    Jossberger, H., Brand-Gruwel, S., Van de Wiel, M., & Boshuizen, H. P. A. (2011, August). A design-based approach with vocational teachers to promote self-regulated learning. Presentation at the 14th European Conference for Research on Learning and Instruction (EARLI), Exeter, England.

  14. A comparative evaluation of supervised and unsupervised representation learning approaches for anaplastic medulloblastoma differentiation

    Science.gov (United States)

    Cruz-Roa, Angel; Arevalo, John; Basavanhally, Ajay; Madabhushi, Anant; González, Fabio

    2015-01-01

    Learning data representations directly from the data itself is an approach that has shown great success in different pattern recognition problems, outperforming state-of-the-art feature extraction schemes for different tasks in computer vision, speech recognition and natural language processing. Representation learning applies unsupervised and supervised machine learning methods to large amounts of data to find building-blocks that better represent the information in it. Digitized histopathology images represents a very good testbed for representation learning since it involves large amounts of high complex, visual data. This paper presents a comparative evaluation of different supervised and unsupervised representation learning architectures to specifically address open questions on what type of learning architectures (deep or shallow), type of learning (unsupervised or supervised) is optimal. In this paper we limit ourselves to addressing these questions in the context of distinguishing between anaplastic and non-anaplastic medulloblastomas from routine haematoxylin and eosin stained images. The unsupervised approaches evaluated were sparse autoencoders and topographic reconstruct independent component analysis, and the supervised approach was convolutional neural networks. Experimental results show that shallow architectures with more neurons are better than deeper architectures without taking into account local space invariances and that topographic constraints provide useful invariant features in scale and rotations for efficient tumor differentiation.

  15. Learning Biology through Innovative Curricula: A Comparison of Game- and Nongame-Based Approaches

    Science.gov (United States)

    Sadler, Troy D.; Romine, William L.; Menon, Deepika; Ferdig, Richard E.; Annetta, Leonard

    2015-01-01

    This study explored student learning in the context of innovative biotechnology curricula and the effects of gaming as a central element of the learning experience. The quasi-experimentally designed study compared learning outcomes between two curricular approaches: One built around a computer-based game, and the other built around a narrative…

  16. The use of an active learning approach in a SCALE-UP learning space improves academic performance in undergraduate General Biology.

    Science.gov (United States)

    Hacisalihoglu, Gokhan; Stephens, Desmond; Johnson, Lewis; Edington, Maurice

    2018-01-01

    Active learning is a pedagogical approach that involves students engaging in collaborative learning, which enables them to take more responsibility for their learning and improve their critical thinking skills. While prior research examined student performance at majority universities, this study focuses on specifically Historically Black Colleges and Universities (HBCUs) for the first time. Here we present work that focuses on the impact of active learning interventions at Florida A&M University, where we measured the impact of active learning strategies coupled with a SCALE-UP (Student Centered Active Learning Environment with Upside-down Pedagogies) learning environment on student success in General Biology. In biology sections where active learning techniques were employed, students watched online videos and completed specific activities before class covering information previously presented in a traditional lecture format. In-class activities were then carefully planned to reinforce critical concepts and enhance critical thinking skills through active learning techniques such as the one-minute paper, think-pair-share, and the utilization of clickers. Students in the active learning and control groups covered the same topics, took the same summative examinations and completed identical homework sets. In addition, the same instructor taught all of the sections included in this study. Testing demonstrated that these interventions increased learning gains by as much as 16%, and students reported an increase in their positive perceptions of active learning and biology. Overall, our results suggest that active learning approaches coupled with the SCALE-UP environment may provide an added opportunity for student success when compared with the standard modes of instruction in General Biology.

  17. Deep learning for single-molecule science

    Science.gov (United States)

    Albrecht, Tim; Slabaugh, Gregory; Alonso, Eduardo; Al-Arif, SM Masudur R.

    2017-10-01

    Exploring and making predictions based on single-molecule data can be challenging, not only due to the sheer size of the datasets, but also because a priori knowledge about the signal characteristics is typically limited and poor signal-to-noise ratio. For example, hypothesis-driven data exploration, informed by an expectation of the signal characteristics, can lead to interpretation bias or loss of information. Equally, even when the different data categories are known, e.g., the four bases in DNA sequencing, it is often difficult to know how to make best use of the available information content. The latest developments in machine learning (ML), so-called deep learning (DL) offer interesting, new avenues to address such challenges. In some applications, such as speech and image recognition, DL has been able to outperform conventional ML strategies and even human performance. However, to date DL has not been applied much in single-molecule science, presumably in part because relatively little is known about the ‘internal workings’ of such DL tools within single-molecule science as a field. In this Tutorial, we make an attempt to illustrate in a step-by-step guide how one of those, a convolutional neural network (CNN), may be used for base calling in DNA sequencing applications. We compare it with a SVM as a more conventional ML method, and discuss some of the strengths and weaknesses of the approach. In particular, a ‘deep’ neural network has many features of a ‘black box’, which has important implications on how we look at and interpret data.

  18. A STUDY ON LEARNING APPROACHES USED AMONG POST-GRADUATE STUDENTS IN RESEARCH UNIVERSITY

    Directory of Open Access Journals (Sweden)

    Roziana Shaari

    2011-07-01

    Full Text Available This paper aims to determine the method of learningapproaches adopted by post-graduate students in Universiti Teknologi Malaysia(UTM and to identifywhether these approaches are associated with demographic factors (age, gender,main streams, mode of study and working experience. Participants included 354post-graduate students from different faculties inUTM whereas questionnaireswere distributed via email and throughdesignated contact person. The One-WayAnalysis of Variance (ANOVA revealed that there were significant differenceson the usage of the three post-graduates’ learningapproaches across age, mainstreams and years of working experience. Significance was not seen betweenlearning approaches on gender and mode of study. Deep approach was found to bepreferred approaches to their learning methods. Ourinvestigation suggests thatapproach to learning should be included in their academics, however thesuggestion is tailored according on the tasks givento the students. Hence, weconcluded that further investigation could be carried out the effect of learningenvironment towards students dynamic in learning.

  19. Blended Learning: An Innovative Approach

    Science.gov (United States)

    Lalima; Dangwal, Kiran Lata

    2017-01-01

    Blended learning is an innovative concept that embraces the advantages of both traditional teaching in the classroom and ICT supported learning including both offline learning and online learning. It has scope for collaborative learning; constructive learning and computer assisted learning (CAI). Blended learning needs rigorous efforts, right…

  20. A new approach for crude oil price prediction based on stream learning

    Directory of Open Access Journals (Sweden)

    Shuang Gao

    2017-01-01

    Full Text Available Crude oil is the world's leading fuel, and its prices have a big impact on the global environment, economy as well as oil exploration and exploitation activities. Oil price forecasts are very useful to industries, governments and individuals. Although many methods have been developed for predicting oil prices, it remains one of the most challenging forecasting problems due to the high volatility of oil prices. In this paper, we propose a novel approach for crude oil price prediction based on a new machine learning paradigm called stream learning. The main advantage of our stream learning approach is that the prediction model can capture the changing pattern of oil prices since the model is continuously updated whenever new oil price data are available, with very small constant overhead. To evaluate the forecasting ability of our stream learning model, we compare it with three other popular oil price prediction models. The experiment results show that our stream learning model achieves the highest accuracy in terms of both mean squared prediction error and directional accuracy ratio over a variety of forecast time horizons.

  1. WeedML: a Tool for Collaborative Weed Demographic Modeling

    OpenAIRE

    Holst, Niels

    2010-01-01

    WeedML is a proposed standard to formulate models of weed demography, or maybe even complex models in general, that are both transparent and straightforward to re-use as building blocks for new models. The paper describes the design and thoughts behind WeedML which relies on XML and object-oriented systems development. Proof-of-concept software is provided as open-source C++ code and executables that can be downloaded freely.

