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Sample records for learned objectives text

  1. Learning Object Repositories

    Science.gov (United States)

    Lehman, Rosemary

    2007-01-01

    This chapter looks at the development and nature of learning objects, meta-tagging standards and taxonomies, learning object repositories, learning object repository characteristics, and types of learning object repositories, with type examples. (Contains 1 table.)

  2. Repurposing learning object components

    NARCIS (Netherlands)

    Verbert, K.; Jovanovic, J.; Gasevic, D.; Duval, E.; Meersman, R.

    2005-01-01

    This paper presents an ontology-based framework for repurposing learning object components. Unlike the usual practice where learning object components are assembled manually, the proposed framework enables on-the-fly access and repurposing of learning object components. The framework supports two

  3. Transfer Learning beyond Text Classification

    Science.gov (United States)

    Yang, Qiang

    Transfer learning is a new machine learning and data mining framework that allows the training and test data to come from different distributions or feature spaces. We can find many novel applications of machine learning and data mining where transfer learning is necessary. While much has been done in transfer learning in text classification and reinforcement learning, there has been a lack of documented success stories of novel applications of transfer learning in other areas. In this invited article, I will argue that transfer learning is in fact quite ubiquitous in many real world applications. In this article, I will illustrate this point through an overview of a broad spectrum of applications of transfer learning that range from collaborative filtering to sensor based location estimation and logical action model learning for AI planning. I will also discuss some potential future directions of transfer learning.

  4. Active Learning for Text Classification

    OpenAIRE

    Hu, Rong

    2011-01-01

    Text classification approaches are used extensively to solve real-world challenges. The success or failure of text classification systems hangs on the datasets used to train them, without a good dataset it is impossible to build a quality system. This thesis examines the applicability of active learning in text classification for the rapid and economical creation of labelled training data. Four main contributions are made in this thesis. First, we present two novel selection strategies to cho...

  5. Learning Objects Web

    DEFF Research Database (Denmark)

    Blåbjerg, Niels Jørgen

    2005-01-01

    Learning Objects Web er et DEFF projekt som Aalborg Universitetsbibliotek har initieret. Projektet tager afsæt i de resultater og erfaringer som er opnået med vores tidligere projekt Streaming Webbased Information Modules (SWIM). Vi har et internationalt netværk af interessenter som giver os...... sparring og feedback i forhold til udviklingskoncept både omkring de teoretiske rammer og i forhold til praktisk anvendelse af vores undervisningskoncept. Med disse rygstød og input har vi forfulgt ønsket om at videreudvikle SWIM i det nye projekt Learning Objects Web. Udgivelsesdato: juni...

  6. Elaborazione didattica di Learning Objects.

    Directory of Open Access Journals (Sweden)

    Luigi Guerra

    2006-01-01

    Full Text Available L’idea di un modello didattico problematico per la realizzazione di Learning Objects riprende i temi del problematicismo pedagogico e si impegna a definire un’ipotesi formativa complessa capace di valorizzare la possibile positiva compresenza integrata di strategie didattiche diverse (finanche antitetiche ma componibili in una logica appunto di matrice problematicista. Il punto di partenza del modello proposto è rappresentato dalla opportunità di definire tre tipologie fondamentali di Learning Objects, rispettivamente centrati sull’oggetto, sul processo e sul soggetto dell’apprendimento.

  7. From learning objects to learning activities

    DEFF Research Database (Denmark)

    Dalsgaard, Christian

    2005-01-01

    This paper discusses and questions the current metadata standards for learning objects from a pedagogical point of view. From a social constructivist approach, the paper discusses how learning objects can support problem based, self-governed learning activities. In order to support this approach......, it is argued that it is necessary to focus on learning activities rather than on learning objects. Further, it is argued that descriptions of learning objectives and learning activities should be separated from learning objects. The paper presents a new conception of learning objects which supports problem...... based, self-governed activities. Further, a new way of thinking pedagogy into learning objects is introduced. It is argued that a lack of pedagogical thinking in learning objects is not solved through pedagogical metadata. Instead, the paper suggests the concept of references as an alternative...

  8. Interest, Inferences, and Learning from Texts

    Science.gov (United States)

    Clinton, Virginia; van den Broek, Paul

    2012-01-01

    Topic interest and learning from texts have been found to be positively associated with each other. However, the reason for this positive association is not well understood. The purpose of this study is to examine a cognitive process, inference generation, that could explain the positive association between interest and learning from texts. In…

  9. Authoring Systems Delivering Reusable Learning Objects

    Directory of Open Access Journals (Sweden)

    George Nicola Sammour

    2009-10-01

    Full Text Available A three layer e-learning course development model has been defined based on a conceptual model of learning content object. It starts by decomposing the learning content into small chunks which are initially placed in a hierarchic structure of units and blocks. The raw content components, being the atomic learning objects (ALO, were linked to the blocks and are structured in the database. We set forward a dynamic generation of LO's using re-usable e-learning raw materials or ALO’s In that view we need a LO authoring/ assembling system fitting the requirements of interoperability and reusability and starting from selecting the raw learning content from the learning materials content database. In practice authoring systems are used to develop e-learning courses. The company EDUWEST has developed an authoring system that is database based and will be SCORM compliant in the near future.

  10. THE BLENDED LEARNING OF ELECTRICITY USING LEARNING OBJECTS IN ENGINEERING

    Directory of Open Access Journals (Sweden)

    Lilia Maria Siqueira

    2010-09-01

    Full Text Available This work presents a proposal for the blended learning of Electricity education in Engineering, using resources called learning objects. The experience occurred with students enrolled on the Electrical Engineering and Computer Engineering courses at PUCPR University. It made possible the contact with interdisciplinary themes related to the study of electricity and the professional curriculum contents. The learning objects, offered during the semester, were anchored on PUCPR’s proprietary virtual educational environment, called Eureka. The students’ evaluation results showed that the study through learning objects in a virtual environment is significant for learning.

  11. Repurposeable Learning Objects Linked to Teaching and Learning Styles

    Directory of Open Access Journals (Sweden)

    Jeremy Dunning

    2004-02-01

    Full Text Available Multimedia learning objects are an essential component of high quality, technology-mediated instruction. Learning objects allow the student to use the content learned in a particular part of a course and; 1. demonstrate mastery of the content, 2. apply that knowledge to solving a problem, and 3. use the content in a critical thinking exercise that both demonstrates mastery and allows the student to place the content within the context of the larger topic of the course. The difficulty associated with the use of learning objects on a broad scale is that they require programming skills most professors and instructors do not possess. Learning objects also tend to be custom productions and are defined in terms of the programming and code terminology, further limiting the professor's ability to understand how they are created. Learning objects defined in terms of styles of learning and teaching allow professors and instructors to develop a deeper understanding of the learning objects and the design process. A set of learning objects has been created that are designed for some of the important styles of learning and teaching. They include; visual learning, writing skills, critical thinking, time-revealed scenarios, case studies and empirical observation. The learning objects are designed and described in terms that the average instructor can readily understand , redesign and incorporate into their own courses. They are also designed in such a way that they can readily be repurposed for new applications in other courses and subject areas, with little or no additional programming.

  12. Educational Rationale Metadata for Learning Objects

    Directory of Open Access Journals (Sweden)

    Tom Carey

    2002-10-01

    Full Text Available Instructors searching for learning objects in online repositories will be guided in their choices by the content of the object, the characteristics of the learners addressed, and the learning process embodied in the object. We report here on a feasibility study for metadata to record process-oriented information about instructional approaches for learning objects, though a set of Educational Rationale [ER] tags which would allow authors to describe the critical elements in their design intent. The prototype ER tags describe activities which have been demonstrated to be of value in learning, and authors select the activities whose support was critical in their design decisions. The prototype ER tag set consists descriptors of the instructional approach used in the design, plus optional sub-elements for Comments, Importance and Features which implement the design intent. The tag set was tested by creators of four learning object modules, three intended for post-secondary learners and one for K-12 students and their families. In each case the creators reported that the ER tag set allowed them to express succinctly the key instructional approaches embedded in their designs. These results confirmed the overall feasibility of the ER tag approach as a means of capturing design intent from creators of learning objects. Much work remains to be done before a usable ER tag set could be specified, including evaluating the impact of ER tags during design to improve instructional quality of learning objects.

  13. Elaboration of Statistics Learning Objects for Mobile Devices

    Directory of Open Access Journals (Sweden)

    Francisco Javier Tapia Moreno

    2012-04-01

    Full Text Available Mobile learning (m-learning allows a person to study using a mobile computer device anywhere and anytime. In this work we report the elaboration of learning objects for the teaching of introductory statistics using cellular phones.

  14. Mere exposure alters category learning of novel objects

    Directory of Open Access Journals (Sweden)

    Jonathan R Folstein

    2010-08-01

    Full Text Available We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.

  15. Text mining from ontology learning to automated text processing applications

    CERN Document Server

    Biemann, Chris

    2014-01-01

    This book comprises a set of articles that specify the methodology of text mining, describe the creation of lexical resources in the framework of text mining and use text mining for various tasks in natural language processing (NLP). The analysis of large amounts of textual data is a prerequisite to build lexical resources such as dictionaries and ontologies and also has direct applications in automated text processing in fields such as history, healthcare and mobile applications, just to name a few. This volume gives an update in terms of the recent gains in text mining methods and reflects

  16. Learning from text benefits from enactment.

    Science.gov (United States)

    Cutica, Ilaria; Ianì, Francesco; Bucciarelli, Monica

    2014-10-01

    Classical studies on enactment have highlighted the beneficial effects of gestures performed in the encoding phase on memory for words and sentences, for both adults and children. In the present investigation, we focused on the role of enactment for learning from scientific texts among primary-school children. We assumed that enactment would favor the construction of a mental model of the text, and we verified the derived predictions that gestures at the time of encoding would result in greater numbers of correct recollections and discourse-based inferences at recall, as compared to no gestures (Exp. 1), and in a bias to confound paraphrases of the original text with the verbatim text in a recognition test (Exp. 2). The predictions were confirmed; hence, we argue in favor of a theoretical framework that accounts for the beneficial effects of enactment on memory for texts.

  17. Learning Convolutional Text Representations for Visual Question Answering

    OpenAIRE

    Wang, Zhengyang; Ji, Shuiwang

    2017-01-01

    Visual question answering is a recently proposed artificial intelligence task that requires a deep understanding of both images and texts. In deep learning, images are typically modeled through convolutional neural networks, and texts are typically modeled through recurrent neural networks. While the requirement for modeling images is similar to traditional computer vision tasks, such as object recognition and image classification, visual question answering raises a different need for textual...

  18. Authoring of Learning Objects in Context

    Science.gov (United States)

    Specht, Marcus; Kravcik, Milos

    2006-01-01

    Learning objects and content interchange standards provide new possibilities for e-learning. Nevertheless the content often lacks context data to find appropriate use for adaptive learning on demand and personalized learning experiences. In the Remotely Accessible Field Trips (RAFT) project mobile authoring of learning content in context has shown…

  19. Database functionality for learning objects

    NARCIS (Netherlands)

    Sessink, O.D.T.; Beeftink, H.H.; Hartog, R.J.M.

    2005-01-01

    The development of student-activating digital learning material in six research projects revealed several shortcomings in the current learning management systems. Once the SCORM 2004 and the IMS Sharable State Persistence specifications are implemented in learning management systems, some of these

  20. Learning Ontology from Object-Relational Database

    Directory of Open Access Journals (Sweden)

    Kaulins Andrejs

    2015-12-01

    Full Text Available This article describes a method of transformation of object-relational model into ontology. The offered method uses learning rules for such complex data types as object tables and collections – arrays of a variable size, as well as nested tables. Object types and their transformation into ontologies are insufficiently considered in scientific literature. This fact served as motivation for the authors to investigate this issue and to write the article on this matter. In the beginning, we acquaint the reader with complex data types and object-oriented databases. Then we describe an algorithm of transformation of complex data types into ontologies. At the end of the article, some examples of ontologies described in the OWL language are given.

  1. Using Learning Games to Meet Learning Objectives

    DEFF Research Database (Denmark)

    Henriksen, Thomas Duus

    2013-01-01

    This paper addresses the question on how learning games can be used to meet with the different levels in Bloom’s and the SOLO taxonomy, which are commonly used for evaluating the learning outcome of educational activities. The paper discusses the quality of game-based learning outcomes based on a...... on a case study of the learning game 6Styles....

  2. Maximizing Reading Narrative Text Ability by Probing Prompting Learning Technique

    Directory of Open Access Journals (Sweden)

    Wiwied Pratiwi

    2017-12-01

    Full Text Available The objective of this research was to know whether Probing Prompting Learning Technique can be used to get the maximum effect of students’ reading narrative ability in teaching and learning process. This research was applied collaborative action reEsearch, this research was done in two cycle. The subject of this research was 23 students at tenth grade of SMA Kartikatama Metro. The result of the research showed that the Probing Prompting Learning Technique is useful and effective to help students get maximum effect of their reading. Based on the results of the questionnaire obtained an average percentage of 95%, it indicated that application of Probing Prompting Learning Technique in teaching l reading was appropriately applied. In short that students’ responses toward Probing Prompting Learning Technique in teaching reading was positive. In conclusion, Probing Prompting Learning Technique can get maximum effect of students’ reading ability. In relation to the result of the reserach, some suggestion are offered to english teacher, that  the use of Probing Prompting learning Technique in teaching reading will get the maximum effect of students’ reading abilty.

  3. 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

  4. Learning from Scientific Texts: Personalizing the Text Increases Transfer Performance and Task Involvement

    Science.gov (United States)

    Dutke, Stephan; Grefe, Anna Christina; Leopold, Claudia

    2016-01-01

    In an experiment with 65 high-school students, we tested the hypothesis that personalizing learning materials would increase students' learning performance and motivation to study the learning materials. Students studied either a 915-word standard text on the anatomy and functionality of the human eye or a personalized version of the same text in…

  5. Text feature extraction based on deep learning: a review.

    Science.gov (United States)

    Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

    2017-01-01

    Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

  6. LONS: Learning Object Negotiation System

    Science.gov (United States)

    García, Antonio; García, Eva; de-Marcos, Luis; Martínez, José-Javier; Gutiérrez, José-María; Gutiérrez, José-Antonio; Barchino, Roberto; Otón, Salvador; Hilera, José-Ramón

    This system comes up as a result of the increase of e-learning systems. It manages all relevant modules in this context, such as the association of digital rights with the contents (courses), management and payment processing on rights. There are three blocks:

  7. Constraints on reusability of learning objects

    DEFF Research Database (Denmark)

    May, Michael; Hussmann, Peter Munkebo; Jensen, Anne Skov

    2010-01-01

    It is the aim of this paper to discuss some didactic constraints on the use and reuse of digital modular learning objects. Engineering education is used as the specific context of use with examples from courses in introductory electronics and mathematics. Digital multimedia and modular learning....... Constraints on reuse arise from the nature of conceptual understanding in higher education and the functionality of learning objects within present technologies. We will need didactic as well as technical perspectives on learning objects in designing for understanding....

  8. Unifying Learning Object Repositories in MACE

    NARCIS (Netherlands)

    Prause, Christian; Ternier, Stefaan; De Jong, Tim; Apelt, Stefan; Scholten, Marius; Wolpers, Martin; Eisenhauer, Markus; Vandeputte, Bram; Specht, Marcus; Duval, Erik

    2007-01-01

    Prause, C., Ternier, S., De Jong, T., Apelt, S., Scholten, M., Wolpers, M., et al. (2007). Unifying Learning Object Repositories in MACE. In D. Massart, J.-N. Colin & F. V. Assche (Eds.). Proceedings of the First International Workshop on Learning Object Discovery & Exchange (LODE'07). September,

  9. Tagging the didactic functionality of learning objects

    DEFF Research Database (Denmark)

    Hansen, Per Skafte; Brostroem, Stig

    2002-01-01

    From a components-in-a-network point of view, the most important issues are: a didactically based typing of the learning objects themselves; the entire design superstructure, into which the learning objects must be fitted; and the symmetry of the interfaces, as seen by each pair of the triad...

  10. Learning models of activities involving interacting objects

    DEFF Research Database (Denmark)

    Manfredotti, Cristina; Pedersen, Kim Steenstrup; Hamilton, Howard J.

    2013-01-01

    We propose the LEMAIO multi-layer framework, which makes use of hierarchical abstraction to learn models for activities involving multiple interacting objects from time sequences of data concerning the individual objects. Experiments in the sea navigation domain yielded learned models that were t...

  11. Transforming existing content into reusable Learning Objects

    NARCIS (Netherlands)

    Doorten, Monique; Giesbers, Bas; Janssen, José; Daniels, Jan; Koper, Rob

    2003-01-01

    Please cite as: Doorten, M., Giesbers, B., Janssen, J., Daniëls, J, & Koper, E.J.R., (2004). Transforming existing content into reusable learning objects. In R. McGreal, Online Education using Learning Objects (pp. 116-127). London: RoutledgeFalmer.

  12. Object recognition and concept learning with Confucius

    Energy Technology Data Exchange (ETDEWEB)

    Cohen, B; Sammut, C

    1982-01-01

    A learning program produces, as its output, a Boolean function which describes a concept. The function returns true if and only if the argument is an object which satisfies the logical expression in the body of the function. The learning program's input is a set of objects which are instances of the concept to be learnt. The paper describes an algorithm devised to learn concept descriptions in this form. 15 references.

  13. Logistic regression a self-learning text

    CERN Document Server

    Kleinbaum, David G

    1994-01-01

    This textbook provides students and professionals in the health sciences with a presentation of the use of logistic regression in research. The text is self-contained, and designed to be used both in class or as a tool for self-study. It arises from the author's many years of experience teaching this material and the notes on which it is based have been extensively used throughout the world.

  14. An Exploratory Study into the Efficacy of Learning Objects

    Directory of Open Access Journals (Sweden)

    Nicholas W. Farha, Ph.D.

    2009-07-01

    Full Text Available Learning objects have quickly become a widely accepted approach to instructional technology, particularly in on-line and computer-based learning environments. While there is a substantial body of literature concerning learning objects, very little of it verifies their efficacy. This research investigated the effectiveness of learning objects by comparing learning outcomes using a learning object with outcomes using a traditional textbook-based method of instruction. Participants were 327 undergraduate college students at a traditional public four-year coed institution, a private four-year women’s college, a private four-year engineering institution, and a public two-year community college. Through a series of independent samples t-tests and Analyses of Variance, results revealed mean scores for the learning object group that were nearly three times higher than the mean scores for the textbook-taught group. Gaming experience, age, gender, and learner preference were evaluated for their potential influence on the results; no statistically significant differences were found, implying that the learning object itself was central to the outcomes achieved. The future of learning objects is bright, and more empirical research is called for in the area of learning object effectiveness.

  15. Learning Object Retrieval and Aggregation Based on Learning Styles

    Science.gov (United States)

    Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel

    2017-01-01

    The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students' learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step…

  16. Generative Learning Objects Instantiated with Random Numbers Based Expressions

    Directory of Open Access Journals (Sweden)

    Ciprian Bogdan Chirila

    2015-12-01

    Full Text Available The development of interactive e-learning content requires special skills like programming techniques, web integration, graphic design etc. Generally, online educators do not possess such skills and their e-learning products tend to be static like presentation slides and textbooks. In this paper we propose a new interactive model of generative learning objects as a compromise betweenstatic, dull materials and dynamic, complex software e-learning materials developed by specialized teams. We find that random numbers based automatic initialization learning objects increases content diversity, interactivity thus enabling learners’ engagement. The resulted learning object model is at a limited level of complexity related to special e-learning software, intuitive and capable of increasing learners’ interactivity, engagement and motivation through dynamic content. The approach was applied successfully on several computer programing disciplines.

  17. An Imagination Effect in Learning from Scientific Text

    Science.gov (United States)

    Leopold, Claudia; Mayer, Richard E.

    2015-01-01

    Asking students to imagine the spatial arrangement of the elements in a scientific text constitutes a learning strategy intended to foster deep processing of the instructional material. Two experiments investigated the effects of mental imagery prompts on learning from scientific text. Students read a computer-based text on the human respiratory…

  18. Improving learning of anatomy with reusable learning objects

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    P Rad

    2015-12-01

    Full Text Available Introduction: The use of modern educational technologies is useful for learning, durability, sociability, and upgrading professionalism. The aim of this study was evaluating the effect of reusable learning objects on improving learning of anatomy. Methods: This was a quasi-experimental study. Fourteen (reusable learning objects RLO from different parts of anatomy of human body including thorax, abdomen, and pelvis were prepared for medical student in Yasuj University of Medical Sciences in 2009. The length of the time for RLO was between 11-22 min. Because their capacities were low, so they were easy to use with cell phone or MP4. These materials were available to the students before the classes. The mean scores of students in anatomy of human body group were compared to the medical students who were not used this method and entered the university in 2008. A questionnaire was designed by the researcher to evaluate the effect of RLO and on, content, interest and motivation, participation, preparation and attitude. Result: The mean scores of anatomy of human body of medical student who were entered the university in 2009 have been increased compare to the students in 2008, but this difference was not significant. Based on the questionnaire data, it was shown that the RLO had a positive effect on improving learning anatomy of human body (75.5% and the effective relationship (60.6%. The students were interested in using RLO (74.6%, some students (54.2% believed that this method should be replaced by lecture. Conclusion: The use of RLO could promote interests and effective communication among the students and led to increasing self-learning motivation.