  2. Using an Active-Learning Approach to Teach Epigenetics

    Science.gov (United States)

    Colon-Berlingeri, Migdalisel

    2010-01-01

    Epigenetics involves heritable changes in gene expression that do not involve alterations in the DNA sequence. I developed an active-learning approach to convey this topic to students in a college genetics course. I posted a brief summary of the topic before class to stimulate exchange in cooperative groups. During class, we discussed the…

  3. Students' approaches to learning in a clinical practicum: A psychometric evaluation based on item response theory.

    Science.gov (United States)

    Zhao, Yue; Kuan, Hoi Kei; Chung, Joyce O K; Chan, Cecilia K Y; Li, William H C

    2018-07-01

    The investigation of learning approaches in the clinical workplace context has remained an under-researched area. Despite the validation of learning approach instruments and their applications in various clinical contexts, little is known about the extent to which an individual item, that reflects a specific learning strategy and motive, effectively contributes to characterizing students' learning approaches. This study aimed to measure nursing students' approaches to learning in a clinical practicum using the Approaches to Learning at Work Questionnaire (ALWQ). Survey research design was used in the study. A sample of year 3 nursing students (n = 208) who undertook a 6-week clinical practicum course participated in the study. Factor analyses were conducted, followed by an item response theory analysis, including model assumption evaluation (unidimensionality and local independence), item calibration and goodness-of-fit assessment. Two subscales, deep and surface, were derived. Findings suggested that: (a) items measuring the deep motive from intrinsic interest and deep strategies of relating new ideas to similar situations, and that of concept mapping served as the strongest discriminating indicators; (b) the surface strategy of memorizing facts and details without an overall picture exhibited the highest discriminating power among all surface items; and, (c) both subscales appeared to be informative in assessing a broad range of the corresponding latent trait. The 21-item ALWQ derived from this study presented an efficient, internally consistent and precise measure. Findings provided a useful psychometric evaluation of the ALWQ in the clinical practicum context, added evidence to the utility of the ALWQ for nursing education practice and research, and echoed the discussions from previous studies on the role of the contextual factors in influencing student choices of different learning strategies. They provided insights for clinical educators to measure

  4. Acceleration of saddle-point searches with machine learning

    Energy Technology Data Exchange (ETDEWEB)

    Peterson, Andrew A., E-mail: andrew-peterson@brown.edu [School of Engineering, Brown University, Providence, Rhode Island 02912 (United States)

    2016-08-21

    In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the number of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.

  5. Acceleration of saddle-point searches with machine learning

    International Nuclear Information System (INIS)

    Peterson, Andrew A.

    2016-01-01

    In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the number of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.

  6. Acceleration of saddle-point searches with machine learning.

    Science.gov (United States)

    Peterson, Andrew A

    2016-08-21

    In atomistic simulations, the location of the saddle point on the potential-energy surface (PES) gives important information on transitions between local minima, for example, via transition-state theory. However, the search for saddle points often involves hundreds or thousands of ab initio force calls, which are typically all done at full accuracy. This results in the vast majority of the computational effort being spent calculating the electronic structure of states not important to the researcher, and very little time performing the calculation of the saddle point state itself. In this work, we describe how machine learning (ML) can reduce the number of intermediate ab initio calculations needed to locate saddle points. Since machine-learning models can learn from, and thus mimic, atomistic simulations, the saddle-point search can be conducted rapidly in the machine-learning representation. The saddle-point prediction can then be verified by an ab initio calculation; if it is incorrect, this strategically has identified regions of the PES where the machine-learning representation has insufficient training data. When these training data are used to improve the machine-learning model, the estimates greatly improve. This approach can be systematized, and in two simple example problems we demonstrate a dramatic reduction in the number of ab initio force calls. We expect that this approach and future refinements will greatly accelerate searches for saddle points, as well as other searches on the potential energy surface, as machine-learning methods see greater adoption by the atomistics community.

  7. Machine-learning techniques for family demography: an application of random forests to the analysis of divorce determinants in Germany

    OpenAIRE

    Arpino, Bruno; Le Moglie, Marco; Mencarini, Letizia

    2018-01-01

    Demographers often analyze the determinants of life-course events with parametric regression-type approaches. Here, we present a class of nonparametric approaches, broadly defined as machine learning (ML) techniques, and discuss advantages and disadvantages of a popular type known as random forest. We argue that random forests can be useful either as a substitute, or a complement, to more standard parametric regression modeling. Our discussion of random forests is intuitive and...

  8. Assessing the Learning Path Specification: a Pragmatic Quality Approach

    NARCIS (Netherlands)

    Janssen, José; Berlanga, Adriana; Heyenrath, Stef; Martens, Harrie; Vogten, Hubert; Finders, Anton; Herder, Eelco; Hermans, Henry; Melero, Javier; Schaeps, Leon; Koper, Rob

    2010-01-01

    Janssen, J., Berlanga, A. J., Heyenrath, S., Martens, H., Vogten, H., Finders, A., Herder, E., Hermans, H., Melero Gallardo, J., Schaeps, L., & Koper, R. (2010). Assessing the Learning Path Specification: a Pragmatic Quality Approach. Journal of Universal Computer Science, 16(21), 3191-3209.

  9. Prediction of revascularization after myocardial perfusion SPECT by machine learning in a large population.

    Science.gov (United States)

    Arsanjani, Reza; Dey, Damini; Khachatryan, Tigran; Shalev, Aryeh; Hayes, Sean W; Fish, Mathews; Nakanishi, Rine; Germano, Guido; Berman, Daniel S; Slomka, Piotr

    2015-10-01

    We aimed to investigate if early revascularization in patients with suspected coronary artery disease can be effectively predicted by integrating clinical data and quantitative image features derived from perfusion SPECT (MPS) by machine learning (ML) approach. 713 rest (201)Thallium/stress (99m)Technetium MPS studies with correlating invasive angiography with 372 revascularization events (275 PCI/97 CABG) within 90 days after MPS (91% within 30 days) were considered. Transient ischemic dilation, stress combined supine/prone total perfusion deficit (TPD), supine rest and stress TPD, exercise ejection fraction, and end-systolic volume, along with clinical parameters including patient gender, history of hypertension and diabetes mellitus, ST-depression on baseline ECG, ECG and clinical response during stress, and post-ECG probability by boosted ensemble ML algorithm (LogitBoost) to predict revascularization events. These features were selected using an automated feature selection algorithm from all available clinical and quantitative data (33 parameters). Tenfold cross-validation was utilized to train and test the prediction model. The prediction of revascularization by ML algorithm was compared to standalone measures of perfusion and visual analysis by two experienced readers utilizing all imaging, quantitative, and clinical data. The sensitivity of machine learning (ML) (73.6% ± 4.3%) for prediction of revascularization was similar to one reader (73.9% ± 4.6%) and standalone measures of perfusion (75.5% ± 4.5%). The specificity of ML (74.7% ± 4.2%) was also better than both expert readers (67.2% ± 4.9% and 66.0% ± 5.0%, P < .05), but was similar to ischemic TPD (68.3% ± 4.9%, P < .05). The receiver operator characteristics areas under curve for ML (0.81 ± 0.02) was similar to reader 1 (0.81 ± 0.02) but superior to reader 2 (0.72 ± 0.02, P < .01) and standalone measure of perfusion (0.77 ± 0.02, P < .01). ML approach is comparable or better than

  10. Problematic Smartphone Use, Deep and Surface Approaches to Learning, and Social Media Use in Lectures †

    Science.gov (United States)

    Rozgonjuk, Dmitri; Saal, Kristiina

    2018-01-01

    Several studies have shown that problematic smartphone use (PSU) is related to detrimental outcomes, such as worse psychological well-being, higher cognitive distraction, and poorer academic outcomes. In addition, many studies have shown that PSU is strongly related to social media use. Despite this, the relationships between PSU, as well as the frequency of social media use in lectures, and different approaches to learning have not been previously studied. In our study, we hypothesized that both PSU and the frequency of social media use in lectures are negatively correlated with a deep approach to learning (defined as learning for understanding) and positively correlated with a surface approach to learning (defined as superficial learning). The study participants were 415 Estonian university students aged 19–46 years (78.8% females; age M = 23.37, SD = 4.19); the effective sample comprised 405 participants aged 19–46 years (79.0% females; age M = 23.33, SD = 4.21). In addition to basic socio-demographics, participants were asked about the frequency of their social media use in lectures, and they filled out the Estonian Smartphone Addiction Proneness Scale and the Estonian Revised Study Process Questionnaire. Bivariate correlation analysis showed that PSU and the frequency of social media use in lectures were negatively correlated with a deep approach to learning and positively correlated with a surface approach to learning. Mediation analysis showed that social media use in lectures completely mediates the relationship between PSU and approaches to learning. These results indicate that the frequency of social media use in lectures might explain the relationships between poorer academic outcomes and PSU. PMID:29316697

  11. Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.

    Science.gov (United States)

    Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel

    2017-06-01

    Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.

  12. Deep-Learning-Based Approach for Prediction of Algal Blooms

    Directory of Open Access Journals (Sweden)

    Feng Zhang

    2016-10-01

    Full Text Available Algal blooms have recently become a critical global environmental concern which might put economic development and sustainability at risk. However, the accurate prediction of algal blooms remains a challenging scientific problem. In this study, a novel prediction approach for algal blooms based on deep learning is presented—a powerful tool to represent and predict highly dynamic and complex phenomena. The proposed approach constructs a five-layered model to extract detailed relationships between the density of phytoplankton cells and various environmental parameters. The algal blooms can be predicted by the phytoplankton density obtained from the output layer. A case study is conducted in coastal waters of East China using both our model and a traditional back-propagation neural network for comparison. The results show that the deep-learning-based model yields better generalization and greater accuracy in predicting algal blooms than a traditional shallow neural network does.

  13. An overview of the CellML API and its implementation

    Directory of Open Access Journals (Sweden)

    Halstead Matt

    2010-04-01

    Full Text Available Abstract Background CellML is an XML based language for representing mathematical models, in a machine-independent form which is suitable for their exchange between different authors, and for archival in a model repository. Allowing for the exchange and archival of models in a computer readable form is a key strategic goal in bioinformatics, because of the associated improvements in scientific record accuracy, the faster iterative process of scientific development, and the ability to combine models into large integrative models. However, for CellML models to be useful, tools which can process them correctly are needed. Due to some of the more complex features present in CellML models, such as imports, developing code ab initio to correctly process models can be an onerous task. For this reason, there is a clear and pressing need for an application programming interface (API, and a good implementation of that API, upon which tools can base their support for CellML. Results We developed an API which allows the information in CellML models to be retrieved and/or modified. We also developed a series of optional extension APIs, for tasks such as simplifying the handling of connections between variables, dealing with physical units, validating models, and translating models into different procedural languages. We have also provided a Free/Open Source implementation of this application programming interface, optimised to achieve good performance. Conclusions Tools have been developed using the API which are mature enough for widespread use. The API has the potential to accelerate the development of additional tools capable of processing CellML, and ultimately lead to an increased level of sharing of mathematical model descriptions.

  14. Machine learning & artificial intelligence in the quantum domain: a review of recent progress.

    Science.gov (United States)

    Dunjko, Vedran; Briegel, Hans J

    2018-03-05

    Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and

  15. A blended learning approach to teaching sociolinguistic research methods

    Directory of Open Access Journals (Sweden)

    Olivier, Jako

    2014-12-01

    Full Text Available This article reports on the use of Wiktionary, an open source online dictionary, as well as generic wiki pages within a university’s e-learning environment as teaching and learning resources in an Afrikaans sociolinguistics module. In a communal constructivist manner students learnt, but also constructed learning content. From the qualitative research conducted with students it is clear that wikis provide for effective facilitation of a blended learning approach to sociolinguistic research. The use of this medium was positively received, however, some students did prefer handing in assignments in hard copy. The issues of computer literacy and access to the internet were also raised by the respondents. The use of wikis and Wiktionary prompted useful unplanned discussions around reliability and quality of public wikis. The use of a public wiki such as Wiktionary served as encouragement for students as they were able to contribute to the promotion of Afrikaans in this way.

  16. Theoretical analysis of hydrogen chemisorption on Pd(111), Re(0001) and PdML/Re(0001), ReML/Pd(111) pseudomorphic overlayers

    DEFF Research Database (Denmark)

    Pallassana, Venkataraman; Neurock, Matthew; Hansen, Lars Bruno

    1999-01-01

    not appear to provide an independent parameter for assessing surface reactivity. The weak chemisorption of hydrogen on the Pd-ML/Re(0001) surface relates to substantial lowering of the d-band center of Pd, when it is pseudomorphically deposited as a monolayer on a Re substrate. [S0163-1829(99)00331-2].......Gradient-corrected density-functional theory (DFT-GGA) periodic slab calculations have been used to analyze the binding of atomic hydrogen on monometallic Pd(111), Re(0001), and bimetallic Pd-mL/Re(0001) [pseudomorphic monolayer of Pd(111) on Re(0001)] and Re-ML/Pd(111) surfaces. The computed...

  17. Learning to perceive in the sensorimotor approach: Piaget's theory of equilibration interpreted dynamically

    Directory of Open Access Journals (Sweden)

    Ezequiel Alejandro Di Paolo

    2014-07-01

    Full Text Available Learning to perceive faces a classical paradox: if understanding is required for perception, how can we learn to perceive something new, something we do not yet understand? According to the sensorimotor approach, perception involves mastery of regular sensorimotor co-variations that depend on the agent and the environment, also known as the ‘laws’ of sensorimotor contingencies. In this sense, perception involves enacting relevant sensorimotor skills in each situation. It is important for this proposal that such skills can be learned and refined with experience and yet up to this date, the sensorimotor approach has had no explicit theory of perceptual learning. The situation is made more complex if we acknowledge the open-ended nature of human learning. In this paper we propose Piaget’s theory of equilibration as a potential candidate to fulfill this role. This theory highlights the importance of intrinsic sensorimotor norms, in terms of the closure of sensorimotor schemes. It also explains how the equilibration of a sensorimotor organization faced with novelty or breakdowns proceeds by re-shaping pre-existing structures in coupling with dynamical regularities of the world. This way learning to perceive is guided by the equilibration of emerging forms of skillful coping with the world. We demonstrate the compatibility between Piaget’s theory and the sensorimotor approach by providing a dynamical formalization of equilibration to give an explicit micro-genetic account of sensorimotor learning and, by extension, of how we learn to perceive. This allows us to draw important lessons in the form of general principles for open-ended sensorimotor learning, including the need for an intrinsic normative evaluation by the agent itself. We also explore implications of our micro-genetic account at the personal level.

  18. From Indoctrination to Initiation: A Non-Coercive Approach to Faith-Learning Integration

    Science.gov (United States)

    Reichard, Joshua D.