  19. ROBOT LEARNING OF OBJECT MANIPULATION TASK ACTIONS FROM HUMAN DEMONSTRATIONS

    Directory of Open Access Journals (Sweden)

    Maria Kyrarini

    2017-08-01

    Full Text Available Robot learning from demonstration is a method which enables robots to learn in a similar way as humans. In this paper, a framework that enables robots to learn from multiple human demonstrations via kinesthetic teaching is presented. The subject of learning is a high-level sequence of actions, as well as the low-level trajectories necessary to be followed by the robot to perform the object manipulation task. The multiple human demonstrations are recorded and only the most similar demonstrations are selected for robot learning. The high-level learning module identifies the sequence of actions of the demonstrated task. Using Dynamic Time Warping (DTW and Gaussian Mixture Model (GMM, the model of demonstrated trajectories is learned. The learned trajectory is generated by Gaussian mixture regression (GMR from the learned Gaussian mixture model.  In online working phase, the sequence of actions is identified and experimental results show that the robot performs the learned task successfully.

  20. Learning objects and interactive whiteboards: a evaluation proposal of learning objects for mathematics teaching

    Directory of Open Access Journals (Sweden)

    Silvio Henrique Fiscarelli

    2016-05-01

    Full Text Available The current conditions of the classroom learning tend to be a one-way process based in teacher exposition, this make a negative impact on learning make it a mechanical and not meaningful activity. One possibility to improve the quality of teaching is to innovate methodologies and varying forms of presenting information to students, such as the use of technology in the teaching process. The Interactive Whiteboard (IBW is one of the technologies that are being implemented in Brazilian schools. One of the promising possibilities to add value to the use of LDI in classroom are "learning objects" (LO. However, one problem is that often the LO are not fully suited to the dynamics of IWB, whether functional or pedagogical point of view. The objective of this study is to analyze and propose a set of indicators that evaluate the learning objects for use in conjunction with Interactive Whiteboards. The selection and definition of evaluation indicators was carried from the literature review on the subject and based on LDI experiences of use in Municipal Elementary School. After defining the set of indicators was conducted a evaluation of a sample of 30 OA utilized to teaching mathematics in 3rd grade of elementary school. The results of the evaluation indicate that the proposed indicators are suitable for a pre-analysis of OA and assisting in the process of selection of these.

  1. A Critique of Stephen Downes' "Learning Objects": A Chinese perspective

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    Fuhua (Oscar Lin

    2001-07-01

    Full Text Available This paper by Stephen Downes recommends a way of sharing online teaching/ course materials to accelerate course development and make education more cost-effective. His paper is a review of basic information about learning objects (LOs and includes examples that illustrate such technical terms as XML and TML. His paper, however, does not identify several important issues such as: a the level of granularity of learning objects; b selection and integration of learning objects in an appropriate way to form higher level units of study; c training of professors in the use of learning objects; d appropriate use of metadata to facilitate composition of higher level units; and e the potential of computer agents to facilitate the dynamic composition of personalized lessons. An unorganized aggregate of learning objects simply does not constitute a course. In order to create a properly designed final course, student and instructor interaction must be built in.

  2. Predictable Locations Aid Early Object Name Learning

    Science.gov (United States)

    Benitez, Viridiana L.; Smith, Linda B.

    2012-01-01

    Expectancy-based localized attention has been shown to promote the formation and retrieval of multisensory memories in adults. Three experiments show that these processes also characterize attention and learning in 16- to 18-month old infants and, moreover, that these processes may play a critical role in supporting early object name learning. The…

  3. Learning Objects, Repositories, Sharing and Reusability

    Science.gov (United States)

    Koppi, Tony; Bogle, Lisa; Bogle, Mike

    2005-01-01

    The online Learning Resource Catalogue (LRC) Project has been part of an international consortium for several years and currently includes 25 institutions worldwide. The LRC Project has evolved for several pragmatic reasons into an academic network whereby members can identify and share reusable learning objects as well as collaborate in a number…

  4. Innovating Everything: Examining Teacher Learning of Unfamiliar Texts

    Science.gov (United States)

    Goff, Maria Hernandez

    2017-01-01

    This dissertation explored how a teacher learned to teach with and about unfamiliar (to her) media texts in her high school English classroom. This study also examined my role as the researcher/mentor in the teacher's learning and development process. Through situated learning theories (Lave & Wenger, 1991) and discourse through identities…

  5. Learning from Conflicting Texts: The Role of Intertextual Conflict Resolution in Between-Text Integration

    Science.gov (United States)

    Kobayashi, Keiichi

    2015-01-01

    The present study examined the effect of intertextual conflict resolution on learning from conflicting texts. In two experiments, participants read sets of two texts under the condition of being encouraged either to resolve a conflict between the texts' arguments (the resolution condition) or to comprehend the arguments (the comprehension…

  6. Learning second language vocabulary: neural dissociation of situation-based learning and text-based learning.

    Science.gov (United States)

    Jeong, Hyeonjeong; Sugiura, Motoaki; Sassa, Yuko; Wakusawa, Keisuke; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

    2010-04-01

    Second language (L2) acquisition necessitates learning and retrieving new words in different modes. In this study, we attempted to investigate the cortical representation of an L2 vocabulary acquired in different learning modes and in cross-modal transfer between learning and retrieval. Healthy participants learned new L2 words either by written translations (text-based learning) or in real-life situations (situation-based learning). Brain activity was then measured during subsequent retrieval of these words. The right supramarginal gyrus and left middle frontal gyrus were involved in situation-based learning and text-based learning, respectively, whereas the left inferior frontal gyrus was activated when learners used L2 knowledge in a mode different from the learning mode. Our findings indicate that the brain regions that mediate L2 memory differ according to how L2 words are learned and used. Copyright 2009 Elsevier Inc. All rights reserved.

  7. On the Concepts of Usability and Reusability of Learning Objects

    Directory of Open Access Journals (Sweden)

    Miguel-Angel Sicilia

    2003-10-01

    Full Text Available “Reusable learning objects” oriented towards increasing their potential reusability are required to satisfy concerns about their granularity and their independence of concrete contexts of use. Such requirements also entail that the definition of learning object “usability,” and the techniques required to carry out their “usability evaluation” must be substantially different from those commonly used to characterize and evaluate the usability of conventional educational applications. In this article, a specific characterization of the concept of learning object usability is discussed, which places emphasis on “reusability,” the key property of learning objects residing in repositories. The concept of learning object reusability is described as the possibility and adequacy for the object to be usable in prospective educational settings, so that usability and reusability are considered two interrelated – and in many cases conflicting – properties of learning objects. Following the proposed characterization of two characteristics or properties of learning objects, a method to evaluate usability of specific learning objects will be presented.

  8. Can Strategies Facilitate Learning from Illustrated Science Texts?

    Science.gov (United States)

    Iding, Marie K.

    2000-01-01

    Examines the effectiveness of schema training in illustration types and text-illustration relations for learning from college level physiology texts and discusses findings that are consistent with prior research on learning from illustrated materials and with dual coding theory. Considers future directions for strategy training research and…

  9. Effects of incidental pictorial and verbal adjuncts on text learning.

    Science.gov (United States)

    Terry, W S; Howe, D C

    1988-01-01

    In this study, college students read and studied texts on historical figures in psychology, which were supplemented by drawings and/or brief biographies of these persons. In Experiment 1, a 2 x 2 between-groups design was conducted in which students received one adjunct with each text, both adjuncts, or neither. In Experiment 2, a single group of students received a within-subjects manipulation of the same adjunct conditions. In the between-groups comparison, students receiving biographies learned less of the target text passages, with the group receiving illustrations and biographies performing least accurately. In the within-subject conditions, texts accompanied by an illustration were better learned, with these students doing best on the text with both picture and biography. The results suggest that adjuncts may emphasize some texts, at the expense of learning from the other texts, but that too much adjunct material interferes with the learning of the target passages.

  10. Empirical Studies On Machine Learning Based Text Classification Algorithms

    OpenAIRE

    Shweta C. Dharmadhikari; Maya Ingle; Parag Kulkarni

    2011-01-01

    Automatic classification of text documents has become an important research issue now days. Properclassification of text documents requires information retrieval, machine learning and Natural languageprocessing (NLP) techniques. Our aim is to focus on important approaches to automatic textclassification based on machine learning techniques viz. supervised, unsupervised and semi supervised.In this paper we present a review of various text classification approaches under machine learningparadig...

  11. Learn Objective-C for Java Developers

    CERN Document Server

    Bucanek, James

    2009-01-01

    Learn Objective-C for Java Developers will guide experienced Java developers into the world of Objective-C. It will show them how to take their existing language knowledge and design patterns and transfer that experience to Objective-C and the Cocoa runtime library. This is the express train to productivity for every Java developer who dreamt of developing for Mac OS X or iPhone, but felt that Objective-C was too intimidating. So hop on and enjoy the ride!

  12. Learning Faster by Discovering and Exploiting Object Similarities

    Directory of Open Access Journals (Sweden)

    Tadej Janež

    2013-03-01

    Full Text Available In this paper we explore the question: “Is it possible to speed up the learning process of an autonomous agent by performing experiments in a more complex environment (i.e., an environment with a greater number of different objects?” To this end, we use a simple robotic domain, where the robot has to learn a qualitative model predicting the change in the robot's distance to an object. To quantify the environment's complexity, we defined cardinal complexity as the number of objects in the robot's world, and behavioural complexity as the number of objects' distinct behaviours. We propose Error reduction merging (ERM, a new learning method that automatically discovers similarities in the structure of the agent's environment. ERM identifies different types of objects solely from the data measured and merges the observations of objects that behave in the same or similar way in order to speed up the agent's learning. We performed a series of experiments in worlds of increasing complexity. The results in our simple domain indicate that ERM was capable of discovering structural similarities in the data which indeed made the learning faster, clearly superior to conventional learning. This observed trend occurred with various machine learning algorithms used inside the ERM method.

  13. OBJECTIVES AND PROCESSES OF SECOND LANGUAGE LEARNING.

    Science.gov (United States)

    SIZEMORE, MAMIE

    THE OBJECTIVES OF SECOND LANGUAGE TEACHING, AND SPECIFIC DIRECTIONS FOR PRESENTING AND DRILLING STRUCTURES BY THE USE OF CERTAIN GESTURES, WERE PRESENTED. RECOMMENDATIONS FOR CONCENTRATING EFFORTS ON THE ESSENTIALS OF LANGUAGE LEARNING REVOLVED AROUND AN EMPHASIS ON THE TEACHING OF THE LANGUAGE ITSELF RATHER THAN ABOUT ITS HISTORY, VOCABULARY,…

  14. Learning in Organizations - an Object Relations Perspective

    DEFF Research Database (Denmark)

    Andersen, Anders Siig

    Learning in organizations – an object relations perspective As a researcher with a primary interest in the study of learning environments in organizations I have conducted a number of empirical research projects primarily concerning work places in the state sector. The aim of the research has been...... of organizations as learning environments for the employees. Theoretically I draw on object relations theory. Within this tradition the theoretical point of departure is twofold: the study of work conditions in hospitals carried out by Menzies (1975) and Hinschelwood & Skogstad (2000). With regard to the first...... positive and negative impact do they have with respect to the staff itself? With regard to Hinschelwood & Skogstad (2000) they are introduced to further develop and contrast Menzies’ theoretical ideas. Instead of only emphasizing the connection between the work organization and the defence techniques...

  15. Learning object repositories as knowledge management systems

    Directory of Open Access Journals (Sweden)

    Demetrios G. Sampson

    2013-06-01

    Full Text Available Over the past years, a number of international initiatives that recognize the importance of sharing and reusing digital educational resources among educational communities through the use of Learning Object Repositories (LORs have emerged. Typically, these initiatives focus on collecting digital educational resources that are offered by their creators for open access and potential reuse. Nevertheless, most of the existing LORs are designed more as digital repositories, rather than as Knowledge Management Systems (KMS. By exploiting KMSs functionalities in LORs would bare the potential to support the organization and sharing of educational communities’ explicit knowledge (depicted in digital educational resources constructed by teachers and/or instructional designers and tacit knowledge (depicted in teachers’ and students’ experiences and interactions of using digital educational resources available in LORs. Within this context, in this paper we study the design and the implementation of fourteen operating LORs from the KMSs’ perspective, so as to identify additional functionalities that can support the management of educational communities’ explicit and tacit knowledge. Thus, we propose a list of essential LORs’ functionalities, which aim to facilitate the organization and sharing of educational communities’ knowledge. Finally, we present the added value of these functionalities by identifying their importance towards addressing the current demands of web-facilitated educational communities, as well as the knowledge management activities that they execute.

  16. Towards a semantic learning model fostering learning object reusability

    OpenAIRE

    Fernandes , Emmanuel; Madhour , Hend; Wentland Forte , Maia; Miniaoui , Sami

    2005-01-01

    We try in this paper to propose a domain model for both author's and learner's needs concerning learning objects reuse. First of all, we present four key criteria for an efficient authoring tool: adaptive level of granularity, flexibility, integration and interoperability. Secondly, we introduce and describe our six-level Semantic Learning Model (SLM) designed to facilitate multi-level reuse of learning materials and search by defining a multi-layer model for metadata. Finally, after mapping ...

  17. I learning object: la condivisione dei materiali didattici come naturale evoluzione del web

    Directory of Open Access Journals (Sweden)

    Corrado Petrucco

    2004-01-01

    Full Text Available Discussion of Learning Objects (LO and sharing of educational materials. In addition to the standards that exist today, some issues are dealt with the emergence of these new objects of learning.

  18. Learning history by composing synthesis texts: Effects of an instructional programme on learning, reading and writing processes, and text quality

    NARCIS (Netherlands)

    Martínez, I.; Mateos, M.; Martín, E.; Rijlaarsdam, G.

    2015-01-01

    The aim of the present study was to improve learning from texts via strategies that train students how to process synthesis texts. Processing such texts requires goal-oriented interaction between reading and writing activities. The participants were 62 sixth-grade students, 33 in the experimental

  19. Learning attention for historical text normalization by learning to pronounce

    DEFF Research Database (Denmark)

    Bollmann, Marcel; Bingel, Joachim; Søgaard, Anders

    2017-01-01

    Automated processing of historical texts often relies on pre-normalization to modern word forms. Training encoder-decoder architectures to solve such problems typically requires a lot of training data, which is not available for the named task. We address this problem by using several novel encoder...

  20. Learning object for teacher training aimed to develop communication skills

    Directory of Open Access Journals (Sweden)

    Norma Esmeralda RODRÍGUEZ RAMÍREZ

    2014-06-01

    Full Text Available This article presents the results and reflections obtained across a research aimed to analyze the quality criteria of an opened learning object oriented to develop communication skills in order to be able to report and validate it according to its content, pedagogic structure, technological structure, graphical and textual language and usability to teacher training, in order to base it theoretically, pedagogically and technologically. The research question was: Which are the quality criteria that a learning object aimed to develop communication skills must cover? Under a quantitative approach, there were electronic questionnaires applied to: 34 Technological University teachers, eight experts about of communicative competence, teaching, technology and graphic design. The results indicated that some of the quality criteria of learning object are: the effective managing of the learning content, the balanced composition of his pedagogic structure, the technological structure efficiency and the proper managing of graphical and textual language.

  1. How Well can We Learn Interpretable Entity Types from Text?

    DEFF Research Database (Denmark)

    Hovy, Dirk

    2014-01-01

    We investigate a largely unsupervised approach to learning interpretable, domain-specific entity types from unlabeled text. It assumes that any common noun in a domain can function as potential entity type, and uses those nouns as hidden variables in a HMM. To constrain training, it extracts co......-occurrence dictionaries of entities and common nouns from the data. We evaluate the learned types by measuring their prediction accuracy for verb arguments in several domains. The results suggest that it is possible to learn domain-specific entity types from unlabeled data. We show significant improvements over...

  2. Students’ Views on Different Learning Objects Types

    DEFF Research Database (Denmark)

    Natsis, Antonios; Hormova, Hara; Mikropoulos, Tassos

    2014-01-01

    of different type: an educational game, a dynamic simulation and a digital concept map. The basic difference among these three LOs is the fact that both dynamic simulation and concept map are lacking game-like characteristics. The educational game has as a learning goal to familiarize students......The paper attempts to compare students’ views on three different Learning Objects (LOs), also known as Web-Based Learning Tools (WBLTs), which are used for educational purposes aiming at natural disaster readiness. Following an iterative development process, 100 LOs of various types are being...... they will be protected during the earthquake. The educational game comprises of 9 levels of ascending difficulty that have to be completed so as the game to be ended. The dynamic simulation aims to familiarize students with the causes of fog. In that context, they move temperature, wind and humidity bars and thus...

  3. Intelligent Discovery for Learning Objects Using Semantic Web Technologies

    Science.gov (United States)

    Hsu, I-Ching

    2012-01-01

    The concept of learning objects has been applied in the e-learning field to promote the accessibility, reusability, and interoperability of learning content. Learning Object Metadata (LOM) was developed to achieve these goals by describing learning objects in order to provide meaningful metadata. Unfortunately, the conventional LOM lacks the…

  4. Checklist for Evaluating SREB-SCORE Learning Objects

    Science.gov (United States)

    Southern Regional Education Board (SREB), 2007

    2007-01-01

    This checklist is based on "Evaluation Criteria for SREB-SCORE Learning Objects" and is designed to help schools and colleges determine the quality and effectiveness of learning objects. It is suggested that each learning object be rated to the extent to which it meets the criteria and the SREB-SCORE definition of a learning object. A learning…

  5. The development of a National set of Physiology learning objectives ...

    African Journals Online (AJOL)

    International Journal of Medicine and Health Development ... engagement that can be utilized to design a national set of learning objectives towards improving learning ... Key words: Learning objectives, Nigeria, Medical education, curriculum ...

  6. Can Music Foster Learning – Effects of Different Text Modalities on Learning and Information Retrieval

    OpenAIRE

    Lehmann, Janina A. M.; Seufert, Tina

    2018-01-01

    This study investigates the possibilities of fostering learning based on differences in recall and comprehension after learning with texts which were presented in one of three modalities: either in a spoken, written, or sung version. All three texts differ regarding their processing, especially when considering working memory. Overall, we assume the best recall performance after learning with the written text and the best comprehension performance after learning with the sung text, respective...

  7. 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...

  8. Supporting Learning from Illustrated Texts: Conceptualizing and Evaluating a Learning Strategy

    Science.gov (United States)

    Schlag, Sabine; Ploetzner, Rolf

    2011-01-01

    Texts and pictures are often combined in order to improve learning. Many students, however, have difficulty to appropriately process text-picture combinations. We have thus conceptualized a learning strategy which supports learning from illustrated texts. By inducing the processes of information selection, organization, integration, and…

  9. Can Questions Facilitate Learning from Illustrated Science Texts?

    Science.gov (United States)

    Iding, Marie K.

    1997-01-01

    Examines the effectiveness of using questions to facilitate processing of diagrams in science texts. Investigates three different elements in experiments on college students. Finds that questions about illustrations do not facilitate learning. Discusses findings with reference to cognitive load theory, the dual coding perspective, and the…

  10. Learning Spatial Object Localization from Vision on a Humanoid Robot

    Directory of Open Access Journals (Sweden)

    Jürgen Leitner

    2012-12-01

    Full Text Available We present a combined machine learning and computer vision approach for robots to localize objects. It allows our iCub humanoid to quickly learn to provide accurate 3D position estimates (in the centimetre range of objects seen. Biologically inspired approaches, such as Artificial Neural Networks (ANN and Genetic Programming (GP, are trained to provide these position estimates using the two cameras and the joint encoder readings. No camera calibration or explicit knowledge of the robot's kinematic model is needed. We find that ANN and GP are not just faster and have lower complexity than traditional techniques, but also learn without the need for extensive calibration procedures. In addition, the approach is localizing objects robustly, when placed in the robot's workspace at arbitrary positions, even while the robot is moving its torso, head and eyes.

  11. Mere exposure alters category learning of novel objects.

    Science.gov (United States)

    Folstein, Jonathan R; Gauthier, Isabel; Palmeri, Thomas J

    2010-01-01

    We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.

  12. Event Recognition Based on Deep Learning in Chinese Texts.

    Directory of Open Access Journals (Sweden)

    Yajun Zhang

    Full Text Available Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM. Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN, then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

  13. Dynamic Learning Objects to Teach Java Programming Language

    Science.gov (United States)

    Narasimhamurthy, Uma; Al Shawkani, Khuloud

    2010-01-01

    This article describes a model for teaching Java Programming Language through Dynamic Learning Objects. The design of the learning objects was based on effective learning design principles to help students learn the complex topic of Java Programming. Visualization was also used to facilitate the learning of the concepts. (Contains 1 figure and 2…

  14. Deep Learning through Reusable Learning Objects in an MBA Program

    Science.gov (United States)

    Rufer, Rosalyn; Adams, Ruifang Hope

    2013-01-01

    It has well been established that it is important to be able to leverage any organization's processes and core competencies to sustain its competitive advantage. Thus, one learning objective of an online MBA is to teach students how to apply the VRIO (value, rarity, inimitable, operationalized) model, developed by Barney and Hesterly (2006), in…

  15. Personalised Learning Object System Based on Self-Regulated Learning Theories

    Directory of Open Access Journals (Sweden)

    Ali Alharbi

    2014-06-01

    Full Text Available Self-regulated learning has become an important construct in education research in the last few years. Selfregulated learning in its simple form is the learner’s ability to monitor and control the learning process. There is increasing research in the literature on how to support students become more self-regulated learners. However, the advancement in the information technology has led to paradigm changes in the design and development of educational content. The concept of learning object instructional technology has emerged as a result of this shift in educational technology paradigms. This paper presents the results of a study that investigated the potential educational effectiveness of a pedagogical framework based on the self-regulated learning theories to support the design of learning object systems to help computer science students. A prototype learning object system was developed based on the contemporary research on self-regulated learning. The system was educationally evaluated in a quasi-experimental study over two semesters in a core programming languages concepts course. The evaluation revealed that a learning object system that takes into consideration contemporary research on self-regulated learning can be an effective learning environment to support computer science education.