    2013-01-01

    This article contributes to ongoing discussions related to the nature, scope, and methods of faith-learning integration. The "initiation" approach developed by Tim McDonough (2011) is adapted to faith-learning integration in an attempt to bridge polarizing discussions regarding indoctrination versus rational autonomy and critical…

  19. Learning to perceive in the sensorimotor approach: Piaget's theory of equilibration interpreted dynamically.

    Science.gov (United States)

    Di Paolo, Ezequiel Alejandro; Barandiaran, Xabier E; Beaton, Michael; Buhrmann, Thomas

    2014-01-01

    if understanding is required for perception, how can we learn to perceive something new, something we do not yet understand? According to the sensorimotor approach, perception involves mastery of regular sensorimotor co-variations that depend on the agent and the environment, also known as the "laws" of sensorimotor contingencies (SMCs). In this sense, perception involves enacting relevant sensorimotor skills in each situation. It is important for this proposal that such skills can be learned and refined with experience and yet up to this date, the sensorimotor approach has had no explicit theory of perceptual learning. The situation is made more complex if we acknowledge the open-ended nature of human learning. In this paper we propose Piaget's theory of equilibration as a potential candidate to fulfill this role. This theory highlights the importance of intrinsic sensorimotor norms, in terms of the closure of sensorimotor schemes. It also explains how the equilibration of a sensorimotor organization faced with novelty or breakdowns proceeds by re-shaping pre-existing structures in coupling with dynamical regularities of the world. This way learning to perceive is guided by the equilibration of emerging forms of skillful coping with the world. We demonstrate the compatibility between Piaget's theory and the sensorimotor approach by providing a dynamical formalization of equilibration to give an explicit micro-genetic account of sensorimotor learning and, by extension, of how we learn to perceive. This allows us to draw important lessons in the form of general principles for open-ended sensorimotor learning, including the need for an intrinsic normative evaluation by the agent itself. We also explore implications of our micro-genetic account at the personal level.

  20. Predicting Turkish Preservice Elementary Teachers' Orientations to Teaching Science with Epistemological Beliefs, Learning Conceptions, and Learning Approaches in Science

    Science.gov (United States)

    Sahin, Elif Adibelli; Deniz, Hasan; Topçu, Mustafa Sami

    2016-01-01

    The present study investigated to what extent Turkish preservice elementary teachers' orientations to teaching science could be explained by their epistemological beliefs, conceptions of learning, and approaches to learning science. The sample included 157 Turkish preservice elementary teachers. The four instruments used in the study were School…

  1. A modelling approach to study learning processes with a focus on knowledge creation

    NARCIS (Netherlands)

    Naeve, Ambjorn; Yli-Luoma, Pertti; Kravcik, Milos; Lytras, Miltiadis

    2008-01-01

    Naeve, A., Yli-Luoma, P., Kravcik, M., & Lytras, M. D. (2008). A modelling approach to study learning processes with a focus on knowledge creation. International Journal Technology Enhanced Learning, 1(1/2), 1–34.

  2. An H(∞) control approach to robust learning of feedforward neural networks.

    Science.gov (United States)

    Jing, Xingjian

    2011-09-01

    A novel H(∞) robust control approach is proposed in this study to deal with the learning problems of feedforward neural networks (FNNs). The analysis and design of a desired weight update law for the FNN is transformed into a robust controller design problem for a discrete dynamic system in terms of the estimation error. The drawbacks of some existing learning algorithms can therefore be revealed, especially for the case that the output data is fast changing with respect to the input or the output data is corrupted by noise. Based on this approach, the optimal learning parameters can be found by utilizing the linear matrix inequality (LMI) optimization techniques to achieve a predefined H(∞) "noise" attenuation level. Several existing BP-type algorithms are shown to be special cases of the new H(∞)-learning algorithm. Theoretical analysis and several examples are provided to show the advantages of the new method. Copyright © 2011 Elsevier Ltd. All rights reserved.

  3. Polymorphic New World monkeys with more than three M/L cone types

    Science.gov (United States)

    Jacobs, Gerald H.; Deegan, Jess F.

    2005-10-01

    Most New World (platyrrhine) monkeys have M/L cone photopigment polymorphisms that map directly into individual variations in visual sensitivity and color vision. We used electroretinogram flicker photometry to examine M/L cone photopigments in the New World monkey Callicebus moloch (the dusky Titi). Like other New World monkeys, this species has an M/L cone photopigment polymorphism that reflects the presence of X-chromosome opsin gene alleles. However, unlike other platyrrhines in which three M/L photopigments are typical, Callicebus has a total of five M/L cone photopigments. The peak sensitivity values for these pigments extend across the range from 530 to 562 nm. The result is an enhanced array of potential color vision phenotypes in this species.

  4. Association of Kinesthetic and Read-Write Learner with Deep Approach Learning and Academic Achievement

    Directory of Open Access Journals (Sweden)

    Latha Rajendra Kumar

    2011-06-01

    Full Text Available Background: The main purpose of the present study was to further investigate study processes, learning styles, and academic achievement in medical students. Methods: A total of 214 (mean age 22.5 years first and second year students - preclinical years - at the Asian Institute of Medical Science and Technology (AIMST University School of Medicine, in Malaysia participated.  There were 119 women (55.6% and 95 men (44.4%.   Biggs questionnaire for determining learning approaches and the VARK questionnaire for determining learning styles were used.  These were compared to the student’s performance in the assessment examinations. Results: The major findings were 1 the majority of students prefer to study alone, 2 most students employ a superficial study approach, and 3 students with high kinesthetic and read-write scores performed better on examinations and approached the subject by deep approach method compared to students with low scores.  Furthermore, there was a correlation between superficial approach scores and visual learner’s scores. Discussion: Read-write and kinesthetic learners who adopt a deep approach learning strategy perform better academically than do the auditory, visual learners that employ superficial study strategies.   Perhaps visual and auditory learners can be encouraged to adopt kinesthetic and read-write styles to enhance their performance in the exams.

  5. Is all motivation good for learning? Dissociable influences of approach and avoidance motivation in declarative memory.

    Science.gov (United States)

    Murty, Vishnu P; LaBar, Kevin S; Hamilton, Derek A; Adcock, R Alison

    2011-01-01

    The present study investigated the effects of approach versus avoidance motivation on declarative learning. Human participants navigated a virtual reality version of the Morris water task, a classic spatial memory paradigm, adapted to permit the experimental manipulation of motivation during learning. During this task, participants were instructed to navigate to correct platforms while avoiding incorrect platforms. To manipulate motivational states participants were either rewarded for navigating to correct locations (approach) or punished for navigating to incorrect platforms (avoidance). Participants' skin conductance levels (SCLs) were recorded during navigation to investigate the role of physiological arousal in motivated learning. Behavioral results revealed that, overall, approach motivation enhanced and avoidance motivation impaired memory performance compared to nonmotivated spatial learning. This advantage was evident across several performance indices, including accuracy, learning rate, path length, and proximity to platform locations during probe trials. SCL analysis revealed three key findings. First, within subjects, arousal interacted with approach motivation, such that high arousal on a given trial was associated with performance deficits. In addition, across subjects, high arousal negated or reversed the benefits of approach motivation. Finally, low-performing, highly aroused participants showed SCL responses similar to those of avoidance-motivation participants, suggesting that for these individuals, opportunities for reward may evoke states of learning similar to those typically evoked by threats of punishment. These results provide a novel characterization of how approach and avoidance motivation influence declarative memory and indicate a critical and selective role for arousal in determining how reinforcement influences goal-oriented learning.

  6. Design Guide for Earth System Science Education: Common Student Learning Objectives and Special Pedagogical Approaches

    Science.gov (United States)

    Baker, D.

    2006-12-01

    As part of the NASA-supported undergraduate Earth System Science Education (ESSE) program, fifty-seven institutions have developed and implemented a wide range of Earth system science (ESS) courses, pedagogies, and evaluation tools. The Teaching, Learning, and Evaluation section of USRA's online ESSE Design Guide showcases these ESS learning environments. This Design Guide section also provides resources for faculty who wish to develop ESS courses. It addresses important course design issues including prior student knowledge and interests, student learning objectives, learning resources, pedagogical approaches, and assessments tied to student learning objectives. The ESSE Design Guide provides links to over 130 ESS course syllabi at introductory, senior, and graduate levels. ESS courses over the past 15 years exhibit common student learning objectives and unique pedagogical approaches. From analysis of ESS course syllabi, seven common student learning objectives emerged: 1) demonstrate systems thinking, 2) develop an ESS knowledge base, 3) apply ESS to the human dimension, 4) expand and apply analytical skills, 5) improve critical thinking skills, 6) build professional/career skills, and 7) acquire an enjoyment and appreciation for science. To meet these objectives, ESSE often requires different ways of teaching than in traditional scientific disciplines. This presentation will highlight some especially successful pedagogical approaches for creating positive and engaging ESS learning environments.