  16. Development and assessment of learning objects about intramuscular medication administration

    Directory of Open Access Journals (Sweden)

    Lilian Mayumi Chinen Tamashiro

    2014-10-01

    Full Text Available OBJECTIVES: to develop and assess a learning object about intramuscular medication administration for nursing undergraduates and nurses.METHOD: a random, intentional and non-probabilistic sample was selected of nurses from a Brazilian social network of nursing and students from the Undergraduate Program at the University of São Paulo School of Nursing to serve as research subjects and assess the object.RESULTS: the participants, 8 nurses and 8 students, studied the object and answered an assessment instrument that included the following criteria: educational aspects (relevance of the theme, objectives and texts/hypertexts, interface of the environment (navigation, accessibility and screen design and didactic resources (interactivity and presentation of resources. In total, 128 significant answers were obtained, 124 (97% of which were positive, assessed as excellent and satisfactory, considered as a flexible, dynamic, objective resources that is appropriate to the nursing learning process.CONCLUSION: the educational technology shows a clear and easily understandable language and the teaching method could be applied in other themes, contributing to the education and training of nursing professionals, positively affecting nursing teaching, stimulating the knowledge, autonomous and independent learning, aligned with the new professional education requirements.

  17. Constraints on Perceptual Learning: Objects and Dimensions.

    Science.gov (United States)

    Bedford, Felice L.

    1995-01-01

    Addresses two questions that may be unique to perceptual learning: What are the circumstances that produce learning? and What is the content of learning? Suggests a critical principle for each question. Provides a discussion of perceptual learning theory, how learning occurs, and what gets learned. Includes a 121-item bibliography. (DR)

  18. The effect of graphic organizers on subjective and objective comprehension of a health education text.

    Science.gov (United States)

    Kools, Marieke; van de Wiel, Margaretha W J; Ruiter, Robert A C; Crüts, Anica; Kok, Gerjo

    2006-12-01

    This study examined the effect of graphic organizers on the comprehension of a health education brochure text and compared subjective with objective comprehension measures. Graphic organizers are graphical depictions of relations among concepts in a text. Participants read a brochure text about asthma with and without these organizers, and subjective and objective text comprehension was measured. It was found that graphic organizers had effects on four levels of objective comprehension as indicated by open comprehension questions. However, on the subjective comprehension measure using Likert-type scales, the groups with and without graphic organizers did not differ from each other. It is concluded that health education texts could benefit from relatively simple techniques to increase comprehension. Furthermore, in developing health education materials, comprehension should be measured objectively.

  19. Learning How to Write an Academic Text: The Effect of Instructional Method and Reflection on Text Quality

    Science.gov (United States)

    van der Loo, Janneke; Krahmer, Emiel; van Amelsvoort, Marije

    2016-01-01

    In this paper we present preliminary results on a study on the effect of instructional method (observational learning and learning by doing) and reflection (yes or no) on academic text quality and self-efficacy beliefs. 56 undergraduate students were assigned to either an observational learning or learning-by-doing condition, with or without…

  20. Building a Smart E-Portfolio Platform for Optimal E-Learning Objects Acquisition

    Directory of Open Access Journals (Sweden)

    Chih-Kun Ke

    2013-01-01

    Full Text Available In modern education, an e-portfolio platform helps students in acquiring e-learning objects in a learning activity. Quality is an important consideration in evaluating the desirable e-learning object. Finding a means of determining a high quality e-learning object from a large number of candidate e-learning objects is an important requirement. To assist student learning in a modern e-portfolio platform, this work proposed an optimal selection approach determining a reasonable e-learning object from various candidate e-learning objects. An optimal selection approach which uses advanced information techniques is proposed. Each e-learning object undergoes a formalization process. An Information Retrieval (IR technique extracts and analyses key concepts from the student’s previous learning contexts. A context-based utility model computes the expected utility values of various e-learning objects based on the extracted key concepts. The expected utility values of e-learning objects are used in a multicriteria decision analysis to determine the optimal selection order of the candidate e-learning objects. The main contribution of this work is the demonstration of an effective e-learning object selection method which is easy to implement within an e-portfolio platform and which makes it smarter.

  1. Can Music Foster Learning – Effects of Different Text Modalities on Learning and Information Retrieval

    Directory of Open Access Journals (Sweden)

    Janina A. M. Lehmann

    2018-01-01

    Full Text Available This study investigates the possibilities of fostering learning based on differences in recall and comprehension after learning with texts which were presented in one of three modalities: either in a spoken, written, or sung version. All three texts differ regarding their processing, especially when considering working memory. Overall, we assume the best recall performance after learning with the written text and the best comprehension performance after learning with the sung text, respectively, compared to both other text modalities. We also analyzed whether the melody of the sung material functions as a mnemonic aid for the learners in the sung text condition. If melody and text of the sung version are closely linked, presentation of the melody during the post-test phase could foster text retrieval. 108 students either learned from a sung text performed by a professional singer, a printed text, or the same text read out loud. Half of the participants worked on the post-test while listening to the melody used for the musical learning material and the other half did not listen to a melody. The written learning modality led to significantly better recall than with the spoken (d = 0.97 or sung text (d = 0.78. However, comprehension after learning with the sung modality was significantly superior compared to when learning with the written learning modality (d = 0.40. Reading leads to more focus on details, which is required to answer recall questions, while listening fosters a general understanding of the text, leading to higher levels of comprehension. Listening to the melody during the post-test phase negatively affected comprehension, irrespective of the modality during the learning phase. This can be explained by the seductive detail effect, as listening to the melody during the post-test phase may distract learners from their main task. In closing, theoretical and practical implications are discussed.

  2. Can Music Foster Learning - Effects of Different Text Modalities on Learning and Information Retrieval.

    Science.gov (United States)

    Lehmann, Janina A M; Seufert, Tina

    2017-01-01

    This study investigates the possibilities of fostering learning based on differences in recall and comprehension after learning with texts which were presented in one of three modalities: either in a spoken, written, or sung version. All three texts differ regarding their processing, especially when considering working memory. Overall, we assume the best recall performance after learning with the written text and the best comprehension performance after learning with the sung text, respectively, compared to both other text modalities. We also analyzed whether the melody of the sung material functions as a mnemonic aid for the learners in the sung text condition. If melody and text of the sung version are closely linked, presentation of the melody during the post-test phase could foster text retrieval. 108 students either learned from a sung text performed by a professional singer, a printed text, or the same text read out loud. Half of the participants worked on the post-test while listening to the melody used for the musical learning material and the other half did not listen to a melody. The written learning modality led to significantly better recall than with the spoken ( d = 0.97) or sung text ( d = 0.78). However, comprehension after learning with the sung modality was significantly superior compared to when learning with the written learning modality ( d = 0.40). Reading leads to more focus on details, which is required to answer recall questions, while listening fosters a general understanding of the text, leading to higher levels of comprehension. Listening to the melody during the post-test phase negatively affected comprehension, irrespective of the modality during the learning phase. This can be explained by the seductive detail effect, as listening to the melody during the post-test phase may distract learners from their main task. In closing, theoretical and practical implications are discussed.

  3. Patterns of Learning Object Reuse in the Connexions Repository

    Science.gov (United States)

    Duncan, S. M.

    2009-01-01

    Since the term "learning object" was first published, there has been either an explicit or implicit expectation of reuse. There has also been a lot of speculation about why learning objects are, or are not, reused. This study quantitatively examined the actual amount and type of learning object use, to include reuse, modification, and translation,…

  4. Experiments on Supervised Learning Algorithms for Text Categorization

    Science.gov (United States)

    Namburu, Setu Madhavi; Tu, Haiying; Luo, Jianhui; Pattipati, Krishna R.

    2005-01-01

    Modern information society is facing the challenge of handling massive volume of online documents, news, intelligence reports, and so on. How to use the information accurately and in a timely manner becomes a major concern in many areas. While the general information may also include images and voice, we focus on the categorization of text data in this paper. We provide a brief overview of the information processing flow for text categorization, and discuss two supervised learning algorithms, viz., support vector machines (SVM) and partial least squares (PLS), which have been successfully applied in other domains, e.g., fault diagnosis [9]. While SVM has been well explored for binary classification and was reported as an efficient algorithm for text categorization, PLS has not yet been applied to text categorization. Our experiments are conducted on three data sets: Reuter's- 21578 dataset about corporate mergers and data acquisitions (ACQ), WebKB and the 20-Newsgroups. Results show that the performance of PLS is comparable to SVM in text categorization. A major drawback of SVM for multi-class categorization is that it requires a voting scheme based on the results of pair-wise classification. PLS does not have this drawback and could be a better candidate for multi-class text categorization.

  5. Language and Text-to-Speech Technologies for Highly Accessible Language & Culture Learning

    Directory of Open Access Journals (Sweden)

    Anouk Gelan

    2011-06-01

    Full Text Available This contribution presents the results of the “Speech technology integrated learning modules for Intercultural Dialogue” project. The project objective was to increase the availability and quality of e-learning opportunities for less widely-used and less taught European languages using a user-friendly and highly accessible learning environment. The integration of new Text-to-Speech developments into web-based authoring software for tutorial CALL had a double goal: on the one hand increase the accessibility of e-learning packages, also for learners having difficulty reading (e.g. dyslexic learners or preferring auditory learning; on the other hand exploiting some didactic possibilities of this technology.

  6. An Investigation on the Correlation of Learner Styles and Learning Objects Characteristics in a Proposed Learning Objects Management Model (LOMM)

    Science.gov (United States)

    Wanapu, Supachanun; Fung, Chun Che; Kerdprasop, Nittaya; Chamnongsri, Nisachol; Niwattanakul, Suphakit

    2016-01-01

    The issues of accessibility, management, storage and organization of Learning Objects (LOs) in education systems are a high priority of the Thai Government. Incorporating personalized learning or learning styles in a learning object management system to improve the accessibility of LOs has been addressed continuously in the Thai education system.…

  7. DEEP LEARNING MODEL FOR BILINGUAL SENTIMENT CLASSIFICATION OF SHORT TEXTS

    Directory of Open Access Journals (Sweden)

    Y. B. Abdullin

    2017-01-01

    Full Text Available Sentiment analysis of short texts such as Twitter messages and comments in news portals is challenging due to the lack of contextual information. We propose a deep neural network model that uses bilingual word embeddings to effectively solve sentiment classification problem for a given pair of languages. We apply our approach to two corpora of two different language pairs: English-Russian and Russian-Kazakh. We show how to train a classifier in one language and predict in another. Our approach achieves 73% accuracy for English and 74% accuracy for Russian. For Kazakh sentiment analysis, we propose a baseline method, that achieves 60% accuracy; and a method to learn bilingual embeddings from a large unlabeled corpus using a bilingual word pairs.

  8. Effects of Text Illustration on Children's Learning of a School Science Topic.

    Science.gov (United States)

    Reid, D. J.; Beveridge, M.

    1986-01-01

    This study of 272 13-year-old science students in England focuses on the effect of varied text and picture content on learning. A criterion-referenced objective items test was used to measure the effect of pictures on students of varying abilities and compare the effectiveness of traditional worksheet presentation and microcomputer presentation.…

  9. A Convergent Participation Model for Evaluation of Learning Objects

    Directory of Open Access Journals (Sweden)

    John Nesbit

    2002-10-01

    Full Text Available The properties that distinguish learning objects from other forms of educational software - global accessibility, metadata standards, finer granularity and reusability - have implications for evaluation. This article proposes a convergent participation model for learning object evaluation in which representatives from stakeholder groups (e.g., students, instructors, subject matter experts, instructional designers, and media developers converge toward more similar descriptions and ratings through a two-stage process supported by online collaboration tools. The article reviews evaluation models that have been applied to educational software and media, considers models for gathering and meta-evaluating individual user reviews that have recently emerged on the Web, and describes the peer review model adopted for the MERLOT repository. The convergent participation model is assessed in relation to other models and with respect to its support for eight goals of learning object evaluation: (1 aid for searching and selecting, (2 guidance for use, (3 formative evaluation, (4 influence on design practices, (5 professional development and student learning, (6 community building, (7 social recognition, and (8 economic exchange.

  10. Personalised learning object based on multi-agent model and learners’ learning styles

    Directory of Open Access Journals (Sweden)

    Noppamas Pukkhem

    2011-09-01

    Full Text Available A multi-agent model is proposed in which learning styles and a word analysis technique to create a learning object recommendation system are used. On the basis of a learning style-based design, a concept map combination model is proposed to filter out unsuitable learning concepts from a given course. Our learner model classifies learners into eight styles and implements compatible computational methods consisting of three recommendations: i non-personalised, ii preferred feature-based, and iii neighbour-based collaborative filtering. The analysis of preference error (PE was performed by comparing the actual preferred learning object with the predicted one. In our experiments, the feature-based recommendation algorithm has the fewest PE.

  11. Mobile Authoring of Open Educational Resources as Reusable Learning Objects

    Directory of Open Access Journals (Sweden)

    Dr Kinshuk

    2013-06-01

    Full Text Available E-learning technologies have allowed authoring and playback of standardized reusable learning objects (RLO for several years. Effective mobile learning requires similar functionality at both design time and runtime. Mobile devices can play RLO using applications like SMILE, mobile access to a learning management system (LMS, or other systems which deploy content to mobile learners (Castillo & Ayala, 2008; Chu, Hwang, & Tseng, 2010; Hsu & Chen, 2010; Nakabayashi, 2009; Zualkernan, Nikkhah, & Al-Sabah, 2009. However, implementations which author content in a mobile context do not typically permit reuse across multiple contexts due to a lack of standardization. Standards based (IMS and SCORM authoring implementations exist for non-mobile platforms (Gonzalez-Barbone & Anido-Rifon, 2008; Griffiths, Beauvoir, Liber, & Barrett-Baxendale, 2009; Téllez, 2010; Yang, Chiu, Tsai, & Wu, 2004. However, this paradigm precludes capturing learning where and when it occurs. Consequently, RLO authored for e-learning lack learner generated content, especially with timely, relevant, and location aware examples.

  12. Deep Learning to Classify Radiology Free-Text Reports.

    Science.gov (United States)

    Chen, Matthew C; Ball, Robyn L; Yang, Lingyao; Moradzadeh, Nathaniel; Chapman, Brian E; Larson, David B; Langlotz, Curtis P; Amrhein, Timothy J; Lungren, Matthew P

    2018-03-01

    Purpose To evaluate the performance of a deep learning convolutional neural network (CNN) model compared with a traditional natural language processing (NLP) model in extracting pulmonary embolism (PE) findings from thoracic computed tomography (CT) reports from two institutions. Materials and Methods Contrast material-enhanced CT examinations of the chest performed between January 1, 1998, and January 1, 2016, were selected. Annotations by two human radiologists were made for three categories: the presence, chronicity, and location of PE. Classification of performance of a CNN model with an unsupervised learning algorithm for obtaining vector representations of words was compared with the open-source application PeFinder. Sensitivity, specificity, accuracy, and F1 scores for both the CNN model and PeFinder in the internal and external validation sets were determined. Results The CNN model demonstrated an accuracy of 99% and an area under the curve value of 0.97. For internal validation report data, the CNN model had a statistically significant larger F1 score (0.938) than did PeFinder (0.867) when classifying findings as either PE positive or PE negative, but no significant difference in sensitivity, specificity, or accuracy was found. For external validation report data, no statistical difference between the performance of the CNN model and PeFinder was found. Conclusion A deep learning CNN model can classify radiology free-text reports with accuracy equivalent to or beyond that of an existing traditional NLP model. © RSNA, 2017 Online supplemental material is available for this article.

  13. Web based Interactive 3D Learning Objects for Learning Management Systems

    Directory of Open Access Journals (Sweden)

    Stefan Hesse

    2012-02-01

    Full Text Available In this paper, we present an approach to create and integrate interactive 3D learning objects of high quality for higher education into a learning management system. The use of these resources allows to visualize topics, such as electro-technical and physical processes in the interior of complex devices. This paper addresses the challenge of combining rich interactivity and adequate realism with 3D exercise material for distance elearning.

  14. Investigating the Use of Text Messages in Mobile Learning

    Science.gov (United States)

    Geng, Gretchen

    2013-01-01

    Nowadays, teaching and learning have been shifted from traditional classrooms to technology-supported learning environment. By offering a convenient, efficient and financially affordable information technology learning environment, mobile learning is a topic that is of considerable interest for education audiences owing to the pervasive nature of…

  15. Learning stoichiometry: A comparison of text and multimedia instructional formats

    Science.gov (United States)

    Evans, Karen L.

    Even after multiple instructional opportunities, first year college chemistry students are often unable to apply stoichiometry knowledge in equilibrium and acid-base chemistry problem solving. Cognitive research findings suggest that for learning to be meaningful, learners need to actively construct their own knowledge by integrating new information into, and reorganizing, their prior understandings. Scaffolded inquiry in which facts, procedures, and principles are introduced as needed within the context of authentic problem solving may provide the practice and encoding opportunities necessary for construction of a memorable and usable knowledge base. The dynamic and interactive capabilities of online technology may facilitate stoichiometry instruction that promotes this meaningful learning. Entering college freshmen were randomly assigned to either a technology-rich or text-only set of cognitively informed stoichiometry review materials. Analysis of posttest scores revealed a significant but small difference in the performance of the two treatment groups, with the technology-rich group having the advantage. Both SAT and gender, however, explained more of the variability in the scores. Analysis of the posttest scores from the technology-rich treatment group revealed that the degree of interaction with the Virtual Lab simulation was significantly related to posttest performance and subsumed any effect of prior knowledge as measured by SAT scores. Future users of the online course should be encouraged to engage with the problem-solving opportunities provided by the Virtual Lab simulation through either explicit instruction and/or implementation of some level of program control within the course's navigational features.

  16. Participative Knowledge Production of Learning Objects for E-Books.

    Science.gov (United States)

    Dodero, Juan Manuel; Aedo, Ignacio; Diaz, Paloma

    2002-01-01

    Defines a learning object as any digital resource that can be reused to support learning and thus considers electronic books as learning objects. Highlights include knowledge management; participative knowledge production, i.e. authoring electronic books by a distributed group of authors; participative knowledge production architecture; and…

  17. Summarize to learn: summarization and visualization of text for ubiquitous learning

    DEFF Research Database (Denmark)

    Chongtay, Rocio; Last, Mark; Verbeke, Mathias

    2013-01-01

    Visualizations can stand in many relations to texts – and, as research into learning with pictures has shown, they can become particularly valuable when they transform the contents of the text (rather than just duplicate its message or structure it). But what kinds of transformations can...... be particularly helpful in the learning process? In this paper, we argue that interacting with, and creating, summaries of texts is a key transformation technique, and we investigate how textual and graphical summarization approaches, as well as automatic and manual summarization, can complement one another...... to support effective learning....

  18. Learning Semantic Tags from Big Data for Clinical Text Representation.

    Science.gov (United States)

    Li, Yanpeng; Liu, Hongfang

    2015-01-01

    In clinical text mining, it is one of the biggest challenges to represent medical terminologies and n-gram terms in sparse medical reports using either supervised or unsupervised methods. Addressing this issue, we propose a novel method for word and n-gram representation at semantic level. We first represent each word by its distance with a set of reference features calculated by reference distance estimator (RDE) learned from labeled and unlabeled data, and then generate new features using simple techniques of discretization, random sampling and merging. The new features are a set of binary rules that can be interpreted as semantic tags derived from word and n-grams. We show that the new features significantly outperform classical bag-of-words and n-grams in the task of heart disease risk factor extraction in i2b2 2014 challenge. It is promising to see that semantics tags can be used to replace the original text entirely with even better prediction performance as well as derive new rules beyond lexical level.

  19. The Game Object Model and expansive learning: Creation ...

    African Journals Online (AJOL)

    The Game Object Model and expansive learning: Creation, instantiation, ... The aim of the paper is to develop insights into the design, integration, evaluation and use of video games in learning and teaching. ... AJOL African Journals Online.

  20. Learning User Preferences for Sets of Objects

    Science.gov (United States)

    desJardins, Marie; Eaton, Eric; Wagstaff, Kiri L.

    2006-01-01

    Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of items. Our learning method takes as input a collection of positive examples--that is, one or more sets that have been identified by a user as desirable. Kernel density estimation is used to estimate the value function for individual items, and the desired set diversity is estimated from the average set diversity observed in the collection. Since this is a new learning problem, we introduce a new evaluation methodology and evaluate the learning method on two data collections: synthetic blocks-world data and a new real-world music data collection that we have gathered.

  1. Developing Learning Objectives for Accounting Ethics Using Bloom's Taxonomy

    Science.gov (United States)

    Kidwell, Linda A.; Fisher, Dann G.; Braun, Robert L.; Swanson, Diane L.

    2013-01-01

    The purpose of our article is to offer a set of core knowledge learning objectives for accounting ethics education. Using Bloom's taxonomy of educational objectives, we develop learning objectives in six content areas: codes of ethical conduct, corporate governance, the accounting profession, moral development, classical ethics theories, and…

  2. Utopia2000: An Online Learning-Object Management Tool.

    Science.gov (United States)

    Aspillaga, Macarena

    2002-01-01

    Describes Utopia2002, a database that contains learning objects that enables faculty to design and develop interactive Web-based instruction. Topics include advanced distributed learning; sharable content objects (SCOs) and sharable content object reference model (SCORM); instructional systems design process; templates; and quality assurance. (LRW)

  3. Using machine learning to disentangle homonyms in large text corpora.

    Science.gov (United States)

    Roll, Uri; Correia, Ricardo A; Berger-Tal, Oded

    2018-06-01

    Systematic reviews are an increasingly popular decision-making tool that provides an unbiased summary of evidence to support conservation action. These reviews bridge the gap between researchers and managers by presenting a comprehensive overview of all studies relating to a particular topic and identify specifically where and under which conditions an effect is present. However, several technical challenges can severely hinder the feasibility and applicability of systematic reviews, for example, homonyms (terms that share spelling but differ in meaning). Homonyms add noise to search results and cannot be easily identified or removed. We developed a semiautomated approach that can aid in the classification of homonyms among narratives. We used a combination of automated content analysis and artificial neural networks to quickly and accurately sift through large corpora of academic texts and classify them to distinct topics. As an example, we explored the use of the word reintroduction in academic texts. Reintroduction is used within the conservation context to indicate the release of organisms to their former native habitat; however, a Web of Science search for this word returned thousands of publications in which the term has other meanings and contexts. Using our method, we automatically classified a sample of 3000 of these publications with over 99% accuracy, relative to a manual classification. Our approach can be used easily with other homonyms and can greatly facilitate systematic reviews or similar work in which homonyms hinder the harnessing of large text corpora. Beyond homonyms we see great promise in combining automated content analysis and machine-learning methods to handle and screen big data for relevant information in conservation science. © 2017 Society for Conservation Biology.

  4. Active learning for clinical text classification: is it better than random sampling?

    Science.gov (United States)

    Figueroa, Rosa L; Ngo, Long H; Goryachev, Sergey; Wiechmann, Eduardo P

    2012-01-01

    Objective This study explores active learning algorithms as a way to reduce the requirements for large training sets in medical text classification tasks. Design Three existing active learning algorithms (distance-based (DIST), diversity-based (DIV), and a combination of both (CMB)) were used to classify text from five datasets. The performance of these algorithms was compared to that of passive learning on the five datasets. We then conducted a novel investigation of the interaction between dataset characteristics and the performance results. Measurements Classification accuracy and area under receiver operating characteristics (ROC) curves for each algorithm at different sample sizes were generated. The performance of active learning algorithms was compared with that of passive learning using a weighted mean of paired differences. To determine why the performance varies on different datasets, we measured the diversity and uncertainty of each dataset using relative entropy and correlated the results with the performance differences. Results The DIST and CMB algorithms performed better than passive learning. With a statistical significance level set at 0.05, DIST outperformed passive learning in all five datasets, while CMB was found to be better than passive learning in four datasets. We found strong correlations between the dataset diversity and the DIV performance, as well as the dataset uncertainty and the performance of the DIST algorithm. Conclusion For medical text classification, appropriate active learning algorithms can yield performance comparable to that of passive learning with considerably smaller training sets. In particular, our results suggest that DIV performs better on data with higher diversity and DIST on data with lower uncertainty. PMID:22707743

  5. Learning objects as coadjuvants in the human physiology teaching-learning process

    Directory of Open Access Journals (Sweden)

    Marcus Vinícius Lara

    2014-08-01

    Full Text Available The use of Information and Communication Technologies (ICTs in the academic environment of biomedical area has gained much importance, both for their ability to complement the understanding of the subject obtained in the classroom, is the ease of access, or makes more pleasure the learning process, since these tools are present in everyday of the students and use a simple language. Considering that, this study aims to report the experience of building learning objects in human physiology as a tool for learning facilitation, and discuss the impact of this teaching methodology

  6. 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…

  7. Indexing, Query Processing, and Clustering of Spatio-Temporal Text Objects

    DEFF Research Database (Denmark)

    Skovsgaard, Anders

    With the increasing mobile use of the web from geo-positioned devices, the Internet is increasingly acquiring a spatial aspect, with still more types of content being geo-tagged. As a result of this development, a wide range of location-aware queries and applications have emerged. The large amounts...... of data available coupled with the increasing number of location-aware queries calls for efficient indexing and query processing techniques. This dissertation investigates how to manage geo-tagged text content to support these workloads in three specific areas: (i) grouping of spatio-textual objects, (ii......, the grouping of spatio-textual objects is done without considering query locations, and a clustering approach is proposed that takes into account both the spatial and textual attributes of the objects. The technique expands clusters based on a proposed quality function that enables clusters of arbitrary shape...

  8. Event Recognition Based on Deep Learning in Chinese Texts.

    Science.gov (United States)

    Zhang, Yajun; Liu, Zongtian; Zhou, Wen

    2016-01-01

    Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

  9. Liberating Learning Object Design from the Learning Style of Student Instructional Designers

    Science.gov (United States)

    Akpinar, Yavuz

    2007-01-01

    Learning objects are a new form of learning resource, and the design of these digital environments has many facets. To investigate senior instructional design students' use of reflection tools in designing learning objects, a series of studies was conducted using the Reflective Action Instructional Design and Learning Object Review Instrument…

  10. Form over Substance: Learning Objectives in the Business Core

    Science.gov (United States)

    Stokes, Leonard; Rosetti, Joseph L.; King, Michelle

    2010-01-01

    While members of the business faculty community have been advocating active learning in the classroom, it appears that textbooks encourage learning from a passive perspective. A review of learning objectives from 16 textbooks used in Financial Accounting, Managerial Accounting, Finance, and Marketing demonstrates a focus on basically the same set…

  11. Things to Say: Future Applications of Smart Objects in Learning

    Science.gov (United States)

    Preis, Kevin

    2008-01-01

    Smart object technology allows users to know something in real time about the physical objects in their presence. Each object, from cereal boxes to skyscrapers, becomes a source of information with which users can interact. Through a series of usage scenarios, the article explores the potential impact of smart objects on learning in formal and…

  12. Learning Object-Orientation through ICT-mediated Apprenticeship

    DEFF Research Database (Denmark)

    Fjuk, A.; Berge, O.; Bennedsen, J.

    2004-01-01

    In this paper, we show how sociocultural theories inform the design of a course in object-oriented programming. An essential learning objective within this philosophy is the programming processes as such. To move toward this learning goal, the course design incorporates a combination of the so...

  13. Searching for and Positioning of Contextualized Learning Objects

    Science.gov (United States)

    Baldiris, Silvia; Graf, Sabine; Fabregat, Ramon; Mendez, Nestor Dario Duque

    2012-01-01

    Learning object economies are marketplaces for the sharing and reuse of learning objects (LO). There are many motivations for stimulating the development of the LO economy. The main reason is the possibility of providing the right content, at the right time, to the right learner according to adequate quality standards in the context of a lifelong…

  14. Guide to good practices for developing learning objectives. DOE guideline

    Energy Technology Data Exchange (ETDEWEB)

    1992-07-01

    This guide to good practices provides information and guidance on the types of, and the development of learning objectives in performance-based training system at reactor and nonreactor nuclear facilities. Contractors are encouraged to consider this guidance as a reference when developing new learning objectives or refining existing ones. Training managers, designers, developers, and instructors are the intended audiences.

  15. Guide to good practices for developing learning objectives. DOE Handbook

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1992-07-01

    This guide to good practices provides information and guidance on the types of and development of learning objectives in a systematic approach to training program. This document can serve as a reference during the development of new learning objectives or refinement of existing ones.

  16. Model of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System

    Directory of Open Access Journals (Sweden)

    Ronaldo Lima Rocha Campos

    2012-07-01

    Full Text Available This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.

  17. Sparse Machine Learning Methods for Understanding Large Text Corpora

    Data.gov (United States)

    National Aeronautics and Space Administration — Sparse machine learning has recently emerged as powerful tool to obtain models of high-dimensional data with high degree of interpretability, at low computational...

  18. Learning Objectives for Master's theses at DTU Management Engineering

    DEFF Research Database (Denmark)

    Hansen, Claus Thorp; Rasmussen, Birgitte; Hinz, Hector Nøhr

    2010-01-01

    , different. The DTU Study Handbook states that:”Learning objectives are an integrated part of the supervision”, which provides you with the opportunity – naturally in cooperation with your supervisor – to formulate learning objectives for your Master's thesis. There are at least three good reasons for being...... that you formulate precise and useful learning objectives for your Master's thesis. These notes of inspiration have been written to help you do exactly this. The notes discuss the requirements for the learning objectives, examples of learning objectives and the assessment criteria defined by DTU Management...... Engineering as well as, but not least, some useful things to remember concerning your submission and the assessment of the Master's thesis. DTU Management Engineering Claus Thorp Hansen Birgitte Rasmussen Hector Nøhr Hinz © DTU Management Engineering 2010 ISBN nr. 978-87-90855-94-7 This document...

  19. Assessing Complex Learning Objectives through Analytics

    Science.gov (United States)

    Horodyskyj, L.; Mead, C.; Buxner, S.; Semken, S. C.; Anbar, A. D.

    2016-12-01

    A significant obstacle to improving the quality of education is the lack of easy-to-use assessments of higher-order thinking. Most existing assessments focus on recall and understanding questions, which demonstrate lower-order thinking. Traditionally, higher-order thinking is assessed with practical tests and written responses, which are time-consuming to analyze and are not easily scalable. Computer-based learning environments offer the possibility of assessing such learning outcomes based on analysis of students' actions within an adaptive learning environment. Our fully online introductory science course, Habitable Worlds, uses an intelligent tutoring system that collects and responds to a range of behavioral data, including actions within the keystone project. This central project is a summative, game-like experience in which students synthesize and apply what they have learned throughout the course to identify and characterize a habitable planet from among hundreds of stars. Student performance is graded based on completion and accuracy, but two additional properties can be utilized to gauge higher-order thinking: (1) how efficient a student is with the virtual currency within the project and (2) how many of the optional milestones a student reached. In the project, students can use the currency to check their work and "unlock" convenience features. High-achieving students spend close to the minimum amount required to reach these goals, indicating a high-level of concept mastery and efficient methodology. Average students spend more, indicating effort, but lower mastery. Low-achieving students were more likely to spend very little, which indicates low effort. Differences on these metrics were statistically significant between all three of these populations. We interpret this as evidence that high-achieving students develop and apply efficient problem-solving skills as compared to lower-achieving student who use more brute-force approaches.

  20. Text-based Learning (Tbl) to Activate Adult Efl Learners in Learning English: a Narrative Inquiry

    OpenAIRE

    Iftanti, Erna

    2017-01-01

    In response to the fact that college students complain on their unsuccessful story of their EFL learning experience such as the limited number of vocabulary, English Grammar confusion, low competence of English language skills, this article explores an alternative effective way of helping them to improve their English through Text-Based Learning (TBL) model. This article is then intended to narrate the implementation of TBL to teach English for college students of non English Department of Po...

  1. PARTICULARITIES OF EDUCATIONAL OBJECTS IN COMPUTER-ASSISTED LEARNING FOR PERSONS WITH DISABILITIES

    Directory of Open Access Journals (Sweden)

    Narcisa ISĂILĂ

    2010-12-01

    Full Text Available The current trend in computer-assisted learning is the creation of reusable learning objects. They can be used independently or can be coupled to make lessons that best fit the users' learning needs. From this perspective, the specific of learning objects for people with disabilities is to ensure accessibility and usability. Using standards in the process of creating learning objects provide flexibility in achieving lessons, thus being helpful for educational content creators (teachers. Metadata have an essential role in achieving interoperability and provide standardized information about the learning objects, allowing the searching, accessing and their finding. The compliance of eLearning standards ensures the compatibility and portability of materials from one system to another, which reduces the time and cost of development.

  2. Learning Object Metadata in a Web-Based Learning Environment

    NARCIS (Netherlands)

    Avgeriou, Paris; Koutoumanos, Anastasios; Retalis, Symeon; Papaspyrou, Nikolaos

    2000-01-01

    The plethora and variance of learning resources embedded in modern web-based learning environments require a mechanism to enable their structured administration. This goal can be achieved by defining metadata on them and constructing a system that manages the metadata in the context of the learning

  3. Learning to Detect Human-Object Interactions

    KAUST Repository

    Chao, Yu-Wei; Liu, Yunfan; Liu, Xieyang; Zeng, Huayi; Deng, Jia

    2017-01-01

    In this paper we study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects. We introduce HICO-DET, a new large benchmark for HOI detection, by augmenting the current HICO classification benchmark with instance annotations. We propose Human-Object Region-based Convolutional Neural Networks (HO-RCNN), a novel DNN-based framework for HOI detection. At the core of our HO-RCNN is the Interaction Pattern, a novel DNN input that characterizes the spatial relations between two bounding boxes. We validate the effectiveness of our HO-RCNN using HICO-DET. Experiments demonstrate that our HO-RCNN, by exploiting human-object spatial relations through Interaction Patterns, significantly improves the performance of HOI detection over baseline approaches.

  4. Learning to Detect Human-Object Interactions

    KAUST Repository

    Chao, Yu-Wei

    2017-02-17

    In this paper we study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that connects them. HOI detection is a fundamental problem in computer vision as it provides semantic information about the interactions among the detected objects. We introduce HICO-DET, a new large benchmark for HOI detection, by augmenting the current HICO classification benchmark with instance annotations. We propose Human-Object Region-based Convolutional Neural Networks (HO-RCNN), a novel DNN-based framework for HOI detection. At the core of our HO-RCNN is the Interaction Pattern, a novel DNN input that characterizes the spatial relations between two bounding boxes. We validate the effectiveness of our HO-RCNN using HICO-DET. Experiments demonstrate that our HO-RCNN, by exploiting human-object spatial relations through Interaction Patterns, significantly improves the performance of HOI detection over baseline approaches.

  5. Digital learning object for diagnostic reasoning in nursing applied to the integumentary system

    Directory of Open Access Journals (Sweden)

    Cecília Passos Vaz da Costa

    Full Text Available Objective: To describe the creation of a digital learning object for diagnostic reasoning in nursing applied to the integumentary system at a public university of Piaui. Method: A methodological study applied to technological production based on the pedagogical framework of problem-based learning. The methodology for creating the learning object observed the stages of analysis, design, development, implementation and evaluation recommended for contextualized instructional design. The revised taxonomy of Bloom was used to list the educational goals. Results: The four modules of the developed learning object were inserted into the educational platform Moodle. The theoretical assumptions allowed the design of an important online resource that promotes effective learning in the scope of nursing education. Conclusion: This study should add value to nursing teaching practices through the use of digital learning objects for teaching diagnostic reasoning applied to skin and skin appendages.

  6. Learning Photometric Invariance for Object Detection

    NARCIS (Netherlands)

    Álvarez, J.M.; Gevers, T.; López, A.M.

    2010-01-01

    Color is a powerful visual cue in many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the imaging conditions that negatively affect the performance of the task at hand. Often, a reflection model (e.g., Lambertian

  7. Localization-Aware Active Learning for Object Detection

    OpenAIRE

    Kao, Chieh-Chi; Lee, Teng-Yok; Sen, Pradeep; Liu, Ming-Yu

    2018-01-01

    Active learning - a class of algorithms that iteratively searches for the most informative samples to include in a training dataset - has been shown to be effective at annotating data for image classification. However, the use of active learning for object detection is still largely unexplored as determining informativeness of an object-location hypothesis is more difficult. In this paper, we address this issue and present two metrics for measuring the informativeness of an object hypothesis,...

  8. Text messages as a learning tool for midwives | Woods | South ...

    African Journals Online (AJOL)

    The use of cell phone text messaging to improve access to continuing ... with 50 of the message recipients, demonstrated that the text messages were well received by ... services, such as the management of HIV-infected children and adults.

  9. Machine learning versus knowledge based classification of legal texts

    NARCIS (Netherlands)

    de Maat, E.; Krabben, K.; Winkels, R.; Winkels, R.G.F.

    2010-01-01

    This paper presents results of an experiment in which we used machine learning (ML) techniques to classify sentences in Dutch legislation. These results are compared to the results of a pattern-based classifier. Overall, the ML classifier performs as accurate (>90%) as the pattern based one, but

  10. A Theoretical Discussion for E-Text Communication in Learning

    Science.gov (United States)

    Lee, Hye-Jung

    2015-01-01

    With the recent development of internet and mobile technology, a new kind of e-text communication is emerging. From messenger chatting, mobile texting, to social networking through Twitter or Facebook, e-text communication is becoming a main communication channel, especially for the younger generation. However, there has not been sufficient…

  11. Object based implicit contextual learning: a study of eye movements.

    Science.gov (United States)

    van Asselen, Marieke; Sampaio, Joana; Pina, Ana; Castelo-Branco, Miguel

    2011-02-01

    Implicit contextual cueing refers to a top-down mechanism in which visual search is facilitated by learned contextual features. In the current study we aimed to investigate the mechanism underlying implicit contextual learning using object information as a contextual cue. Therefore, we measured eye movements during an object-based contextual cueing task. We demonstrated that visual search is facilitated by repeated object information and that this reduction in response times is associated with shorter fixation durations. This indicates that by memorizing associations between objects in our environment we can recognize objects faster, thereby facilitating visual search.

  12. A Framework for the Flexible Content Packaging of Learning Objects and Learning Designs

    Science.gov (United States)

    Lukasiak, Jason; Agostinho, Shirley; Burnett, Ian; Drury, Gerrard; Goodes, Jason; Bennett, Sue; Lockyer, Lori; Harper, Barry

    2004-01-01

    This paper presents a platform-independent method for packaging learning objects and learning designs. The method, entitled a Smart Learning Design Framework, is based on the MPEG-21 standard, and uses IEEE Learning Object Metadata (LOM) to provide bibliographic, technical, and pedagogical descriptors for the retrieval and description of learning…

  13. TEXT-BASED LEARNING (TBL TO ACTIVATE ADULT EFL LEARNERS IN LEARNING ENGLISH: A NARRATIVE INQUIRY

    Directory of Open Access Journals (Sweden)

    Erna Iftanti

    2017-06-01

    Full Text Available In response to the fact that college students complain on their unsuccessful story of their EFL learning experience such as the limited number of vocabulary, English Grammar confusion, low competence of English language skills, this article explores an alternative effective way of helping them to improve their English through Text-Based Learning (TBL model. This article is then intended to narrate the implementation of TBL to teach English for college students of non English Department of Post Graduate Program of State Islamic Institute of Tulungagung, Indonesia. The result of implementing this teaching model proves to be able to not only stimulate joyful learning atmosphere but to attract the students’ active participation during the EFL instructional process as well. This further brings about their better practical understanding on English language skills as their expectation. Therefore, for English lecturers, this model is pedagogically good to be implemented in their English instructional practices.

  14. Science Integrating Learning Objectives: A Cooperative Learning Group Process

    Science.gov (United States)

    Spindler, Matt

    2015-01-01

    The integration of agricultural and science curricular content that capitalizes on natural and inherent connections represents a challenge for secondary agricultural educators. The purpose of this case study was to create information about the employment of Cooperative Learning Groups (CLG) to enhance the science integrating learning objectives…

  15. Hierarchical image segmentation for learning object priors

    Energy Technology Data Exchange (ETDEWEB)

    Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.; Li, Nan [TEMPLE UNIV.

    2010-11-10

    The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

  16. Learners misperceive the benefits of redundant text in multimedia learning.

    Science.gov (United States)

    Fenesi, Barbara; Kim, Joseph A

    2014-01-01

    Research on metacognition has consistently demonstrated that learners fail to endorse instructional designs that produce benefits to memory, and often prefer designs that actually impair comprehension. Unlike previous studies in which learners were only exposed to a single multimedia design, the current study used a within-subjects approach to examine whether exposure to both redundant text and non-redundant text multimedia presentations improved learners' metacognitive judgments about presentation styles that promote better understanding. A redundant text multimedia presentation containing narration paired with verbatim on-screen text (Redundant) was contrasted with two non-redundant text multimedia presentations: (1) narration paired with images and minimal text (Complementary) or (2) narration paired with minimal text (Sparse). Learners watched presentation pairs of either Redundant + Complementary, or Redundant + Sparse. Results demonstrate that Complementary and Sparse presentations produced highest overall performance on the final comprehension assessment, but the Redundant presentation produced highest perceived understanding and engagement ratings. These findings suggest that learners misperceive the benefits of redundant text, even after direct exposure to a non-redundant, effective presentation.

  17. Learning Objects 2: standarts, metadatas, repositories, &LCMS

    Directory of Open Access Journals (Sweden)

    De Giusti, Laura Cristina

    2015-06-01

    Full Text Available La presencia de objetos de aprendizaje ha generado una nueva forma de pensar acerca del contenido de aprendizaje. El contenido deja de ser un medio para la consecución de un objetivo y se convierte en un objeto con entidad propia, susceptible de ser reutilizado. La utilización de objetos de aprendizaje como recurso didáctico requiere nuevos enfoques en el diseño, en la metodología docente y en las estrategias de aprendizaje del alumno.