  7. A Project-based Learning approach for teaching Robotics to ...

    African Journals Online (AJOL)

    In this research we used a project-based learning approach to teach robotics basics to undergraduate business computing students. The course coverage includes basic electronics, robot construction and programming using arduino. Students developed and tested a robot prototype. The project was evaluated using a ...

  8. Defining Leadership: Collegiate Women's Learning Circles: A Qualitative Approach

    Science.gov (United States)

    Preston-Cunningham, Tammie; Elbert, Chanda D.; Dooley, Kim E.

    2017-01-01

    The researchers employed qualitative methods to evaluate first-year female students' definition of "leadership" through involvement in the Women's Learning Circle. The findings revealed that students defined leadership in two dimensions: traits and behaviors. The qualitative findings explore a multidimensional approach to the voices of…

  9. Residents' perceptions of simulation as a clinical learning approach.

    Science.gov (United States)

    Walsh, Catharine M; Garg, Ankit; Ng, Stella L; Goyal, Fenny; Grover, Samir C

    2017-02-01

    Simulation is increasingly being integrated into medical education; however, there is little research into trainees' perceptions of this learning modality. We elicited trainees' perceptions of simulation-based learning, to inform how simulation is developed and applied to support training. We conducted an instrumental qualitative case study entailing 36 semi-structured one-hour interviews with 12 residents enrolled in an introductory simulation-based course. Trainees were interviewed at three time points: pre-course, post-course, and 4-6 weeks later. Interview transcripts were analyzed using a qualitative descriptive analytic approach. Residents' perceptions of simulation included: 1) simulation serves pragmatic purposes; 2) simulation provides a safe space; 3) simulation presents perils and pitfalls; and 4) optimal design for simulation: integration and tension. Key findings included residents' markedly narrow perception of simulation's capacity to support non-technical skills development or its use beyond introductory learning. Trainees' learning expectations of simulation were restricted. Educators should critically attend to the way they present simulation to learners as, based on theories of problem-framing, trainees' a priori perceptions may delimit the focus of their learning experiences. If they view simulation as merely a replica of real cases for the purpose of practicing basic skills, they may fail to benefit from the full scope of learning opportunities afforded by simulation.

  10. The Development of a Robot-Based Learning Companion: A User-Centered Design Approach

    Science.gov (United States)

    Hsieh, Yi-Zeng; Su, Mu-Chun; Chen, Sherry Y.; Chen, Gow-Dong

    2015-01-01

    A computer-vision-based method is widely employed to support the development of a variety of applications. In this vein, this study uses a computer-vision-based method to develop a playful learning system, which is a robot-based learning companion named RobotTell. Unlike existing playful learning systems, a user-centered design (UCD) approach is…

  11. ISAC's Gating-ML 2.0 data exchange standard for gating description.

    Science.gov (United States)

    Spidlen, Josef; Moore, Wayne; Brinkman, Ryan R

    2015-07-01

    The lack of software interoperability with respect to gating has traditionally been a bottleneck preventing the use of multiple analytical tools and reproducibility of flow cytometry data analysis by independent parties. To address this issue, ISAC developed Gating-ML, a computer file format to encode and interchange gates. Gating-ML 1.5 was adopted and published as an ISAC Candidate Recommendation in 2008. Feedback during the probationary period from implementors, including major commercial software companies, instrument vendors, and the wider community, has led to a streamlined Gating-ML 2.0. Gating-ML has been significantly simplified and therefore easier to support by software tools. To aid developers, free, open source reference implementations, compliance tests, and detailed examples are provided to stimulate further commercial adoption. ISAC has approved Gating-ML as a standard ready for deployment in the public domain and encourages its support within the community as it is at a mature stage of development having undergone extensive review and testing, under both theoretical and practical conditions. © 2015 International Society for Advancement of Cytometry.

  12. Brain based learning with contextual approach to mathematics achievement

    Directory of Open Access Journals (Sweden)

    V Kartikaningtyas

    2017-12-01

    Full Text Available The aim of this study was to know the effect of Brain Based Learning (BBL with a contextual approach to mathematics achievement. BBL-contextual is the learning model that designed to develop and optimize the brain ability for getting a new concept and solving the real life problem. This study method was a quasi-experiment. The population was the junior high school students. The sample chosen by using stratified cluster random sampling. The sample was 109 students. The data collected through a mathematics achievement test that was given after the treatment. The data analyzed by using one way ANOVA. The results of the study showed that BBL-contextual is better than direct learning on mathematics achievement. It means BBL-contextual could be an effective and innovative model.

  13. A FIRST LOOK AT CREATING MOCK CATALOGS WITH MACHINE LEARNING TECHNIQUES

    Energy Technology Data Exchange (ETDEWEB)

    Xu Xiaoying; Ho, Shirley; Trac, Hy; Schneider, Jeff; Ntampaka, Michelle [McWilliams Center for Cosmology, Department of Physics, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States); Poczos, Barnabas [School of Computer Science, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213 (United States)

    2013-08-01

    We investigate machine learning (ML) techniques for predicting the number of galaxies (N{sub gal}) that occupy a halo, given the halo's properties. These types of mappings are crucial for constructing the mock galaxy catalogs necessary for analyses of large-scale structure. The ML techniques proposed here distinguish themselves from traditional halo occupation distribution (HOD) modeling as they do not assume a prescribed relationship between halo properties and N{sub gal}. In addition, our ML approaches are only dependent on parent halo properties (like HOD methods), which are advantageous over subhalo-based approaches as identifying subhalos correctly is difficult. We test two algorithms: support vector machines (SVM) and k-nearest-neighbor (kNN) regression. We take galaxies and halos from the Millennium simulation and predict N{sub gal} by training our algorithms on the following six halo properties: number of particles, M{sub 200}, {sigma}{sub v}, v{sub max}, half-mass radius, and spin. For Millennium, our predicted N{sub gal} values have a mean-squared error (MSE) of {approx}0.16 for both SVM and kNN. Our predictions match the overall distribution of halos reasonably well and the galaxy correlation function at large scales to {approx}5%-10%. In addition, we demonstrate a feature selection algorithm to isolate the halo parameters that are most predictive, a useful technique for understanding the mapping between halo properties and N{sub gal}. Lastly, we investigate these ML-based approaches in making mock catalogs for different galaxy subpopulations (e.g., blue, red, high M{sub star}, low M{sub star}). Given its non-parametric nature as well as its powerful predictive and feature selection capabilities, ML offers an interesting alternative for creating mock catalogs.

  14. Adopting a blended learning approach to teaching evidence based medicine: a mixed methods study

    Science.gov (United States)

    2013-01-01

    Background Evidence Based Medicine (EBM) is a core unit delivered across many medical schools. Few studies have investigated the most effective method of teaching a course in EBM to medical students. The objective of this study was to identify whether a blended-learning approach to teaching EBM is more effective a didactic-based approach at increasing medical student competency in EBM. Methods A mixed-methods study was conducted consisting of a controlled trial and focus groups with second year graduate medical students. Students received the EBM course delivered using either a didactic approach (DID) to learning EBM or a blended-learning approach (BL). Student competency in EBM was assessed using the Berlin tool and a criterion-based assessment task, with student perceptions on the interventions assessed qualitatively. Results A total of 61 students (85.9%) participated in the study. Competency in EBM did not differ between the groups when assessed using the Berlin tool (p = 0.29). Students using the BL approach performed significantly better in one of the criterion-based assessment tasks (p = 0.01) and reported significantly higher self-perceived competence in critical appraisal skills. Qualitative analysis identified that students had a preference for the EBM course to be delivered using the BL approach. Conclusions Implementing a blended-learning approach to EBM teaching promotes greater student appreciation of EBM principles within the clinical setting. Integrating a variety of teaching modalities and approaches can increase student self-confidence and assist in bridging the gap between the theory and practice of EBM. PMID:24341502