  18. Learning From Short Text Streams With Topic Drifts.

    Science.gov (United States)

    Li, Peipei; He, Lu; Wang, Haiyan; Hu, Xuegang; Zhang, Yuhong; Li, Lei; Wu, Xindong

    2017-09-18

    Short text streams such as search snippets and micro blogs have been popular on the Web with the emergence of social media. Unlike traditional normal text streams, these data present the characteristics of short length, weak signal, high volume, high velocity, topic drift, etc. Short text stream classification is hence a very challenging and significant task. However, this challenge has received little attention from the research community. Therefore, a new feature extension approach is proposed for short text stream classification with the help of a large-scale semantic network obtained from a Web corpus. It is built on an incremental ensemble classification model for efficiency. First, more semantic contexts based on the senses of terms in short texts are introduced to make up of the data sparsity using the open semantic network, in which all terms are disambiguated by their semantics to reduce the noise impact. Second, a concept cluster-based topic drifting detection method is proposed to effectively track hidden topic drifts. Finally, extensive studies demonstrate that as compared to several well-known concept drifting detection methods in data stream, our approach can detect topic drifts effectively, and it enables handling short text streams effectively while maintaining the efficiency as compared to several state-of-the-art short text classification approaches.

  19. Networking European Universities through e-learning (reviewed text

    Directory of Open Access Journals (Sweden)

    Jana Dlouhá

    2008-05-01

    The main purpose of the Inventory is to show concrete examples which have been implemented in the Member States under the concept of ESD in formal and non-formal learning contexts and which are at the forefront as regards innovative approaches. Projects/programmes selected as innovative good practice will be used to inform the preparation of the next Progress Report on the EU Sustainable Development Strategy in Education. See European Commission DG Education and Culture Inventory of innovative practices in education for sustainable development, the case study VCSE - Virtual Campus for a Sustainable Europe (EUROPEAN LEVEL, page 33.

  20. Networking European Universities through e-learning (reviewed text)

    OpenAIRE

    Dlouhá, Jana

    2008-01-01

    Virtual Campus for a Sustainable Europe (VCSE) network has been selected to be part of the EC DG EAC Inventory of innovative good practice on education for sustainable development. The main purpose of the Inventory is to show concrete examples which have been implemented in the Member States under the concept of ESD in formal and non-formal learning contexts and which are at the forefront as regards innovative approaches. Projects/programmes selected as innovative good practice will be use...

  1. A critique of Stephen Downes' article, "Learning Objects" -- A perspective from Bahrain

    Directory of Open Access Journals (Sweden)

    Muain H. Jamlan

    2001-07-01

    Full Text Available With the availability of technology, hardware, and software, learning objects become fundamental to the learning process and change the way in which learning materials are designed. The vast development of technology forces both teacher and learner to modify their roles. Teachers become facilitators, while learners became active and responsible for selecting modes and styles of learning. Assuming this attitude of implementing technology in the learning process and seeking new methods of facilitating learning, universities and colleges have to adopt new techniques. One of these new techniques is the use of learning objects. Although learning objects are considered products of technology developed in the USA, Japan, and European countries, universities in the Middle East have been influenced by this development. While there are differences in the quantity and quality of these technologies available in many Middle East countries, computer applications, especially those that deploy the Internet, have now become available. Educational authorities in Middle East countries are now turning to the availability of learning objects. Let me clarify some of the issues Downes discusses in his article on learning objects, Vol. 2, No. 1 of the International Review of Research in Open and Distance Learning.

  2. ICT Competence-Based Learning Object Recommendations for Teachers

    Science.gov (United States)

    Sergis, Stylianos; Zervas, Panagiotis; Sampson, Demetrios G.

    2014-01-01

    Recommender Systems (RS) have been applied in the Technology enhanced Learning (TeL) field for facilitating, among others, Learning Object (LO) selection and retrieval. Most of the existing approaches, however, aim at accommodating the needs of learners and teacher-oriented RS are still an under-investigated field. Moreover, the systems that focus…

  3. Methodology for Evaluating Quality and Reusability of Learning Objects

    Science.gov (United States)

    Kurilovas, Eugenijus; Bireniene, Virginija; Serikoviene, Silvija

    2011-01-01

    The aim of the paper is to present the scientific model and several methods for the expert evaluation of quality of learning objects (LOs) paying especial attention to LOs reusability level. The activities of eQNet Quality Network for a European Learning Resource Exchange (LRE) aimed to improve reusability of LOs of European Schoolnet's LRE…

  4. An OWL Ontology for Metadata of Interactive Learning Objects

    Science.gov (United States)

    Luz, Bruno N.; Santos, Rafael; Alves, Bruno; Areão, Andreza S.; Yokoyama, Marcos H.; Guimarães, Marcelo P.

    2015-01-01

    The main purpose of this paper is to present the importance of Interactive Learning Objects (ILO) to improve the teaching-learning process by assuring a constant interaction among teachers and students, which in turn, allows students to be constantly supported by the teacher. The paper describes the ontology that defines the ILO available on the…

  5. Technology and human issues in reusing learning objects

    NARCIS (Netherlands)

    Collis, Betty; Strijker, A.

    2004-01-01

    Reusing learning objects is as old as retelling a story or making use of libraries and textbooks, and in electronic form has received an enormous new impetus because of the World Wide Web and Web technologies. Are we at the brink of changing the "shape and form of learning, ... of being able to

  6. Speckle-learning-based object recognition through scattering media.

    Science.gov (United States)

    Ando, Takamasa; Horisaki, Ryoichi; Tanida, Jun

    2015-12-28

    We experimentally demonstrated object recognition through scattering media based on direct machine learning of a number of speckle intensity images. In the experiments, speckle intensity images of amplitude or phase objects on a spatial light modulator between scattering plates were captured by a camera. We used the support vector machine for binary classification of the captured speckle intensity images of face and non-face data. The experimental results showed that speckles are sufficient for machine learning.

  7. How learning might strengthen existing visual object representations in human object-selective cortex.

    Science.gov (United States)

    Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

    2016-02-15

    Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. EDUCATEE'S THESAURUS AS AN OBJECT OF MEASURING LEARNED MATERIAL OF THE DISTANCE LEARNING COURSE

    Directory of Open Access Journals (Sweden)

    Alexander Aleksandrovich RYBANOV

    2013-10-01

    Full Text Available Monitoring and control over the process of studying the distance learning course are based on solving the problem of making out an adequate integral mark to the educatee for mastering entire study course, by testing results. It is suggested to use the degree of correspondence between educatee's thesaurus and the study course thesaurus as an integral mark for the degree of mastering the distance learning course. Study course thesaurus is a set of the course objects with relations between them specified. The article considers metrics of the study course thesaurus complexity, made on the basis of the graph theory and the information theory. It is suggested to use the amount of information contained in the study course thesaurus graph as the metrics of the study course thesaurus complexity. Educatee's thesaurus is considered as an object of measuring educational material learned at the semantic level and is assessed on the basis of amount of information contained in its graph, taking into account the factors of learning the thesaurus objects.

  9. Identifying child abuse through text mining and machine learning

    NARCIS (Netherlands)

    Amrit, Chintan; Paauw, Tim; Aly, Robin; Lavric, Miha

    2017-01-01

    In this paper, we describe how we used text mining and analysis to identify and predict cases of child abuse in a public health institution. Such institutions in the Netherlands try to identify and prevent different kinds of abuse. A significant part of the medical data that the institutions have on

  10. Students' Learning Experiences from Didactic Teaching Sessions Including Patient Case Examples as Either Text or Video

    DEFF Research Database (Denmark)

    Pedersen, Kamilla; Moeller, Martin Holdgaard; Paltved, Charlotte

    2017-01-01

    OBJECTIVES: The aim of this study was to explore medical students' learning experiences from the didactic teaching formats using either text-based patient cases or video-based patient cases with similar content. The authors explored how the two different patient case formats influenced students......' perceptions of psychiatric patients and students' reflections on meeting and communicating with psychiatric patients. METHODS: The authors conducted group interviews with 30 medical students who volunteered to participate in interviews and applied inductive thematic content analysis to the transcribed...

  11. e-Learning objects in the cloud: SCORM compliance, creation and deployment options

    Directory of Open Access Journals (Sweden)

    Stephanie Day

    2017-12-01

    Full Text Available In the field of education, cloud computing is changing the way learning is delivered and experienced, by providing software, storage, teaching resources, artefacts, and knowledge that can be shared by educators on a global scale. In this paper, the first objective is to understand the general trends in educational use of the cloud, particularly the provision of large scale education opportunities, use of open and free services, and interoperability of learning objects. A review of current literature reveals the opportunities and issues around managing learning and teaching related knowledge in the cloud. The educational use of the cloud will continue to grow as the services, pedagogies, personalization, and standardization of learning are refined and adopted. Secondly, the paper presents an example of how the cloud can support learning opportunities using SCORM interoperable learning objects. The case study findings show that, while the use of SCORM enables a variety of trackable learning opportunities, the constraints of maintaining the currency of the learning also need to be considered. It is recommended that the SCORM content are combined with cloud based student activities. These learning objects can be used to support alternative learning opportunities within blended and online learning environments.

  12. Definition of a Learning Object from Perspectives of In-Service Teachers (Case of Duzce Province

    Directory of Open Access Journals (Sweden)

    Kürşat ARSLAN

    2016-08-01

    Full Text Available Learning objects, as a relatively new technological concept, have drawn much attention from educators because these dijital resources are easily accessible, relatively easy to use due to their limited size and focus, interactive, and adaptable to many different educational contexts. Despite the fact that learning objects have the great potential to improve teaching and learning experiences by providing teachers reusable learning materials and reducing costs, the lack of a “working and clear” definition of these materials has restricted their effective and efficient use. This study aimed to explore elementary school teacher perceptions of their use of learning objects from a qualitative research paradigm in order to reveal the extent to which teachers understand concept of learning object and its instruction approach. The method of the study was based on descriptive phenomenology. Data were collected using multiple methods, including the semi-structured interview, field observation reports, and photos from nine in-service elementary school teachers from different departments in Duzce, Turkey. Methods of data analysis were based on Giorgi’s method of descriptive phenomenology including four stages of content analysis: data coding, developing themes, organizing code and themes, describing findings. Overall findings of the study indicate that teachers use learning objects in their lesson activities without explicit recognition; however they generally fail to understand the exact meaning of a learning object approach and its applications in the classroom. Participants understood different properties of learning objects. Almost all participants perceive objectivity as the most important characteristic of the learning object.  In addition, a majority of the teachers recognized the value of a learning object’s reusability. In-service teachers’ vague perceptions of the definition and usage of learning objects indicated that they used these

  13. Learning chemistry from text: The effect of decision making

    Science.gov (United States)

    Pedersen, Jon; J., Ronald; Alice, Bonnstetter; Corkill, J.; Glover, John A.

    Two experiments examined the relative effects of questions requiring decisions, statements providing the decision information to students, questions not requiring decisions, and control procedures on students' memory for chemistry text reading materials. Experiment 1 employed immediate recall. The results of Experiment 1 indicated that students who made and justified decisions about the contents recalled significantly more information than students in any other condition. In addition, students who answered questions that did not require decisions recalled significantly more of the content than students in the control or the statements conditions. No other contrasts reached significance. Experiment 2 employed delayed recall assessed one week after reading. The results confirmed those of Experiment 1. The overall results of the study are discussed in terms of an elaboration perspective on memory.

  14. Individualized Learning Through Non-Linear use of Learning Objects: With Examples From Math and Stat

    DEFF Research Database (Denmark)

    Rootzén, Helle

    2015-01-01

    Our aim is to ensure individualized learning that is fun, inspiring and innovative. We believe that when you enjoy, your brain will open up and learning will be easier and more effective. The methods use a non-linear learning environment based on self-contained learning objects which are pieced t...

  15. Reinforcement active learning in the vibrissae system: optimal object localization.

    Science.gov (United States)

    Gordon, Goren; Dorfman, Nimrod; Ahissar, Ehud

    2013-01-01

    Rats move their whiskers to acquire information about their environment. It has been observed that they palpate novel objects and objects they are required to localize in space. We analyze whisker-based object localization using two complementary paradigms, namely, active learning and intrinsic-reward reinforcement learning. Active learning algorithms select the next training samples according to the hypothesized solution in order to better discriminate between correct and incorrect labels. Intrinsic-reward reinforcement learning uses prediction errors as the reward to an actor-critic design, such that behavior converges to the one that optimizes the learning process. We show that in the context of object localization, the two paradigms result in palpation whisking as their respective optimal solution. These results suggest that rats may employ principles of active learning and/or intrinsic reward in tactile exploration and can guide future research to seek the underlying neuronal mechanisms that implement them. Furthermore, these paradigms are easily transferable to biomimetic whisker-based artificial sensors and can improve the active exploration of their environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Learning while Babbling: Prelinguistic Object-Directed Vocalizations Indicate a Readiness to Learn

    Science.gov (United States)

    Goldstein, Michael H.; Schwade, Jennifer; Briesch, Jacquelyn; Syal, Supriya

    2010-01-01

    Two studies illustrate the functional significance of a new category of prelinguistic vocalizing--object-directed vocalizations (ODVs)--and show that these sounds are connected to learning about words and objects. Experiment 1 tested 12-month-old infants' perceptual learning of objects that elicited ODVs. Fourteen infants' vocalizations were…

  17. A Text Mining Approach for Extracting Lessons Learned from Project Documentation: An Illustrative Case Study

    Directory of Open Access Journals (Sweden)

    Benjamin Matthies

    2017-12-01

    Full Text Available Lessons learned are important building blocks for continuous learning in project-based organisations. Nonetheless, the practical reality is that lessons learned are often not consistently reused for organisational learning. Two problems are commonly described in this context: the information overload and the lack of procedures and methods for the assessment and implementation of lessons learned. This paper addresses these problems, and appropriate solutions are combined in a systematic lesson learned process. Latent Dirichlet Allocation is presented to solve the first problem. Regarding the second problem, established risk management methods are adapted. The entire lessons learned process will be demonstrated in a practical case study

  18. Learning Objects and Grasp Affordances through Autonomous Exploration

    DEFF Research Database (Denmark)

    Kraft, Dirk; Detry, Renaud; Pugeault, Nicolas

    2009-01-01

    We describe a system for autonomous learning of visual object representations and their grasp affordances on a robot-vision system. It segments objects by grasping and moving 3D scene features, and creates probabilistic visual representations for object detection, recognition and pose estimation...... image sequences as well as (3) a number of built-in behavioral modules on the one hand, and autonomous exploration on the other hand, the system is able to generate object and grasping knowledge through interaction with its environment....

  19. Estimating the Difficulty Level of EFL Texts: Applying Bloom’s Taxonomy of Educational Objectives

    Directory of Open Access Journals (Sweden)

    Natasha Pourdana

    2013-11-01

    Full Text Available The purpose of the present study was to explore the impact of difficulty level of texts on EFL learners’ reading comprehension through the application of Bloom’s cognitive taxonomy. The researchers’ primary assumption was that reading EFL texts would become more difficult as the learners’ performance proceeds from a text targeting their Knowledge abilities through the texts tapping on their Comprehension, Application, Analysis, Synthesis to Evaluation abilities. To fulfil the ultimate purpose of the research, 32 undergraduate students majoring in English translation at Islamic Azad University, Karaj Branch, Iran took part in this investigation in 2011. In addition to Comprehensive English Language Test (CELT, the participants were given a teacher–made reading comprehension test, included six short reading passages from 154 to 166 ranges of words and 30 multiple- choice items which compiled and constructed based on the six levels in the hierarchy of Bloom’s cognitive taxonomy. Analysis of Variance (ANOVA proved that except for the fifth level, the Synthesis text, the EFL learners’ performance was graded properly based on the difficulty levels expected and explored in Bloom’s levels of Cognitive Domain. The findings in this study are considerably practical in developing EFL materials and teaching reading skills and strategies.

  20. How do students navigate and learn from nonlinear science texts: Can metanavigation support promote science learning?

    Science.gov (United States)

    Stylianou, Agni

    2003-06-01

    Digital texts which are based on hypertext and hypermedia technologies are now being used to support science learning. Hypertext offers certain opportunities for learning as well as difficulties that challenge readers to become metacognitively aware of their navigation decisions in order to trade both meaning and structure while reading. The goal of this study was to investigate whether supporting sixth grade students to monitor and regulate their navigation behavior while reading from hypertext would lead to better navigation and learning. Metanavigation support in the form of prompts was provided to groups of students who used a hypertext system called CoMPASS to complete a design challenge. The metanavigation prompts aimed at encouraging students to understand the affordances of the navigational aids in CoMPASS and use them to guide their navigation. The study was conducted in a real classroom setting during the implementation of CoMPASS in sixth grade science classes. Multiple sources of group and individual data were collected and analyzed. Measures included student's individual performance in a pre-science knowledge test, the Metacognitive Awareness of Reading Strategies Inventory (MARSI), a reading comprehension test and a concept map test. Process measures included log file information that captured group navigation paths during the use of CoMPASS. The results suggested that providing metanavigation support enabled the groups to make coherent transitions among the text units. Findings also revealed that reading comprehension, presence of metanavigation support and prior domain knowledge significantly predicted students' individual understanding of science. Implications for hypertext design and literacy research fields are discussed.

  1. An Initial Approach for Learning Objects from Experience

    Science.gov (United States)

    2018-05-02

    algorithm to delineate objects which are then fed to a simple feed-forward neural network without any other processes in the pipeline. Our neural network...These are the basic requirements for the pipeline and are discussed in more detail below. Additionally, we are interested in testing various parts...that continuously learning objects from experience requires mechanisms to do the following: 1) Focus attention on things and stuff of interest . 2

  2. Object Attention Patches for Text Detection and Recognition in Scene Images using SIFT

    NARCIS (Netherlands)

    Sriman, Bowornrat; Schomaker, Lambertus; De Marsico, Maria; Figueiredo, Mário; Fred, Ana

    2015-01-01

    Natural urban scene images contain many problems for character recognition such as luminance noise, varying font styles or cluttered backgrounds. Detecting and recognizing text in a natural scene is a difficult problem. Several techniques have been proposed to overcome these problems. These are,

  3. Object Recognition in Clutter: Cortical Responses Depend on the Type of Learning

    Directory of Open Access Journals (Sweden)

    Jay eHegdé

    2012-06-01

    Full Text Available Theoretical studies suggest that the visual system uses prior knowledge of visual objects to recognize them in visual clutter, and posit that the strategies for recognizing objects in clutter may differ depending on whether or not the object was learned in clutter to begin with. We tested this hypothesis using functional magnetic resonance imaging (fMRI of human subjects. We trained subjects to recognize naturalistic, yet novel objects in strong or weak clutter. We then tested subjects’ recognition performance for both sets of objects in strong clutter. We found many brain regions that were differentially responsive to objects during object recognition depending on whether they were learned in strong or weak clutter. In particular, the responses of the left fusiform gyrus reliably reflected, on a trial-to-trial basis, subjects’ object recognition performance for objects learned in the presence of strong clutter. These results indicate that the visual system does not use a single, general-purpose mechanism to cope with clutter. Instead, there are two distinct spatial patterns of activation whose responses are attributable not to the visual context in which the objects were seen, but to the context in which the objects were learned.

  4. Creating Learning Objects to Enhance the Educational Experiences of American Sign Language Learners: An Instructional Development Report

    Directory of Open Access Journals (Sweden)

    Simone Conceição

    2002-10-01

    Full Text Available Little attention has been given to involving the deaf community in distance teaching and learning or in designing courses that relate to their language and culture. This article reports on the design and development of video-based learning objects created to enhance the educational experiences of American Sign Language (ASL hearing participants in a distance learning course and, following the course, the creation of several new applications for use of the learning objects. The learning objects were initially created for the web, as a course component for review and rehearsal. The value of the web application, as reported by course participants, led us to consider ways in which the learning objects could be used in a variety of delivery formats: CD-ROM, web-based knowledge repository, and handheld device. The process to create the learning objects, the new applications, and lessons learned are described.

  5. #gottacatchemall: Exploring Pokemon Go in Search of Learning Enhancement Objects

    Science.gov (United States)

    Cacchione, Annamaria; Procter-Legg, Emma; Petersen, Sobah Abbas

    2017-01-01

    The Augmented Reality Game, Pokemon Go, took the world by storm in the summer of 2016. City landscapes were decorated with amusing, colourful objects called Pokemon, and the holiday activities were enhanced by catching these wonderful creatures. In light of this, it is inevitable for mobile language learning researchers to reflect on the impact of…

  6. Evaluating the Use of Learning Objects for Improving Calculus Readiness

    Science.gov (United States)

    Kay, Robin; Kletskin, Ilona

    2010-01-01

    Pre-calculus concepts such as working with functions and solving equations are essential for students to explore limits, rates of change, and integrals. Yet many students have a weak understanding of these key concepts which impedes performance in their first year university Calculus course. A series of online learning objects was developed to…

  7. Semantic Linking of Learning Object Repositories to DBpedia

    Science.gov (United States)

    Lama, Manuel; Vidal, Juan C.; Otero-Garcia, Estefania; Bugarin, Alberto; Barro, Senen

    2012-01-01

    Large-sized repositories of learning objects (LOs) are difficult to create and also to maintain. In this paper we propose a way to reduce this drawback by improving the classification mechanisms of the LO repositories. Specifically, we present a solution to automate the LO classification of the Universia repository, a collection of more than 15…

  8. Exploring Characterizations of Learning Object Repositories Using Data Mining Techniques

    Science.gov (United States)

    Segura, Alejandra; Vidal, Christian; Menendez, Victor; Zapata, Alfredo; Prieto, Manuel

    Learning object repositories provide a platform for the sharing of Web-based educational resources. As these repositories evolve independently, it is difficult for users to have a clear picture of the kind of contents they give access to. Metadata can be used to automatically extract a characterization of these resources by using machine learning techniques. This paper presents an exploratory study carried out in the contents of four public repositories that uses clustering and association rule mining algorithms to extract characterizations of repository contents. The results of the analysis include potential relationships between different attributes of learning objects that may be useful to gain an understanding of the kind of resources available and eventually develop search mechanisms that consider repository descriptions as a criteria in federated search.

  9. SAIL: Summation-bAsed Incremental Learning for Information-Theoretic Text Clustering.

    Science.gov (United States)

    Cao, Jie; Wu, Zhiang; Wu, Junjie; Xiong, Hui

    2013-04-01

    Information-theoretic clustering aims to exploit information-theoretic measures as the clustering criteria. A common practice on this topic is the so-called Info-Kmeans, which performs K-means clustering with KL-divergence as the proximity function. While expert efforts on Info-Kmeans have shown promising results, a remaining challenge is to deal with high-dimensional sparse data such as text corpora. Indeed, it is possible that the centroids contain many zero-value features for high-dimensional text vectors, which leads to infinite KL-divergence values and creates a dilemma in assigning objects to centroids during the iteration process of Info-Kmeans. To meet this challenge, in this paper, we propose a Summation-bAsed Incremental Learning (SAIL) algorithm for Info-Kmeans clustering. Specifically, by using an equivalent objective function, SAIL replaces the computation of KL-divergence by the incremental computation of Shannon entropy. This can avoid the zero-feature dilemma caused by the use of KL-divergence. To improve the clustering quality, we further introduce the variable neighborhood search scheme and propose the V-SAIL algorithm, which is then accelerated by a multithreaded scheme in PV-SAIL. Our experimental results on various real-world text collections have shown that, with SAIL as a booster, the clustering performance of Info-Kmeans can be significantly improved. Also, V-SAIL and PV-SAIL indeed help improve the clustering quality at a lower cost of computation.

  10. [Learning objectives achievement in ethics education for medical school students].

    Science.gov (United States)

    Chae, Sujin; Lim, Kiyoung

    2015-06-01

    This study aimed to examine the necessity for research ethics and learning objectives in ethics education at the undergraduate level. A total of 393 fourth-year students, selected from nine medical schools, participated in a survey about learning achievement and the necessity for it. It was found that the students had very few chances to receive systematic education in research ethics and that they assumed that research ethics education was provided during graduate school or residency programs. Moreover, the students showed a relatively high learning performance in life ethics, while learning achievement was low in research ethics. Medical school students revealed low interest in and expectations of research ethics in general; therefore, it is necessary to develop guidelines for research ethics in the present situation, in which medical education mainly focuses on life ethics.

  11. Comparing L2 Word Learning through a Tablet or Real Objects: What Benefits Learning Most?

    NARCIS (Netherlands)

    Vlaar, M.A.J.; Verhagen, J.; Oudgenoeg-Paz, O.; Leseman, P.P.M.

    2017-01-01

    In child-robot interactions focused on language learning, tablets are often used to structure the interaction between the robot and the child. However, it is not clear how tablets affect children’s learning gains. Real-life objects are thought to benefit children’s word learning, but it is not clear

  12. Text-to-audiovisual speech synthesizer for children with learning disabilities.

    Science.gov (United States)

    Mendi, Engin; Bayrak, Coskun

    2013-01-01

    Learning disabilities affect the ability of children to learn, despite their having normal intelligence. Assistive tools can highly increase functional capabilities of children with learning disorders such as writing, reading, or listening. In this article, we describe a text-to-audiovisual synthesizer that can serve as an assistive tool for such children. The system automatically converts an input text to audiovisual speech, providing synchronization of the head, eye, and lip movements of the three-dimensional face model with appropriate facial expressions and word flow of the text. The proposed system can enhance speech perception and help children having learning deficits to improve their chances of success.

  13. Oral History as Complement to Place-as-Text: Approaches to Service Learning

    Science.gov (United States)

    Pederson, JoEllen; Znosko, Jessi; Peters, Jesse; Cannata, Susan M.

    2018-01-01

    The purpose of this paper is to discuss the advantages of combining place-as-text curriculum with an oral history collection to act as catalysts for transformational learning. These experiential and service learning practices complement each other to enrich the encounters students are afforded. First, the nature and procedures of place-as-text and…

  14. Focus of Attention and Choice of Text Modality in Multimedia Learning

    Science.gov (United States)

    Schnotz, Wolfgang; Mengelkamp, Christoph; Baadte, Christiane; Hauck, Georg

    2014-01-01

    The term "modality effect" in multimedia learning means that students learn better from pictures combined with spoken rather than written text. The most prominent explanations refer to the split attention between visual text reading and picture observation which could affect transfer of information into working memory, maintenance of…

  15. Visual object tracking by correlation filters and online learning

    Science.gov (United States)

    Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

    2018-06-01

    Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

  16. Creating Objects and Object Categories for Studying Perception and Perceptual Learning

    Science.gov (United States)

    Hauffen, Karin; Bart, Eugene; Brady, Mark; Kersten, Daniel; Hegdé, Jay

    2012-01-01

    In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created

  17. When Do Pictures Help Learning from Expository Text? Multimedia and Modality Effects in Primary Schools

    Science.gov (United States)

    Herrlinger, Simone; Höffler, Tim N.; Opfermann, Maria; Leutner, Detlev

    2017-06-01

    Adding pictures to a text is very common in today's education and might be especially beneficial for elementary school children, whose abilities to read and understand pure text have not yet been fully developed. Our study examined whether adding pictures supports learning of a biology text in fourth grade and whether the text modality (spoken or written) plays a role. Results indicate that overall, pictures enhanced learning but that the text should be spoken rather than written. These results are in line with instructional design principles derived from common multimedia learning theories. In addition, for elementary school children, it might be advisable to read texts out to the children. Reading by themselves and looking at pictures might overload children's cognitive capacities and especially their visual channel. In this case, text and pictures would not be integrated into one coherent mental model, and effective learning would not take place.

  18. An Analysis on Usage Preferences of Learning Objects and Learning Object Repositories among Pre-Service Teachers

    Science.gov (United States)

    Yeni, Sabiha; Ozdener, Nesrin

    2014-01-01

    The purpose of the study is to investigate how pre-service teachers benefit from learning objects repositories while preparing course content. Qualitative and quantitative data collection methods were used in a mixed methods approach. This study was carried out with 74 teachers from the Faculty of Education. In the first phase of the study,…

  19. How do newcomers learn to use an object?

    DEFF Research Database (Denmark)

    Kjær, Malene

    in the daily practice of assessing how a patient is doing. Learning how to operate it in situ is thus an important task.I will present an empirical example from clinical nursing education in a Danish hospital, where students learn to use specific medical objects (a sphygmomanometer) in the setting...... status and stance (Heritage, 2012) epistemic, cooperative and instrumental stance (Goodwin, 2007) is important, as is the understanding of situated embodied cognition in the workplace practice: the knowledge ‘understanding and use of objects’ that has been limited to the nurse, translates through...

  20. Enriching Student Learning of Astronomy in Online Courses via Hybrid Texts

    Science.gov (United States)

    Montgomery, M.

    2016-01-01

    Hybrid texts such as Horizons: Exploring the Universe, Hybrid (with CengageNOW) and Universe, Hybrid (with CengageNOW) are designed for higher education learning of astronomy in undergraduate online courses. In these hybrid texts, quiz and test bank questions have been revised to minimize easy look-up of answers by students via the Internet and discussion threads have been re-designed to allow for student selection of learning and for personalized learning, for example. By establishing connections between the student and the course content, student learning is enriched, students spend more time learning the material, student copying of answers is minimized, and student social engagement on the subject matter is increased. In this presentation, we discuss how Hybrid texts in Astronomy can increase student learning in online courses.

  1. Effects of Picture Labeling on Science Text Processing and Learning: Evidence from Eye Movements

    Science.gov (United States)

    Mason, Lucia; Pluchino, Patrik; Tornatora, Maria Caterina

    2013-01-01

    This study investigated the effects of reading a science text illustrated by either a labeled or unlabeled picture. Both the online process of reading the text and the offline conceptual learning from the text were examined. Eye-tracking methodology was used to trace text and picture processing through indexes of first- and second-pass reading or…

  2. Validation of virtual learning object to support the teaching of nursing care systematization

    Directory of Open Access Journals (Sweden)

    Pétala Tuani Candido de Oliveira Salvador

    Full Text Available ABSTRACT Objective: to describe the content validation process of a Virtual Learning Object to support the teaching of nursing care systematization to nursing professionals. Method: methodological study, with quantitative approach, developed according to the methodological reference of Pasquali's psychometry and conducted from March to July 2016, from two-stage Delphi procedure. Results: in the Delphi 1 stage, eight judges evaluated the Virtual Object; in Delphi 2 stage, seven judges evaluated it. The seven screens of the Virtual Object were analyzed as to the suitability of its contents. The Virtual Learning Object to support the teaching of nursing care systematization was considered valid in its content, with a Total Content Validity Coefficient of 0.96. Conclusion: it is expected that the Virtual Object can support the teaching of nursing care systematization in light of appropriate and effective pedagogical approaches.

  3. Interaction between the Learners' Initial Grasp of the Object of Learning and the Learning Resource Afforded

    Science.gov (United States)

    Pang, Ming Fai; Marton, Ference

    2013-01-01

    Two studies are reported in this paper. The object of learning in both is the economic principle of changes in price as a function of changes in the relative magnitude of changes in demand and supply. The patterns of variation and invariance, defining the conditions compared were built into pedagogical tools (text, graphs, and worksheets). The…

  4. Learning-based stochastic object models for characterizing anatomical variations

    Science.gov (United States)

    Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

    2018-03-01

    It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

  5. Virtual learning object and environment: a concept analysis.

    Science.gov (United States)

    Salvador, Pétala Tuani Candido de Oliveira; Bezerril, Manacés Dos Santos; Mariz, Camila Maria Santos; Fernandes, Maria Isabel Domingues; Martins, José Carlos Amado; Santos, Viviane Euzébia Pereira

    2017-01-01

    To analyze the concept of virtual learning object and environment according to Rodgers' evolutionary perspective. Descriptive study with a mixed approach, based on the stages proposed by Rodgers in his concept analysis method. Data collection occurred in August 2015 with the search of dissertations and theses in the Bank of Theses of the Coordination for the Improvement of Higher Education Personnel. Quantitative data were analyzed based on simple descriptive statistics and the concepts through lexicographic analysis with support of the IRAMUTEQ software. The sample was made up of 161 studies. The concept of "virtual learning environment" was presented in 99 (61.5%) studies, whereas the concept of "virtual learning object" was presented in only 15 (9.3%) studies. A virtual learning environment includes several and different types of virtual learning objects in a common pedagogical context. Analisar o conceito de objeto e de ambiente virtual de aprendizagem na perspectiva evolucionária de Rodgers. Estudo descritivo, de abordagem mista, realizado a partir das etapas propostas por Rodgers em seu modelo de análise conceitual. A coleta de dados ocorreu em agosto de 2015 com a busca de dissertações e teses no Banco de Teses e Dissertações da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior. Os dados quantitativos foram analisados a partir de estatística descritiva simples e os conceitos pela análise lexicográfica com suporte do IRAMUTEQ. A amostra é constituída de 161 estudos. O conceito de "ambiente virtual de aprendizagem" foi apresentado em 99 (61,5%) estudos, enquanto o de "objeto virtual de aprendizagem" em apenas 15 (9,3%). Concluiu-se que um ambiente virtual de aprendizagem reúne vários e diferentes tipos de objetos virtuais de aprendizagem em um contexto pedagógico comum.

  6. Object-oriented user interfaces for personalized mobile learning

    CERN Document Server

    Alepis, Efthimios

    2014-01-01

    This book presents recent research in mobile learning and advanced user interfaces. It is shown how the combination of this fields can result in personalized educational software that meets the requirements of state-of-the-art mobile learning software. This book provides a framework that is capable of incorporating the software technologies, exploiting a wide range of their current advances and additionally investigating ways to go even further by providing potential solutions to future challenges. The presented approach uses the well-known Object-Oriented method in order to address these challenges. Throughout this book, a general model is constructed using Object-Oriented Architecture. Each chapter focuses on the construction of a specific part of this model, while in the conclusion these parts are unified. This book will help software engineers build more sophisticated personalized software that targets in mobile education, while at the same time retaining a high level of adaptivity and user-friendliness w...

  7. ATTITUDES OF STUDENTS TOWARDS LEARNING OBJECTS IN WEB-BASED LANGUAGE LEARNING

    Directory of Open Access Journals (Sweden)

    Ahmet BASAL

    2012-01-01

    Full Text Available Language education is important in the rapidly changing world. Every year much effort has spent on preparing teaching materials for language education. Since positive attitudes of learners towards a teaching material enhance the effectiveness of that material, it is important to determine the attitudes of learners towards the material used. Learning objects (LOs are a new type of material on which many studies have been conducted in recent years. The aim of this study is to determine the attitudes of students towards LOs in web-based language learning. To this end, the study was conducted in English I Course at the Department of Computer Programming in Kırıkkale University in 2010-2011 Fall Semester. Seventy LOs appropriate for six-week long lecture program were integrated into the Learning Management System (LMS of Kırıkkale University. The study group consisted of 38 students. After the six weeks long implementation period of the study, an attitude scale was administered to the students. The findings indicated that students in web based language education have positive attitudes towards LOs.

  8. Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

    Science.gov (United States)

    Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

    2017-06-21

    In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

  9. Design, Implementation and Evaluation of a Learning Object that Supports the Mathematics Learning in Children with Autism Spectrum Disorders

    Directory of Open Access Journals (Sweden)

    Roberto Munoz

    2018-04-01

    Full Text Available Information technologies have been widely used for entertainment and learning purposes by children with Autism Spectrum Disorders (ASD. Nonetheless, learning objects aiming at specific skills development in children with ASD require both a well bounded learning domain and a user-centered design process, considering skill levels of the users and the local geographical context and language. “Proyect@ Matemáticas” is a multi-touch based app designed for developing pre-calculus and functional mathematical skills in children with ASD, according to the Chilean regulations of learning goals for children with special educational necessities. This paper presents the User-centered design process conducted in order to develop the learning object, which included the evaluation by 15 experts in special educational needs, testing by 10 ASD-diagnosed children with different functional levels, and a multidisciplinary development team that also included a graphic designer diagnosed with ASD of high functionality. The development process yields to a validated learning object in terms of interactivity, design, engagement, and usability, from the point of view of the experts, and successful usage tests with ASD diagnosed children in terms of performance and achievement of learning outcomes. The application is currently available for download in the Google Play store for free, and currently has more than 15,000 downloads and an average rating of 4.2 out of 5 points.

  10. An Eye-Tracking Study of Learning from Science Text with Concrete and Abstract Illustrations

    Science.gov (United States)

    Mason, Lucia; Pluchino, Patrik; Tornatora, Maria Caterina; Ariasi, Nicola

    2013-01-01

    This study investigated the online process of reading and the offline learning from an illustrated science text. The authors examined the effects of using a concrete or abstract picture to illustrate a text and adopted eye-tracking methodology to trace text and picture processing. They randomly assigned 59 eleventh-grade students to 3 reading…

  11. Generative Learning Strategy Use and Self-Regulatory Prompting in Digital Text

    Science.gov (United States)

    Reid, Alan J.; Morrison, Gary M.

    2014-01-01

    The digital revolution is shifting print-based textbooks to digital text, and it has afforded the opportunity to incorporate meaningful learning strategies and otherwise separate metacognitive activities directly into these texts as embedded support. A sample of 89 undergraduates read a digital, expository text on the basics of photography. The…

  12. Orthographic learning and the role of text-to-speech software in Dutch disabled readers.

    Science.gov (United States)

    Staels, Eva; Van den Broeck, Wim

    2015-01-01

    In this study, we examined whether orthographic learning can be demonstrated in disabled readers learning to read in a transparent orthography (Dutch). In addition, we tested the effect of the use of text-to-speech software, a new form of direct instruction, on orthographic learning. Both research goals were investigated by replicating Share's self-teaching paradigm. A total of 65 disabled Dutch readers were asked to read eight stories containing embedded homophonic pseudoword targets (e.g., Blot/Blod), with or without the support of text-to-speech software. The amount of orthographic learning was assessed 3 or 7 days later by three measures of orthographic learning. First, the results supported the presence of orthographic learning during independent silent reading by demonstrating that target spellings were correctly identified more often, named more quickly, and spelled more accurately than their homophone foils. Our results support the hypothesis that all readers, even poor readers of transparent orthographies, are capable of developing word-specific knowledge. Second, a negative effect of text-to-speech software on orthographic learning was demonstrated in this study. This negative effect was interpreted as the consequence of passively listening to the auditory presentation of the text. We clarify how these results can be interpreted within current theoretical accounts of orthographic learning and briefly discuss implications for remedial interventions. © Hammill Institute on Disabilities 2013.

  13. Trends of E-Learning Research from 2000 to 2008: Use of Text Mining and Bibliometrics

    Science.gov (United States)

    Hung, Jui-long

    2012-01-01

    This study investigated the longitudinal trends of e-learning research using text mining techniques. Six hundred and eighty-nine (689) refereed journal articles and proceedings were retrieved from the Science Citation Index/Social Science Citation Index database in the period from 2000 to 2008. All e-learning publications were grouped into two…

  14. More Efficient e-Learning through Design: Color of Text and Background

    Science.gov (United States)

    Zufic, Janko; Kalpic, Damir

    2009-01-01

    Background: The area of research aimed for a more efficient e-learning is slowly widening from purely technical to the areas of psychology, didactics and methodology. The question is whether the text or background color influence the efficiency of memory, i.e. learning. If the answer to that question is positive, then another question arises which…

  15. Combining Machine Learning and Natural Language Processing to Assess Literary Text Comprehension

    Science.gov (United States)

    Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S.

    2017-01-01

    This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

  16. The Use of Conceptual Change Text toward Students’ Argumentation Skills in Learning Sound

    Science.gov (United States)

    Sari, B. P.; Feranie, S.; Winarno, N.

    2017-09-01

    This research aim is to investigate the effect of Conceptual Change Text toward students’ argumentation skills in learning sound concept. The participant comes from one of International school in Bandung, Indonesia. The method that used in this research is a quasi-experimental design with one control group (N=21) and one experimental group (N=21) were involves in this research. The learning model that used in both classes is demonstration model which included teacher explanation and examples, the difference only in teaching materials. In experiment group learn with Conceptual Change Text, while control group learn with conventional book which is used in school. The results showed that Conceptual Change Text instruction was better than the conventional book to improved students’ argumentation skills of sound concept. Based on this results showed that Conceptual Change Text instruction can be an alternative tool to improve students’ argumentation skills significantly.

  17. Opinion Mining in Latvian Text Using Semantic Polarity Analysis and Machine Learning Approach

    Directory of Open Access Journals (Sweden)

    Gatis Špats

    2016-07-01

    Full Text Available In this paper we demonstrate approaches for opinion mining in Latvian text. Authors have applied, combined and extended results of several previous studies and public resources to perform opinion mining in Latvian text using two approaches, namely, semantic polarity analysis and machine learning. One of the most significant constraints that make application of opinion mining for written content classification in Latvian text challenging is the limited publicly available text corpora for classifier training. We have joined several sources and created a publically available extended lexicon. Our results are comparable to or outperform current achievements in opinion mining in Latvian. Experiments show that lexicon-based methods provide more accurate opinion mining than the application of Naive Bayes machine learning classifier on Latvian tweets. Methods used during this study could be further extended using human annotators, unsupervised machine learning and bootstrapping to create larger corpora of classified text.

  18. Comprehension of texts in Digital Format versus Printed Texts and Self-Regulated Learning in University Students

    Directory of Open Access Journals (Sweden)

    Paula Gabriela Flores-Carrasco

    2016-12-01

    Full Text Available This article aims (1 to describe the levels of self-regulation and reading comprehension of scientific expository texts; (2 to establish the relationship between self-regulation and reading comprehension; and (3 to compare the performance in comprehension when the printed media (paper or digital media (computer is used. A quasi-experimental, quantitative, descriptive and correlative design was implemented. The sample was composed of 55 university students from four careers of Education; they were in 1st and 3rd year of study at a regional university of the Council of Rectors of Chilean Universities. Three measuring instruments were used: a questionnaire of self-regulated learning and two comprehension tests based on the understanding of Parodi’s (2005 assessment model. The implementation was made in two consecutive moments; first, the self-questionnaire; then, the tests for reading comprehension in both media. With the data obtained, statistical tests of variance, one-way ANOVA, Pearson’s correlation, and means comparison with Bruner and Munzel and U-Mann Whitney’s tests were calculated. In conclusion, and different from the initial statement, it was obtained that university students have an adequate level of self-regulation and low reading comprehension in both data, even the scores are relatively lower in digital data. In both data the output is inverse to the complexity of the questions. Between 1st and 3rd year, there is no increase either in the self-regulation or in reading comprehension; but, exceptionally, the career of Primary General Education specialist on Language and History did. There is a strong relationship between reading comprehension in printed media and self-regulation (ARATEX. The support does not affect reading comprehension, but individual reading skills of the subjects do. A competent reader will have similar performance in both reading supports.