  15. Adopting a blended learning approach to teaching evidence based medicine: a mixed methods study.

    Science.gov (United States)

    Ilic, Dragan; Hart, William; Fiddes, Patrick; Misso, Marie; Villanueva, Elmer

    2013-12-17

    Evidence Based Medicine (EBM) is a core unit delivered across many medical schools. Few studies have investigated the most effective method of teaching a course in EBM to medical students. The objective of this study was to identify whether a blended-learning approach to teaching EBM is more effective a didactic-based approach at increasing medical student competency in EBM. A mixed-methods study was conducted consisting of a controlled trial and focus groups with second year graduate medical students. Students received the EBM course delivered using either a didactic approach (DID) to learning EBM or a blended-learning approach (BL). Student competency in EBM was assessed using the Berlin tool and a criterion-based assessment task, with student perceptions on the interventions assessed qualitatively. A total of 61 students (85.9%) participated in the study. Competency in EBM did not differ between the groups when assessed using the Berlin tool (p = 0.29). Students using the BL approach performed significantly better in one of the criterion-based assessment tasks (p = 0.01) and reported significantly higher self-perceived competence in critical appraisal skills. Qualitative analysis identified that students had a preference for the EBM course to be delivered using the BL approach. Implementing a blended-learning approach to EBM teaching promotes greater student appreciation of EBM principles within the clinical setting. Integrating a variety of teaching modalities and approaches can increase student self-confidence and assist in bridging the gap between the theory and practice of EBM.

  16. Gating-ML: XML-based gating descriptions in flow cytometry.

    Science.gov (United States)

    Spidlen, Josef; Leif, Robert C; Moore, Wayne; Roederer, Mario; Brinkman, Ryan R

    2008-12-01

    The lack of software interoperability with respect to gating due to lack of a standardized mechanism for data exchange has traditionally been a bottleneck, preventing reproducibility of flow cytometry (FCM) data analysis and the usage of multiple analytical tools. To facilitate interoperability among FCM data analysis tools, members of the International Society for the Advancement of Cytometry (ISAC) Data Standards Task Force (DSTF) have developed an XML-based mechanism to formally describe gates (Gating-ML). Gating-ML, an open specification for encoding gating, data transformations and compensation, has been adopted by the ISAC DSTF as a Candidate Recommendation. Gating-ML can facilitate exchange of gating descriptions the same way that FCS facilitated for exchange of raw FCM data. Its adoption will open new collaborative opportunities as well as possibilities for advanced analyses and methods development. The ISAC DSTF is satisfied that the standard addresses the requirements for a gating exchange standard.

  17. Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology

    Directory of Open Access Journals (Sweden)

    Ashley I. Heinson

    2017-02-01

    Full Text Available Reverse vaccinology (RV is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of the BEXSERO® vaccine against Neisseria meningitidis serogroup B. RV studies have begun to incorporate machine learning (ML techniques to distinguish bacterial protective antigens (BPAs from non-BPAs. This research contributes significantly to the RV field by using permutation analysis to demonstrate that a signal for protective antigens can be curated from published data. Furthermore, the effects of the following on an ML approach to RV were also assessed: nested cross-validation, balancing selection of non-BPAs for subcellular localization, increasing the training data, and incorporating greater numbers of protein annotation tools for feature generation. These enhancements yielded a support vector machine (SVM classifier that could discriminate BPAs (n = 200 from non-BPAs (n = 200 with an area under the curve (AUC of 0.787. In addition, hierarchical clustering of BPAs revealed that intracellular BPAs clustered separately from extracellular BPAs. However, no immediate benefit was derived when training SVM classifiers on data sets exclusively containing intra- or extracellular BPAs. In conclusion, this work demonstrates that ML classifiers have great utility in RV approaches and will lead to new subunit vaccines in the future.

  18. Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology

    KAUST Repository

    Heinson, Ashley

    2017-02-01

    Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of the BEXSERO® vaccine against Neisseria meningitidis serogroup B. RV studies have begun to incorporate machine learning (ML) techniques to distinguish bacterial protective antigens (BPAs) from non-BPAs. This research contributes significantly to the RV field by using permutation analysis to demonstrate that a signal for protective antigens can be curated from published data. Furthermore, the effects of the following on an ML approach to RV were also assessed: nested cross-validation, balancing selection of non-BPAs for subcellular localization, increasing the training data, and incorporating greater numbers of protein annotation tools for feature generation. These enhancements yielded a support vector machine (SVM) classifier that could discriminate BPAs (n = 200) from non-BPAs (n = 200) with an area under the curve (AUC) of 0.787. In addition, hierarchical clustering of BPAs revealed that intracellular BPAs clustered separately from extracellular BPAs. However, no immediate benefit was derived when training SVM classifiers on data sets exclusively containing intra- or extracellular BPAs. In conclusion, this work demonstrates that ML classifiers have great utility in RV approaches and will lead to new subunit vaccines in the future.

  19. Enhancing the Biological Relevance of Machine Learning Classifiers for Reverse Vaccinology

    KAUST Repository

    Heinson, Ashley; Gunawardana, Yawwani; Moesker, Bastiaan; Hume, Carmen; Vataga, Elena; Hall, Yper; Stylianou, Elena; McShane, Helen; Williams, Ann; Niranjan, Mahesan; Woelk, Christopher

    2017-01-01

    Reverse vaccinology (RV) is a bioinformatics approach that can predict antigens with protective potential from the protein coding genomes of bacterial pathogens for subunit vaccine design. RV has become firmly established following the development of the BEXSERO® vaccine against Neisseria meningitidis serogroup B. RV studies have begun to incorporate machine learning (ML) techniques to distinguish bacterial protective antigens (BPAs) from non-BPAs. This research contributes significantly to the RV field by using permutation analysis to demonstrate that a signal for protective antigens can be curated from published data. Furthermore, the effects of the following on an ML approach to RV were also assessed: nested cross-validation, balancing selection of non-BPAs for subcellular localization, increasing the training data, and incorporating greater numbers of protein annotation tools for feature generation. These enhancements yielded a support vector machine (SVM) classifier that could discriminate BPAs (n = 200) from non-BPAs (n = 200) with an area under the curve (AUC) of 0.787. In addition, hierarchical clustering of BPAs revealed that intracellular BPAs clustered separately from extracellular BPAs. However, no immediate benefit was derived when training SVM classifiers on data sets exclusively containing intra- or extracellular BPAs. In conclusion, this work demonstrates that ML classifiers have great utility in RV approaches and will lead to new subunit vaccines in the future.

  20. The performance review of EEWS(Earthquake Early Warning System) about Gyeongju earthquakes with Ml 5.1 and Ml 5.8 in Korea

    Science.gov (United States)

    Park, Jung-Ho; Chi, Heon-Cheol; Lim, In-Seub; Seong, Yun-Jeong; Park, Jihwan

    2017-04-01

    EEW(Earthquake Early Warning) service to the public has been officially operated by KMA (Korea Meteorological Administration) from 2015 in Korea. For the KMA's official EEW service, KIGAM has adopted ElarmS from UC Berkeley BSL and modified local magnitude relation, 1-D travel time curves and association procedures with real time waveform from about 201 seismic stations of KMA, KIGAM, KINS and KEPRI. There were two moderate size earthquakes with magnitude Ml 5.1 and Ml 5.8 close to Gyeongju city located at the southeastern part of Korea on Sep. 12. 2016. We have checked the performance of EEWS(Earthquake Early Warning System) named as TrigDB by KIGAM reviewing of these two Gyeongju earthquakes. The nearest station to epicenters of two earthquakes Ml 5.1(35.7697 N, 129.1904 E) and Ml 5.8(35.7632 N, 129.1898 E) was MKL which detected P phases in about 2.1 and 3.6 seconds after the origin times respectively. The first events were issued in 6.3 and 7.0 seconds from each origin time. Because of the unstable results on the early steps due to very few stations and unexpected automated analysis, KMA has the policy to wait for more 20 seconds for confirming the reliability. For these events KMA published EEW alarms in about 26 seconds after origin times with M 5.3 and M 5.9 respectively.