  19. Evaluation of a Learning Object Based Learning Environment in Different Dimensions

    Directory of Open Access Journals (Sweden)

    Ünal Çakıroğlu

    2009-11-01

    Full Text Available Learning Objects (LOs are web based learning resources presented by Learning Object Repositories (LOR. For recent years LOs have begun to take place on web and it is suggested that appropriate design of LOs can make positive impact on learning. In order to support learning, research studies recommends LOs should have been evaluated pedagogically and technologically, and the content design created by using LOs should have been designed through appropriate instructional models. Since the use of LOs have recently begun, an exact pedagogical model about efficient use of LOs has not been developed. In this study a LOR is designed in order to be used in mathematics education. The LOs in this LOR have been evaluated pedagogically and technologically by mathematics teachers and field experts. In order to evaluate the designed LO based environment, two different questionnaires have been used. These questionnaires are developed by using the related literature about web based learning environments evaluation criteria and also the items are discussed with the field experts for providing the validity. The reliability of the questionnaires is calculated cronbach alpha = 0.715 for the design properties evaluation survey and cronbach alpha =0.726 for pedagogic evaluation. Both of two questionnaires are five point Likert type. The first questionnaire has the items about “Learning Support of LOs, Competency of LOR, The importance of LOs in mathematics education, the usability of LOs by students”. “The activities on LOs are related to outcomes of subjects, there are activities for students have different learning styles. There are activities for wondering students.” are examples for items about learning support of LOs. “System helps for exploration of mathematical relations”, “I think teaching mathematics with this system will be enjoyable.” are example items for importance of LOs in mathematics education. In the competency of LOR title,

  20. Algorithms for Learning Preferences for Sets of Objects

    Science.gov (United States)

    Wagstaff, Kiri L.; desJardins, Marie; Eaton, Eric

    2010-01-01

    A method is being developed that provides for an artificial-intelligence system to learn a user's preferences for sets of objects and to thereafter automatically select subsets of objects according to those preferences. The method was originally intended to enable automated selection, from among large sets of images acquired by instruments aboard spacecraft, of image subsets considered to be scientifically valuable enough to justify use of limited communication resources for transmission to Earth. The method is also applicable to other sets of objects: examples of sets of objects considered in the development of the method include food menus, radio-station music playlists, and assortments of colored blocks for creating mosaics. The method does not require the user to perform the often-difficult task of quantitatively specifying preferences; instead, the user provides examples of preferred sets of objects. This method goes beyond related prior artificial-intelligence methods for learning which individual items are preferred by the user: this method supports a concept of setbased preferences, which include not only preferences for individual items but also preferences regarding types and degrees of diversity of items in a set. Consideration of diversity in this method involves recognition that members of a set may interact with each other in the sense that when considered together, they may be regarded as being complementary, redundant, or incompatible to various degrees. The effects of such interactions are loosely summarized in the term portfolio effect. The learning method relies on a preference representation language, denoted DD-PREF, to express set-based preferences. In DD-PREF, a preference is represented by a tuple that includes quality (depth) functions to estimate how desired a specific value is, weights for each feature preference, the desired diversity of feature values, and the relative importance of diversity versus depth. The system applies statistical

  1. Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial.

    Science.gov (United States)

    Buch, Steen Vigh; Treschow, Frederik Philip; Svendsen, Jesper Brink; Worm, Bjarne Skjødt

    2014-01-01

    This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (Pvideo group performed better on the follow-up test (P=0.04). Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills.

  2. Space Objects Maneuvering Detection and Prediction via Inverse Reinforcement Learning

    Science.gov (United States)

    Linares, R.; Furfaro, R.

    This paper determines the behavior of Space Objects (SOs) using inverse Reinforcement Learning (RL) to estimate the reward function that each SO is using for control. The approach discussed in this work can be used to analyze maneuvering of SOs from observational data. The inverse RL problem is solved using the Feature Matching approach. This approach determines the optimal reward function that a SO is using while maneuvering by assuming that the observed trajectories are optimal with respect to the SO's own reward function. This paper uses estimated orbital elements data to determine the behavior of SOs in a data-driven fashion.

  3. From Learning Object to Learning Cell: A Resource Organization Model for Ubiquitous Learning

    Science.gov (United States)

    Yu, Shengquan; Yang, Xianmin; Cheng, Gang; Wang, Minjuan

    2015-01-01

    This paper presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social, and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a…

  4. Employing Machine-Learning Methods to Study Young Stellar Objects

    Science.gov (United States)

    Moore, Nicholas

    2018-01-01

    Vast amounts of data exist in the astronomical data archives, and yet a large number of sources remain unclassified. We developed a multi-wavelength pipeline to classify infrared sources. The pipeline uses supervised machine learning methods to classify objects into the appropriate categories. The program is fed data that is already classified to train it, and is then applied to unknown catalogues. The primary use for such a pipeline is the rapid classification and cataloging of data that would take a much longer time to classify otherwise. While our primary goal is to study young stellar objects (YSOs), the applications extend beyond the scope of this project. We present preliminary results from our analysis and discuss future applications.

  5. Classroom-Based Integration of Text-Messaging in Mathematics Teaching-Learning Process

    Science.gov (United States)

    Aunzo, Rodulfo T., Jr.

    2017-01-01

    A lot of teachers are complaining that students are "texting" inside the classroom even during class hours. With this, this research study "on students' perception before the integration and the students' attitude after the integration of text messaging inside the classroom during the mathematics teaching-learning process was…

  6. Improving Students' Science Text Comprehension through Metacognitive Self-Regulation When Applying Learning Strategies

    Science.gov (United States)

    Leopold, Claudia; Leutner, Detlev

    2015-01-01

    In three experiments, students were trained to use strategies for learning from scientific texts: text highlighting (Experiment 1), knowledge mapping (Experiment 2), and visualizing (Experiment 3). Each experiment compared a control condition, cognitive strategy training, and a combined cognitive strategy plus metacognitive self-regulation…

  7. An Introduction to Topic Modeling as an Unsupervised Machine Learning Way to Organize Text Information

    Science.gov (United States)

    Snyder, Robin M.

    2015-01-01

    The field of topic modeling has become increasingly important over the past few years. Topic modeling is an unsupervised machine learning way to organize text (or image or DNA, etc.) information such that related pieces of text can be identified. This paper/session will present/discuss the current state of topic modeling, why it is important, and…

  8. Applying Active Learning to Assertion Classification of Concepts in Clinical Text

    Science.gov (United States)

    Chen, Yukun; Mani, Subramani; Xu, Hua

    2012-01-01

    Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

  9. Metacomprehension judgements reflect the belief that diagrams improve learning from text.

    Science.gov (United States)

    Serra, Michael J; Dunlosky, John

    2010-10-01

    In two experiments we systematically explored whether people consider the format of text materials when judging their text learning, and whether doing so might inappropriately bias their judgements. Participants studied either text with diagrams (multimedia) or text alone and made both per-paragraph judgements and global judgements of their text learning. In Experiment 1 they judged their learning to be better for text with diagrams than for text alone. In that study, however, test performance was greater for multimedia, so the judgements may reflect either a belief in the power of multimedia or on-line processing. Experiment 2 replicated this finding and also included a third group that read texts with pictures that did not improve text performance. Judgements made by this group were just as high as those made by participants who received the effective multimedia format. These results confirm the hypothesis that people's metacomprehension judgements can be influenced by their beliefs about text format. Over-reliance on this multimedia heuristic, however, might reduce judgement accuracy in situations where it is invalid.

  10. Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Buch SV

    2014-08-01

    Full Text Available Steen Vigh Buch,1 Frederik Philip Treschow,2 Jesper Brink Svendsen,3 Bjarne Skjødt Worm4 1Department of Vascular Surgery, Rigshospitalet, Copenhagen, Denmark; 2Department of Anesthesia and Intensive Care, Herlev Hospital, Copenhagen, Denmark; 3Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; 4Department of Anesthesia and Intensive Care, Bispebjerg Hospital, Copenhagen, Denmark Background and aims: This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Materials and methods: Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. Results: The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (P<0.001 and in the follow-up test (P<0.01. Regarding theoretical knowledge, no differences were found between the groups on the primary test, though the video group performed better on the follow-up test (P=0.04. Conclusion: Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills. Keywords: e-learning, video versus text, medicine, clinical skills

  11. Creating Usage Context-Based Object Similarities to Boost Recommender Systems in Technology Enhanced Learning

    Science.gov (United States)

    Niemann, Katja; Wolpers, Martin

    2015-01-01

    In this paper, we introduce a new way of detecting semantic similarities between learning objects by analysing their usage in web portals. Our approach relies on the usage-based relations between the objects themselves rather then on the content of the learning objects or on the relations between users and learning objects. We then take this new…

  12. Concept mapping and text writing as learning tools in problem-oriented learning

    NARCIS (Netherlands)

    Fürstenau, B.; Kneppers, L.; Dekker, R.; Cañas, A.J.; Novak, J.D.; Vanhaer, J.

    2012-01-01

    In two studies we investigated whether concept mapping or summary writing better support students while learning from authentic problems in the field of business. We interpret concept mapping and summary writing as elaboration tools aiming at helping students to understand new information, and to

  13. Learning nanotechnology with texts and comics: the impacts on students of different achievement levels

    Science.gov (United States)

    Lin, Shu-Fen; Lin, Huann-shyang

    2016-05-01

    Comics are popular with adolescents because of their features of humor, narrative, and visual imagery. The purposes of this study were to examine the learning outcomes and emotional perceptions of reading a science comic book and a science text booklet for students of different levels of achievement, and to explore the main factors of the two media which attract high-school students to learn science. A mixed-method quasi-experimental design was adopted. The participants were 697 grade ten students from eight schools with different levels of academic achievement. Two similar classes in each of the eight schools were assigned as the comic group or the text group. The results indicated that the science comic book benefited medium achievers more than the science text booklet did, but the contrary result was found for the high achievers. In comparison, the two media benefited the low achievers equally, but both had only a limited effect due to the students' lack of prior knowledge. We conclude four kinds of evidence, including perceived difficulty of comprehension, reasons for interest/disinterest, emotional perceptions of learning science, and learning time, to support the phenomenon of the learning benefit of media specific to certain achievers' science learning.

  14. A Deep Similarity Metric Learning Model for Matching Text Chunks to Spatial Entities

    Science.gov (United States)

    Ma, K.; Wu, L.; Tao, L.; Li, W.; Xie, Z.

    2017-12-01

    The matching of spatial entities with related text is a long-standing research topic that has received considerable attention over the years. This task aims at enrich the contents of spatial entity, and attach the spatial location information to the text chunk. In the data fusion field, matching spatial entities with the corresponding describing text chunks has a big range of significance. However, the most traditional matching methods often rely fully on manually designed, task-specific linguistic features. This work proposes a Deep Similarity Metric Learning Model (DSMLM) based on Siamese Neural Network to learn similarity metric directly from the textural attributes of spatial entity and text chunk. The low-dimensional feature representation of the space entity and the text chunk can be learned separately. By employing the Cosine distance to measure the matching degree between the vectors, the model can make the matching pair vectors as close as possible. Mearnwhile, it makes the mismatching as far apart as possible through supervised learning. In addition, extensive experiments and analysis on geological survey data sets show that our DSMLM model can effectively capture the matching characteristics between the text chunk and the spatial entity, and achieve state-of-the-art performance.

  15. Cloud Computing and Multi Agent System to improve Learning Object Paradigm

    Directory of Open Access Journals (Sweden)

    Ana B. Gil

    2015-05-01

    Full Text Available The paradigm of Learning Object provides Educators and Learners with the ability to access an extensive number of learning resources. To do so, this paradigm provides different technologies and tools, such as federated search platforms and storage repositories, in order to obtain information ubiquitously and on demand. However, the vast amount and variety of educational content, which is distributed among several repositories, and the existence of various and incompatible standards, technologies and interoperability layers among repositories, constitutes a real problem for the expansion of this paradigm. This study presents an agent-based architecture that uses the advantages provided by Cloud Computing platforms to deal with the open issues on the Learning Object paradigm.

  16. Children’s comprehension of informational text: Reading, engaging, and learning

    Directory of Open Access Journals (Sweden)

    Linda BAKER

    2011-11-01

    Full Text Available The Reading, Engaging, and Learning project (REAL investigated whether a classroom intervention that enhanced young children's experience with informational books would increase reading achievement and engagement. Participants attended schools serving low income neighborhoods with 86% African American enrollment. The longitudinal study spanned second through fourth grades. Treatment conditions were: (1 Text Infusion/Reading for Learning Instruction -- students were given greater access to informational books in their classroom libraries and in reading instruction; (2 Text Infusion Alone -- the same books were provided but teachers were not asked to alter their instruction; (3 Traditional Instruction -- students experienced business as usual in the classroom. Children were assessed each year on measures of reading and reading engagement, and classroom instructional practices were observed. On most measures, the informational text infusion intervention did not yield differential growth over time. However, the results inform efforts to increase children’s facility with informational text in the early years in order to improve reading comprehension.

  17. Assessing Program Learning Objectives to Improve Undergraduate Physics Education

    Science.gov (United States)

    Menke, Carrie

    2014-03-01

    Our physics undergraduate program has five program learning objectives (PLOs) focusing on (1) physical principles, (2) mathematical expertise, (3) experimental technique, (4) communication and teamwork, and (5) research proficiency. One PLO is assessed each year, with the results guiding modifications in our curriculum and future assessment practices; we have just completed our first cycle of assessing all PLOs. Our approach strives to maximize the ease and applicability of our assessment practices while maintaining faculty's flexibility in course design and delivery. Objectives are mapped onto our core curriculum with identified coursework collected as direct evidence. We've utilized mostly descriptive rubrics, applying them at the course and program levels as well as sharing them with the students. This has resulted in more efficient assessment that is also applicable to reaccreditation efforts, higher inter-rater reliability than with other rubric types, and higher quality capstone projects. We've also found that the varied quality of student writing can interfere with our assessment of other objectives. This poster outlines our processes, resources, and how we have used PLO assessment to strengthen our undergraduate program.

  18. Delivery of Learning Knowledge Objects Using Fuzzy Clustering

    Science.gov (United States)

    Sabitha, A. Sai; Mehrotra, Deepti; Bansal, Abhay

    2016-01-01

    e-Learning industry is rapidly changing and the current learning trends are based on personalized, social and mobile learning, content reusability, cloud-based and talent management. The learning systems have attained a significant growth catering to the needs of a wide range of learners, having different approaches and styles of learning. Objects…

  19. The Inclusion Potential of Student Production of Digital Learning Objects

    DEFF Research Database (Denmark)

    Levinsen, Karin Tweddell; Sørensen, Birgitte Holm

    2016-01-01

    This account of the inclusion potential of students’ digital production is based on the large-scale research and development project Students’ Digital Production and Students as Learning Designers (2013–2015), funded by the Danish Ministry of Education. The target groups were primary and lower......-designed framework that accommodates and empowers students’ agency. The Danish parliament passed the Law of Inclusion In 2012 with the objective that by 2015, 96% of all students would be included in normal classes. Inclusion was not part of the initial research agenda, but this changed unexpectedly during...... the project. Specifically, students who did not participate or participated only sporadically in everyday school activities at the beginning of the project adopted new positions as participants and agents. We understand these changes as inclusive processes initiated by the combination of teacher...

  20. Development of Learning Virtual Objects as a Strategy to Foster Student Retention in Higher Education

    Directory of Open Access Journals (Sweden)

    Yois S. Pascuas Rengifo

    2015-12-01

    Full Text Available Rev.esc.adm.neg One of the problems that the Colombian higher education system is facing is the problem of student desertion, shwoing that a great amount of students leave their university studies during the first semesters. For this reason, the National Education Ministry and Universidad de la Amazonia implement a new strategy to foster student retention and graduation through academic levelling. This paper shows eight learning virtual objects from different learning áreas, applying technological tolos to design didactic interactive and creative environments.

  1. Discriminative object tracking via sparse representation and online dictionary learning.

    Science.gov (United States)

    Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

    2014-04-01

    We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

  2. Personalized Learning Objects Recommendation Based on the Semantic-Aware Discovery and the Learner Preference Pattern

    Science.gov (United States)

    Wang, Tzone I; Tsai, Kun Hua; Lee, Ming Che; Chiu, Ti Kai

    2007-01-01

    With vigorous development of the Internet, especially the web page interaction technology, distant E-learning has become more and more realistic and popular. Digital courses may consist of many learning units or learning objects and, currently, many learning objects are created according to SCORM standard. It can be seen that, in the near future,…

  3. AN ANALYSIS ON USAGE PREFERENCES OF LEARNING OBJECTS AND LEARNING OBJECT REPOSITORIES AMONG PRE-SERVICE TEACHERS

    Directory of Open Access Journals (Sweden)

    Amirul ISLAM

    2014-04-01

    Full Text Available This study draws on the experience of a cohort of 22 students from 09 tutorial centers enrolled in a Master of Education (M Ed distance learning program administered by the Bangladesh Open University (BOU. It's purpose is to locate the aims and philosophies of distance learning within the experiences of actual distance learners in order to see if learners' needs were being met by the program and to obtain a fuller understanding of core aspects of distance education. The study found that students were, on the whole, satisfied with the course materials, the choice of modules, assignment feedback, and length of time given to complete the assignments, but significant problems surfaced regarding issues of student support, and access to and provision of resource materials. Arguably, these are issues intrinsic to the successful provision of distance learning courses, and the results both concord with aspects of the research literature (Burge & Howard, 1990; Chen, 1997; Hyland, 2001; Morgan, 1995; Robinson, 1995; Simpson, 2000; Tait, 2000 and raise some interesting questions regarding the provision of distance education and its ability to meet the needs of learners

  4. Two-way text messaging: an interactive mobile learning environment in higher education

    OpenAIRE

    Premadasa, H. K. Salinda; Meegama, R. G. N.

    2016-01-01

    Short messaging service (SMS) is perhaps the most popular mobile technology prevalent among students in higher education due to its ubiquitous nature and the capability of two-way communication. However, a major limitation in two-way text messaging is sending back a part of received data with the reply message. This limitation results in users of a mobile learning environment being unable to reply back to the correct destination. This article presents a two-way text messaging system that can ...

  5. The Interrelations between Diagrammatic Representations and Verbal Explanations in Learning from Social Science Texts.

    Science.gov (United States)

    Guri-Rozenblit, Sarah

    1988-01-01

    Describes study that examined the instructional effectiveness of abstract diagrams and verbal explanations in learning from social science texts. The control and treatment groups of adult learners at Everyman's University (Israel) are described, verbal and visual aptitude tests are explained, and results are analyzed. (25 references) (Author/LRW)

  6. Place as Text: Approaches to Active Learning. 2nd Edition. National Collegiate Honors Council Monograph Series

    Science.gov (United States)

    Braid, Bernice, Ed.; Long, Ada, Ed.

    2010-01-01

    The decade since publication of "Place as Text: Approaches to Active Learning" has seen an explosion of interest and productivity in the field of experiential education. This monograph presents a story of an experiment and a blueprint of sorts for anyone interested in enriching an existing program or willing to experiment with pedagogy…

  7. Teachers' Beliefs, Instructional Behaviors, and Students' Engagement in Learning from Texts with Instructional Pictures

    Science.gov (United States)

    Schroeder, Sascha; Richter, Tobias; McElvany, Nele; Hachfeld, Axinja; Baumert, Jurgen; Schnotz, Wolfgang; Horz, Holger; Ullrich, Mark

    2011-01-01

    This study investigated the relations between teachers' pedagogical beliefs and students' self-reported engagement in learning from texts with instructional pictures. Participants were the biology, geography, and German teachers of 46 classes (Grades 5-8) and their students. Teachers' instructional behaviors and students' engagement in learning…

  8. Learning to Queer Text: Epiphanies from a Family Critical Literacy Practice

    Science.gov (United States)

    McClung, Nicola A.

    2018-01-01

    Critical literacy provides the opportunity to queer picture books and challenge normative depictions of family. In this autoethnography, the author describes her 4-year-old's journey of learning to talk back to texts as she actively constructs a better, more just world. The author argues that a critical literacy tool kit is vital to every child's…

  9. Learning Nanotechnology with Texts and Comics: The Impacts on Students of Different Achievement Levels

    Science.gov (United States)

    Lin, Shu-Fen; Lin, Huann-shyang

    2016-01-01

    Comics are popular with adolescents because of their features of humor, narrative, and visual imagery. The purposes of this study were to examine the learning outcomes and emotional perceptions of reading a science comic book and a science text booklet for students of different levels of achievement, and to explore the main factors of the two…

  10. Read-Aloud Accommodations, Expository Text, and Adolescents with Learning Disabilities

    Science.gov (United States)

    Meyer, Nancy K.; Bouck, Emily C.

    2017-01-01

    Adolescents with learning disabilities in reading have difficulties with reading and understanding difficult gradelevel curricular material. One frequently used method of support is using read-aloud accommodations, which can be live read-alouds or text-to-speech (TTS) read-alouds. A single case alternating treatment design was used to examine the…

  11. Reading Multimodal Texts for Learning – a Model for Cultivating Multimodal Literacy

    Directory of Open Access Journals (Sweden)

    Kristina Danielsson

    2016-08-01

    Full Text Available The re-conceptualisation of texts over the last 20 years, as well as the development of a multimodal understanding of communication and representation of knowledge, has profound consequences for the reading and understanding of multimodal texts, not least in educational contexts. However, if teachers and students are given tools to “unwrap” multimodal texts, they can develop a deeper understanding of texts, information structures, and the textual organisation of knowledge. This article presents a model for working with multimodal texts in education with the intention to highlight mutual multimodal text analysis in relation to the subject content. Examples are taken from a Singaporean science textbook as well as a Chilean science textbook, in order to demonstrate that the framework is versatile and applicable across different cultural contexts. The model takes into account the following aspects of texts: the general structure, how different semiotic resources operate, the ways in which different resources are combined (including coherence, the use of figurative language, and explicit/implicit values. Since learning operates on different dimensions – such as social and affective dimensions besides the cognitive ones – our inclusion of figurative language and values as components for textual analysis is a contribution to multimodal text analysis for learning.