  1. HEP meets ML award talk : XGBoost

    CERN Multimedia

    CERN. Geneva; CHEN, Tianqi

    2015-01-01

    Tianqi Chen and Tong He (team crowwork) have provided very early in the challenge to all participants XGBoost (for eXtreme Gradient Boosted). It is a parallelised software to train boost decision trees, which has been effectively used by many participants to the challenge. For this, they have won the "HEP meets ML" award which is the invitation to CERN happening today.

  2. Nuclear Knowledge Creation and Transfer in Enriched Learning Environments: A Practical Approach

    International Nuclear Information System (INIS)

    Ruiz, F.; Gonzalez, J.; Delgado, J.L.

    2016-01-01

    Full text: Technology, the social nature of learning and the generational learning style are conforming new models of training that are changing the roles of the instructors, the channels of communication and the proper learning content of the knowledge to be transferred. New training methodologies are being using in the primary and secondary education and “Vintage” classroom learning does not meet the educational requirements of these methodologies; therefore, it’s necessary to incorporate them in the Knowledge Management processes used in the nuclear industry. This paper describes a practical approach of an enriched learning environment with the purpose of creating and transferring nuclear knowledge. (author

  3. Perceived learning effectiveness of a course Facebook page: teacher-led versus student-led approach

    Directory of Open Access Journals (Sweden)

    Tugba Orten Tugrul

    2017-01-01

    Full Text Available This research aims to compare the perceived effectiveness of teacher -led and student-led content management approaches embraced in a course Facebook page designed to enhance traditional classroom learning. Eighty-five undergraduate marketing course students voluntarily completed a questionnaire composed of two parts; a depiction of a course Facebook page where both teacher and students can share instructional contents, and questions about perceived learning effectiveness. The findings indicate that students have more favorable evaluations of a student-led approach in sharing instructional contents on a course Facebook Page than a teacher-led approach. Additionally, it is shown that instructional contents posted by both teacher and students enhance the overall learning effectiveness of a course Facebook page incorporated into a traditional classroom teaching.

  4. Amp: A modular approach to machine learning in atomistic simulations

    Science.gov (United States)

    Khorshidi, Alireza; Peterson, Andrew A.

    2016-10-01

    Electronic structure calculations, such as those employing Kohn-Sham density functional theory or ab initio wavefunction theories, have allowed for atomistic-level understandings of a wide variety of phenomena and properties of matter at small scales. However, the computational cost of electronic structure methods drastically increases with length and time scales, which makes these methods difficult for long time-scale molecular dynamics simulations or large-sized systems. Machine-learning techniques can provide accurate potentials that can match the quality of electronic structure calculations, provided sufficient training data. These potentials can then be used to rapidly simulate large and long time-scale phenomena at similar quality to the parent electronic structure approach. Machine-learning potentials usually take a bias-free mathematical form and can be readily developed for a wide variety of systems. Electronic structure calculations have favorable properties-namely that they are noiseless and targeted training data can be produced on-demand-that make them particularly well-suited for machine learning. This paper discusses our modular approach to atomistic machine learning through the development of the open-source Atomistic Machine-learning Package (Amp), which allows for representations of both the total and atom-centered potential energy surface, in both periodic and non-periodic systems. Potentials developed through the atom-centered approach are simultaneously applicable for systems with various sizes. Interpolation can be enhanced by introducing custom descriptors of the local environment. We demonstrate this in the current work for Gaussian-type, bispectrum, and Zernike-type descriptors. Amp has an intuitive and modular structure with an interface through the python scripting language yet has parallelizable fortran components for demanding tasks; it is designed to integrate closely with the widely used Atomic Simulation Environment (ASE), which

  5. Deep Learning for ECG Classification

    Science.gov (United States)

    Pyakillya, B.; Kazachenko, N.; Mikhailovsky, N.

    2017-10-01

    The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed.

  6. A tensor-based dictionary learning approach to tomographic image reconstruction

    DEFF Research Database (Denmark)

    Soltani, Sara; Kilmer, Misha E.; Hansen, Per Christian

    2016-01-01

    We consider tomographic reconstruction using priors in the form of a dictionary learned from training images. The reconstruction has two stages: first we construct a tensor dictionary prior from our training data, and then we pose the reconstruction problem in terms of recovering the expansion...... coefficients in that dictionary. Our approach differs from past approaches in that (a) we use a third-order tensor representation for our images and (b) we recast the reconstruction problem using the tensor formulation. The dictionary learning problem is presented as a non-negative tensor factorization problem...... with sparsity constraints. The reconstruction problem is formulated in a convex optimization framework by looking for a solution with a sparse representation in the tensor dictionary. Numerical results show that our tensor formulation leads to very sparse representations of both the training images...

  7. A Multiple Cross-Cultural Comparison of Approaches to Learning

    Science.gov (United States)

    Bowden, Mark P.; Abhayawansa, Subhash; Manzin, Gregoria

    2015-01-01

    This study compares learning approaches of local English-speaking students and students from Asian countries studying at an Australian metropolitan university. The sample consists of students across 13 different countries. Unlike previous studies, students from Asian countries are subdivided into two categories: students from Confucian Heritage…

  8. A novel time series link prediction method: Learning automata approach

    Science.gov (United States)

    Moradabadi, Behnaz; Meybodi, Mohammad Reza

    2017-09-01

    Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.

  9. QualityML: a dictionary for quality metadata encoding

    Science.gov (United States)

    Ninyerola, Miquel; Sevillano, Eva; Serral, Ivette; Pons, Xavier; Zabala, Alaitz; Bastin, Lucy; Masó, Joan

    2014-05-01

    The scenario of rapidly growing geodata catalogues requires tools focused on facilitate users the choice of products. Having quality fields populated in metadata allow the users to rank and then select the best fit-for-purpose products. In this direction, we have developed the QualityML (http://qualityml.geoviqua.org), a dictionary that contains hierarchically structured concepts to precisely define and relate quality levels: from quality classes to quality measurements. Generically, a quality element is the path that goes from the higher level (quality class) to the lowest levels (statistics or quality metrics). This path is used to encode quality of datasets in the corresponding metadata schemas. The benefits of having encoded quality, in the case of data producers, are related with improvements in their product discovery and better transmission of their characteristics. In the case of data users, particularly decision-makers, they would find quality and uncertainty measures to take the best decisions as well as perform dataset intercomparison. Also it allows other components (such as visualization, discovery, or comparison tools) to be quality-aware and interoperable. On one hand, the QualityML is a profile of the ISO geospatial metadata standards providing a set of rules for precisely documenting quality indicator parameters that is structured in 6 levels. On the other hand, QualityML includes semantics and vocabularies for the quality concepts. Whenever possible, if uses statistic expressions from the UncertML dictionary (http://www.uncertml.org) encoding. However it also extends UncertML to provide list of alternative metrics that are commonly used to quantify quality. A specific example, based on a temperature dataset, is shown below. The annual mean temperature map has been validated with independent in-situ measurements to obtain a global error of 0.5 ° C. Level 0: Quality class (e.g., Thematic accuracy) Level 1: Quality indicator (e.g., Quantitative

  10. Adult Learners Understanding in Learning Islam Using the Andragogy Approach in Singapore

    Science.gov (United States)

    Kadir, Mohd Amin Bin

    2016-01-01

    This study describes adult learners understanding in learning Islam using the andragogy approach in Singapore comprising multicultural and multi-religious society. Singapore is a secular state where freedom of religion is encrypted in the constitution and Malay/Muslim comprises 13.3% of the population. Adults learn Islam to deepen their…

  11. Materials Screening for the Discovery of New Half-Heuslers: Machine Learning versus ab Initio Methods.

    Science.gov (United States)

    Legrain, Fleur; Carrete, Jesús; van Roekeghem, Ambroise; Madsen, Georg K H; Mingo, Natalio

    2018-01-18

    Machine learning (ML) is increasingly becoming a helpful tool in the search for novel functional compounds. Here we use classification via random forests to predict the stability of half-Heusler (HH) compounds, using only experimentally reported compounds as a training set. Cross-validation yields an excellent agreement between the fraction of compounds classified as stable and the actual fraction of truly stable compounds in the ICSD. The ML model is then employed to screen 71 178 different 1:1:1 compositions, yielding 481 likely stable candidates. The predicted stability of HH compounds from three previous high-throughput ab initio studies is critically analyzed from the perspective of the alternative ML approach. The incomplete consistency among the three separate ab initio studies and between them and the ML predictions suggests that additional factors beyond those considered by ab initio phase stability calculations might be determinant to the stability of the compounds. Such factors can include configurational entropies and quasiharmonic contributions.

  12. Blended Learning Approach of the Flipped Model for Partograph Short Course

    Directory of Open Access Journals (Sweden)

    Linawati Linawati

    2016-08-01

    Full Text Available Crucial demand of professional and well-trained midwives, midwifery lecturers, general practitioner, and OBGYN in Indonesia could be fulfilled by providing effective learning process to them. Udayana University through its Distance Learning Centre has offered Partograph short course in order to respond the demand. The short course has implemented blended learning approach of the flipped classroom with international collaboration. The course was joint by participants from 11 countries through video conference.  The course was well designed, conducted follow Global Development Learning Network standard, and then it was evaluated.  The course yielded high impact to the participants which could be seen from the participants’ feedback. They testified that the course was marvelous, effective and informative. Finally the evaluation results showed that all components of the learning process have significant result to the overall learning quality which was shown by their correlation coefficients.

  13. Vocational High School Students’ Creativity in Food Additives with Problem Based Learning Approach

    Science.gov (United States)

    Ratnasari, D.; Supriyanti, T.; Rosbiono, M.

    2017-09-01

    The aim of this study is to verify the creativity of vocational students through Problem Based Learning approach in the food additives. The method which used quasi-experiment with one group posttest design. The research subjects were 32 students in grade XII of a vocational high school students courses chemical analysis in Bandung city. Instrument of creativity were essay, Student Worksheet, and observation sheets. Creativity measured include creative thinking skills and creative act skills. The results showed creative thinking skills and creative act skills are good. Research showed that the problem based learning approach can be applied to develop creativity of vocational students in the food additives well, because the students are given the opportunity to determine their own experiment procedure that will be used. It is recommended to often implement Problem Based Learning approach in other chemical concepts so that students’ creativity is sustainable.

  14. A Personalized Recommendation-Based Mobile Learning Approach to Improving the Reading Performance of EFL Students

    Science.gov (United States)

    Hsu, Ching-Kun; Hwang, Gwo-Jen; Chang, Chih-Kai

    2013-01-01

    In this paper, a personalized recommendation-based mobile language learning approach is proposed. A mobile learning system has been developed based on the approach by providing a reading material recommendation mechanism for guiding EFL (English as Foreign Language) students to read articles that match their preferences and knowledge levels, and a…

  15. A Blended Learning Approach to Teaching Project Management: A Model for Active Participation and Involvement--Insights from Norway

    Science.gov (United States)

    Hussein, Bassam A.

    2015-01-01

    The paper demonstrates and evaluates the effectiveness of a blended learning approach to create a meaningful learning environment. We use the term blended learning approach in this paper to refer to the use of multiple or hybrid instructional methods that emphasize the role of learners as contributors to the learning process rather than recipients…

  16. Evaluation of ML-MC as a Depth Discriminant in Yellowstone, USA and Italy

    Science.gov (United States)

    Li, Z.; Koper, K. D.; Burlacu, R.; Sun, D.; D'Amico, S.

    2017-12-01

    Recent work has shown that the difference between two magnitude scales, ML (local Richter magnitude) and MC (coda/duration magnitude), acts as a depth discriminant in Utah. Shallow seismic sources, such as mining induced earthquakes and explosions, have strongly negative ML-MC values, while deeper tectonic earthquakes have ML-MC values near zero. These observations imply that ML-MC might be effective at discriminating small explosions from deeper natural earthquakes at local distances. In this work, we examine seismicity catalogs for the Yellowstone region and Italy to determine if ML-MCacts as a depth discriminant in these regions as well. We identified 4,780 earthquakes that occurred in the Yellowstone region between Sept. 24, 1994 and March 31, 2017 for which both ML and MC were calculated. The ML-MC distribution is well described by a Gaussian function with a mean of 0.102 and a standard deviation of 0.326. We selected a subset of these events with accurate depths and determined mean ML-MC values in various depth bins. An event depth was considered accurate if the formal depth error was less than 2 km and either (1) the nearest station was within one focal depth or (2) the distance to the nearest station was smaller than the bin size. We find that ML-MC decreases as event depths become shallower than about 10 km. Similar to the results for Utah, the decrease is statistically significant and is robust with respect to small changes in bin size and the criteria used to define accurate depths. We used a similar process to evaluate whether ML-MC was a function of source depth for 63,555 earthquakes that occurred between April 16, 2005 and April 30, 2012 in Italy. The ML-MC values in Italy are also well described by a normal distribution, with a mean of -0.477 and standard deviation of 0.315. We again find a statistically significant decrease in ML-MC for shallow earthquakes. In contrast to the Yellowstone results, for Italy ML-MC decreases at a nearly constant rate

  17. Introduction to Machine Learning: Class Notes 67577

    OpenAIRE

    Shashua, Amnon

    2009-01-01

    Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).

  18. Field visit placements: An integrated and community approach to learning in children's nursing.

    LENUS (Irish Health Repository)

    Cummins, Ann

    2010-03-01

    This paper reports on the development of a new initiative, field visit placements towards and integrated and community approach to learning for nursing students. To date, limited literature exists on the potential of community field visits as meaningful learning opportunities for nursing students. Drawing on our experiences, the structure and processes involved in implementing field visits are described in this paper. Students evaluated the field visits positively indicating that they provided a wealth of learning opportunities that enhanced their knowledge and awareness of services available to children and their families in the community. The potential of field visits to promote an integrated and community approach to placements in children\\'s nursing is discussed.

  19. A Model of e-Learning by Constructivism Approach Using Problem-Based Learning to Develop Thinking Skills for Students in Rajaghat University

    Science.gov (United States)

    Shutimarrungson, Werayut; Pumipuntu, Sangkom; Noirid, Surachet

    2014-01-01

    This research aimed to develop a model of e-learning by using Problem-Based Learning--PBL to develop thinking skills for students in Rajabhat University. The research is divided into three phases through the e-learning model via PBL with Constructivism approach as follows: Phase 1 was to study characteristics and factors through the model to…

  20. A Deep Learning based Approach to Reduced Order Modeling of Fluids using LSTM Neural Networks

    Science.gov (United States)

    Mohan, Arvind; Gaitonde, Datta

    2017-11-01

    Reduced Order Modeling (ROM) can be used as surrogates to prohibitively expensive simulations to model flow behavior for long time periods. ROM is predicated on extracting dominant spatio-temporal features of the flow from CFD or experimental datasets. We explore ROM development with a deep learning approach, which comprises of learning functional relationships between different variables in large datasets for predictive modeling. Although deep learning and related artificial intelligence based predictive modeling techniques have shown varied success in other fields, such approaches are in their initial stages of application to fluid dynamics. Here, we explore the application of the Long Short Term Memory (LSTM) neural network to sequential data, specifically to predict the time coefficients of Proper Orthogonal Decomposition (POD) modes of the flow for future timesteps, by training it on data at previous timesteps. The approach is demonstrated by constructing ROMs of several canonical flows. Additionally, we show that statistical estimates of stationarity in the training data can indicate a priori how amenable a given flow-field is to this approach. Finally, the potential and limitations of deep learning based ROM approaches will be elucidated and further developments discussed.