  12. Object tracking by occlusion detection via structured sparse learning

    KAUST Repository

    Zhang, Tianzhu

    2013-06-01

    Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object\\'s track. This is the case when significant occlusion occurs. To accommodate for non-sparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that our tracker consistently outperforms the state-of-the-art. © 2013 IEEE.

  13. Learning to Appraise the Quality of Qualitative Research Articles: A Contextualized Learning Object for Constructing Knowledge

    Science.gov (United States)

    Chenail, Ronald J.

    2011-01-01

    Helping beginning qualitative researchers critically appraise qualitative research articles is a common learning objective for introductory methodology courses. To aid students in achieving competency in appraising the quality of qualitative research articles, a multi-part activity incorporating the Critical Appraisal Skills Programme's (CASP)…

  14. Multimedia Glosses and Their Effect on L2 Text Comprehension and Vocabulary Learning

    Directory of Open Access Journals (Sweden)

    Iñigo Yanguas

    2009-06-01

    Full Text Available The present study investigates the effects that different types of multimedia glosses, namely textual, pictorial, and textual + pictorial, have on text comprehension and vocabulary learning when the goal is exclusively comprehension of a computerized text. This study is based on the theoretical framework of attention, which maintains that attention is critical in the acquisition process of an L2 (Robinson, 1995; Schmidt, 1995, 2001; Tomlin and Villa, 1994. Ninety-four participants read a text under one of four gloss conditions while asked to think aloud. This study investigated whether any of the conditions promoted noticing and whether this noticing led to better comprehension of the text and learning of the target vocabulary words. Reading comprehension, recognition, and production measures were utilized in a pre-post test design. Results of quantitative and qualitative analyses of the data gathered showed first that all multimedia gloss groups noticed and recognized significantly more of the target words than the control group. Second, no significant differences were found among any of the groups in production of the target vocabulary items. Finally, regarding comprehension, results showed that the combination gloss group significantly outperformed all other groups. These results confirm that the multimedia glosses under investigation have a different effect on comprehension and vocabulary learning respectively.

  15. Two-way text messaging: an interactive mobile learning environment in higher education

    Directory of Open Access Journals (Sweden)

    H.K. Salinda Premadasa

    2016-11-01

    Full Text Available Short messaging service (SMS is perhaps the most popular mobile technology prevalent among students in higher education due to its ubiquitous nature and the capability of two-way communication. However, a major limitation in two-way text messaging is sending back a part of received data with the reply message. This limitation results in users of a mobile learning environment being unable to reply back to the correct destination. This article presents a two-way text messaging system that can be integrated into a learning management system (LMS to provide an interactive learning experience to the user community. Initially, a database is integrated into the LMS that holds message information such as recipient's phone number, message body and user data header. A specific port associated with the SMS is used to conceal and exchange data of a particular course unit. Subsequently, software in the student's mobile device captures this message and sends back the reply message to the appropriate course unit allowing both teachers and students to view messages sent and replies received pertaining to a particular course. Results indicate the educational impact of the proposed system in improving the learning environment and benefits it offers to the community in a campus-wide implementation.

  16. Activities Joining Learning Objectives to Assessments in Introductory Astronomy

    Science.gov (United States)

    Palen, Stacy E.; Larson, Ana M.

    2015-01-01

    In recent years, accreditation boards and other governing bodies have been pushing hard for explicit learning goals and quantitative measures of assessment for general education courses such as Astronomy 101. This added assessment burden can be problematic, especially for harried adjuncts teaching multiple courses at multiple institutions. It would be helpful to have a field-tested set of combined hands-on activities and assessment tools that help instructors meet these assessment requirements. The authors have produced just such a set. We have been using hands-on activities in our classrooms for more than 15 years. These activities require no special equipment or preparation and can be completed within an hour by most students working in groups of two or three. The sections of each activity are arranged in steps, guiding the students from initial knowledge-level questions or practice to a final evaluation or synthesis of what they have just accomplished. Students thus get practice thinking at higher cognitive levels. A recent addition to these activities is the inclusion of formalized learning objectives and accompanying pre- and post-activity questions. The pre-activity questions address common misconceptions, relate familiar analogous terrestrial examples to the activity, and act as a brief refresher meta-concepts like scale factors, measurements, and basic mathematics review. The post-activity questions review the most important concepts introduced in the activity. We present a number of examples as well as a summary as to how we have initiated their use in a large lecture setting of 300 students, in smaller classrooms of 15 students, and in a community college online course.

  17. A Synthesis of Research on Informational Text Reading Interventions for Elementary Students With Learning Disabilities.

    Science.gov (United States)

    Ciullo, Stephen; Lo, Yu-Ling Sabrina; Wanzek, Jeanne; Reed, Deborah K

    2016-01-01

    This research synthesis was conducted to understand the effectiveness of interventions designed to improve learning from informational text for students with learning disabilities in elementary school (K-5). The authors identified 18 studies through a comprehensive search. The interventions were evaluated to determine treatment effects and to understand implementation and methodological variables that influenced outcomes. Moderate to large effect sizes on researcher-developed measures for cognitive strategy interventions were reported. Interventions that utilized graphic organizers as study guides to support social studies learning were also associated with improved outcomes. The findings are considered within the context of limited implementation of standardized measures. The authors extend findings from previous research by reporting a paucity of interventions to enhance higher-level cognitive and comprehension skills. The majority of reviewed studies targeted fact acquisition and main idea identification, and overall encouraging findings were noted for these skills. Implications for future research are discussed. © Hammill Institute on Disabilities 2014.

  18. Special Aspects of Learning Objectives Design for Disciplines in Engineering Education

    Directory of Open Access Journals (Sweden)

    Yu. B. Tsvetkov

    2015-01-01

    Full Text Available The article is devoted to a problem of learning objectives design for disciplines in engineering education. It is shown that the system of well defined objectives can form a basis of discipline content analysis, acquisition control and improvement.The detailed defining of clear objectives and designing forms and content of objectives which allow to estimate their achievement are considered.For this purpose the objectives should consider the level of learners, to designate result which they will be able to show after training, conditions and how well they will be able to make it.Some examples of objective formulations are provided which allow to show in an explicit form the results reached by a learner.It is shown that cognitive process dimension can be divided into groups of initial level of thinking (to remember, understand, apply and thinking of high level (to analyze, estimate, create.Thus knowledge dimension include the factual, conceptual, procedural and metacognitive knowledges.On the basis of cognitive process dimension and knowledge dimension in engineering education it is offered to form system of learning objectives on the basis of their twodimensional classification - taxonomy.Objectives examples for engineering discipline are given. They consider conditions of their achievement and criteria of execution for various combinations of cognitive process dimension and levels of knowledge dimension.For some engineering disciplines examples of learning objectives are formulated including their achievement and criterion of execution of the corresponding actions.The given results can form a basis for design of learning objectives at realization of a competence approach in modern engineering education.Further work in this direction preplan the analysis and approbation of two-dimensional matrix applicability for objectives design on examples of various engineering disciplines.It is of profound importance to use matrixes of well defined

  19. Developing Goals and Objectives for Gameplay and Learning

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2014-01-01

    This chapter introduces goals in games and then potential differences between learning goals and goalsin games, as well as the difficulties that may occur when implementing learning goals in games....

  20. Why Sketching May Aid Learning From Science Texts: Contrasting Sketching With Written Explanations.

    Science.gov (United States)

    Scheiter, Katharina; Schleinschok, Katrin; Ainsworth, Shaaron

    2017-10-01

    The goal of this study was to explore two accounts for why sketching during learning from text is helpful: (1) sketching acts like other constructive strategies such as self-explanation because it helps learners to identify relevant information and generate inferences; or (2) that in addition to these general effects, sketching has more specific benefits due to the pictorial representation that is constructed. Seventy-three seventh-graders (32 girls, M = 12.82 years) were first taught how to either create sketches or self-explain while studying science texts. During a subsequent learning phase, all students were asked to read an expository text about the greenhouse effect. Finally, they were asked to write down everything they remembered and then answer transfer questions. Strategy quality during learning was assessed as the number of key concepts that had either been sketched or mentioned in the self-explanations. The results showed that at an overall performance level there were only marginal group differences. However, a more in-depth analysis revealed that whereas no group differences emerged for students implementing either strategy poorly, the sketching group clearly outperformed the self-explanation group for students who applied the strategies with higher quality. Furthermore, higher sketching quality was strongly related to better learning outcomes. Thus, the study's results are more in line with the second account: Sketching can have a beneficial effect on learning above and beyond generating written explanations; at least, if well deployed. Copyright © 2017 Cognitive Science Society, Inc.

  1. Data quality objectives lessons learned for tank waste characterization

    International Nuclear Information System (INIS)

    Eberlein, S.J.

    1996-01-01

    The tank waste characterization process is an integral part of the overall effort to control the hazards associated with radioactive wastes stored in underground tanks at the Hanford Reservation. The programs involved in the characterization of the wastes are employing Data Quality Objective (DQO) process in all information and data collection activities. The DQO process is used by the programs to address an issue or problem rather than a specific sampling event. Practical limits do not always allow for precise characterization of a tank or the implementation of the DQO process. Because of the flexibility of the DQO process, it can be used as a tool for sampling and analysis of the underground waste storage tanks. The iterative nature of the DQO process allows it to be used as additional information is claimed or lessons are learned concerning an issue or problem requiring sampling and analysis of tank waste. In addition, the application of DQO process forces alternative actions to be considered when precise characterization of a tank or the full implementation of the DQO process is not practical

  2. DROpS: an object of learning in computer simulation of discrete events

    Directory of Open Access Journals (Sweden)

    Hugo Alves Silva Ribeiro

    2015-09-01

    Full Text Available This work presents the “Realistic Dynamics Of Simulated Operations” (DROpS, the name given to the dynamics using the “dropper” device as an object of teaching and learning. The objective is to present alternatives for professors teaching content related to simulation of discrete events to graduate students in production engineering. The aim is to enable students to develop skills related to data collection, modeling, statistical analysis, and interpretation of results. This dynamic has been developed and applied to the students by placing them in a situation analogous to a real industry, where various concepts related to computer simulation were discussed, allowing the students to put these concepts into practice in an interactive manner, thus facilitating learning

  3. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

    Directory of Open Access Journals (Sweden)

    Monica Villaverde

    2015-11-01

    Full Text Available The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

  4. Construction and validation of a virtual learning object on intestinal elimination stoma

    Directory of Open Access Journals (Sweden)

    Cecílio Soares Rodrigues Braga

    Full Text Available Objective.To construct and validate a virtual learning object (VLO on intestinal elimination stoma. Methods. Applied, descriptive and quantitative study. In 2014, eight stoma therapists and eight experts in computer science took part of the research. The VLO included four steps: i planning, ii construction of VLO and changes of content; iii development of dynamic, and iv conclusion and analysis. The VLO was inserted into the Moodle virtual learning environment. The ergonomic and pedagogical validation of the VLO was performed. Results. The experts appreciated the VLO satisfactorily, and scored it between good and full agreement. Conclusion. The VLO on intestinal elimination stoma is a tool that can be implemented at undergraduate programs in nursing and continuing education programs for nurses in clinical practice, contributing significantly to improve the theoretical skills necessary for the care of ostomized people safely, with quality and enabling self-care.

  5. Using Machine Learning for Sentiment and Social Influence Analysis in Text

    OpenAIRE

    Kolog, Emmanuel Awuni; Montero, Calkin Suero; Toivonen, Tapani

    2017-01-01

    Students’ academic achievement is largely driven by their social phenomena, which is shaped by social influence and opinion dynamics. In this paper, we employed a machine learning technique to detect social influence and sentiment in text-based students’ life stories. The life stories were first pre-processed and clustered using k-means with euclidean distance. After that, we identified domestic, peer and school staff as the main influences on students’ academic development. The various influ...

  6. NetiNeti: discovery of scientific names from text using machine learning methods

    Directory of Open Access Journals (Sweden)

    Akella Lakshmi

    2012-08-01

    Full Text Available Abstract Background A scientific name for an organism can be associated with almost all biological data. Name identification is an important step in many text mining tasks aiming to extract useful information from biological, biomedical and biodiversity text sources. A scientific name acts as an important metadata element to link biological information. Results We present NetiNeti (Name Extraction from Textual Information-Name Extraction for Taxonomic Indexing, a machine learning based approach for recognition of scientific names including the discovery of new species names from text that will also handle misspellings, OCR errors and other variations in names. The system generates candidate names using rules for scientific names and applies probabilistic machine learning methods to classify names based on structural features of candidate names and features derived from their contexts. NetiNeti can also disambiguate scientific names from other names using the contextual information. We evaluated NetiNeti on legacy biodiversity texts and biomedical literature (MEDLINE. NetiNeti performs better (precision = 98.9% and recall = 70.5% compared to a popular dictionary based approach (precision = 97.5% and recall = 54.3% on a 600-page biodiversity book that was manually marked by an annotator. On a small set of PubMed Central’s full text articles annotated with scientific names, the precision and recall values are 98.5% and 96.2% respectively. NetiNeti found more than 190,000 unique binomial and trinomial names in more than 1,880,000 PubMed records when used on the full MEDLINE database. NetiNeti also successfully identifies almost all of the new species names mentioned within web pages. Conclusions We present NetiNeti, a machine learning based approach for identification and discovery of scientific names. The system implementing the approach can be accessed at http://namefinding.ubio.org.

  7. Axiomatic Ontology Learning Approaches for English Translation of the Meaning of Quranic Texts

    Directory of Open Access Journals (Sweden)

    Saad Saidah

    2017-01-01

    Full Text Available Ontology learning (OL is the computational task of generating a knowledge base in the form of an ontology, given an unstructured corpus in natural language (NL. While most works in the field of ontology learning have been primarily based on a statistical approach to extract lightweight OL, very few attempts have been made to extract axiomatic OL (called heavyweight OL from NL text documents. Axiomatic OL supports more precise formal logic-based reasoning when compared to lightweight OL. Lexico-syntactic pattern matching and statisticsal one cannot lead to very accurate learning, mostly because of several linguistic nuances in the NL. Axiomatic OL is an alternative methodology that has not been explored much, where a deep linguistics analysis in computational linguistics is used to generate formal axioms and definitions instead of simply inducing a taxonomy. The ontology that is created not only stores the information about the application domain in explicit knowledge, but also can deduce the implicit knowledge from this ontology. This research will explore the English translation of the meaning of Quranic texts.

  8. Time to Engage? Texting to Support and Enhance First Year Undergraduate Learning

    Directory of Open Access Journals (Sweden)

    Geraldine Jones

    2009-04-01

    Full Text Available In this paper we discuss a case study investigating how the academic and personal development of first year students on an undergraduate sports education degree can be supported and enhanced with mobile SMS communication. SMS-based technologies were introduced in response to students’ particular needs (in transition to Higher Education and characteristics (‘digital natives’. Despite being unaccustomed to using their mobile phones for academic study, students willingly participated in SMS communication with their tutor via a texting management service. Drawing on evidence from two student surveys, focus groups and a tutor’s journal, we illustrate the potential that mobile SMS communication has to link and establish continuity between face to face teaching sessions and online learning activities in the Virtual Learning Environment (VLE. Many students perceived the SMS communication to have had a positive impact on their management of study time. We link our findings with the existing literature and argue that mobile text based communication has the potential to support the development of time management skills, an important component of self regulatory learning, a skill which has been shown to be key in making a successful transition.

  9. Mobile Message Services Using Text, Audio or Video for Improving the Learning Infrastructure in Higher Education

    Directory of Open Access Journals (Sweden)

    Björn Olof Hedin

    2006-06-01

    Full Text Available This study examines how media files sent to mobile phones can be used to improve education at universities, and describes a prototype implement of such a system using standard components. To accomplish this, university students were equipped with mobile phones and software that allowed teachers to send text-based, audio-based and video-based messages to the students. Data was collected using questionnaires, focus groups and log files. The conclusions were that students preferred to have information and learning content sent as text, rather than audio or video. Text messages sent to phones should be no longer than 2000 characters. The most appreciated services were notifications of changes in course schedules, short lecture introductions and reminders. The prototype showed that this functionality is easy to implement using standard components.

  10. Learning from Objects: A Future for 21st Century Urban Arts Education

    Science.gov (United States)

    Lasky, Dorothea

    2009-01-01

    In this technological age, where mind and body are increasingly disconnected in the classroom, object-based learning--along with strong museum-school partnerships--provide many benefits for student learning. In this article, the author first outlines some of the special mind-body connections that object-based learning in museums affords learners…

  11. Advanced technology for the reuse of learning objects in a course-management system

    NARCIS (Netherlands)

    Strijker, A.; Collis, Betty

    2005-01-01

    The creation, labelling, use, and re-use of learning objects is an important area of development involving learning technology. In the higher education context, instructors typically use a course management system (CMS) to organize and manage their own learning objects. The needs and practices of

  12. Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning

    DEFF Research Database (Denmark)

    Aakerberg, Andreas; Nasrollahi, Kamal; Heder, Thomas

    2018-01-01

    Augmenting RGB images with depth information is a well-known method to significantly improve the recognition accuracy of object recognition models. Another method to im- prove the performance of visual recognition models is ensemble learning. However, this method has not been widely explored...... in combination with deep convolutional neural network based RGB-D object recognition models. Hence, in this paper, we form different ensembles of complementary deep convolutional neural network models, and show that this can be used to increase the recognition performance beyond existing limits. Experiments...

  13. Educational MOO: Text-Based Virtual Reality for Learning in Community. ERIC Digest.

    Science.gov (United States)

    Turbee, Lonnie

    MOO stands for "Multi-user domain, Object-Oriented." Early multi-user domains, or "MUDs," began as net-based dungeons-and-dragons type games, but MOOs have evolved from these origins to become some of cyberspace's most fascinating and engaging online communities. MOOs are social environments in a text-based virtual reality…

  14. Conformance Testing, the Elixer within the Chain for Learning Scenarios and Objects

    NARCIS (Netherlands)

    Nadolski, Rob; O'Neill, Owen; Vegt van der, Wim; Koper, Rob

    2006-01-01

    The chain for learning scenarios and learning objects includes five iterative links: (i) development, (ii) publication, (iii) making resources searchable and reusable and (iv) facilitating their arrangement (v) towards a runnable unit of learning. The use of e-learning specifications and

  15. A Novel Text Clustering Approach Using Deep-Learning Vocabulary Network

    Directory of Open Access Journals (Sweden)

    Junkai Yi

    2017-01-01

    Full Text Available Text clustering is an effective approach to collect and organize text documents into meaningful groups for mining valuable information on the Internet. However, there exist some issues to tackle such as feature extraction and data dimension reduction. To overcome these problems, we present a novel approach named deep-learning vocabulary network. The vocabulary network is constructed based on related-word set, which contains the “cooccurrence” relations of words or terms. We replace term frequency in feature vectors with the “importance” of words in terms of vocabulary network and PageRank, which can generate more precise feature vectors to represent the meaning of text clustering. Furthermore, sparse-group deep belief network is proposed to reduce the dimensionality of feature vectors, and we introduce coverage rate for similarity measure in Single-Pass clustering. To verify the effectiveness of our work, we compare the approach to the representative algorithms, and experimental results show that feature vectors in terms of deep-learning vocabulary network have better clustering performance.

  16. The Role of Reusable Learning Objects in Occupational Therapy Entry-Level Education

    Directory of Open Access Journals (Sweden)

    Bryan M. Gee

    2014-10-01

    Full Text Available Out of early research, Cisco Systems (1999 have built an impressive foundation that advocates for reusable learning objects (RLOs. As the need for online methods for delivering both formal and informal educational content has increased, the prospect of greater influence through carefully constructed RLOs has grown. RLOs are any digital resource that can be used and reused to enhance online learning. RLOs typically are small, discrete, self-contained digital objects that may be sequenced, combined, and used within a variety of instructional activities. RLOs have been implemented in nursing, pharmacy, and physician assistant programs. However, there is a lack of literature regarding RLOs in occupational therapy education. An attitudinal survey was administered to occupational therapy students after they had used an RLO focused on goal writing. Student preferences toward RLO content, instructional design, and eLearning were generally positive. Nearly three-quarters of the students who responded to the survey indicated that the RLO presented was beneficial. All respondents noted that they would use the RLO for future occupational therapy courses. It is argued that incorporating RLOs offers a cost-effective, efficient learning tool, and also adds credibility to the given curriculum program as being innovative with instructing occupational-therapy related concepts.

  17. Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy

    Science.gov (United States)

    2017-01-01

    Background Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing professional development. Objective The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors’ professional performance in the United Kingdom. Methods We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians’ colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Results Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to “popular” (recall=.97), “innovator” (recall=.98), and “respected” (recall=.87) codes and was lower for the “interpersonal” (recall=.80) and “professional” (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as “respected,” “professional,” and “interpersonal” related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P.05). Conclusions Machine learning algorithms can classify open-text feedback

  18. Portal and repository for sharing mathematical learning objects

    NARCIS (Netherlands)

    Zanden, van der A.H.W.; Cuypers, H.; Luca, J.; Weippl, E.R.

    2008-01-01

    Now that Virtual Learning Environments are common within higher education in the Netherlands it is time to work with online validated informational resources. Technologies such as repositories are the systems to manage learning content but are most inconvenient in use. The national project NKBW aims

  19. Time-Contrastive Learning Based DNN Bottleneck Features for Text-Dependent Speaker Verification

    DEFF Research Database (Denmark)

    Sarkar, Achintya Kumar; Tan, Zheng-Hua

    2017-01-01

    In this paper, we present a time-contrastive learning (TCL) based bottleneck (BN) feature extraction method for speech signals with an application to text-dependent (TD) speaker verification (SV). It is well-known that speech signals exhibit quasi-stationary behavior in and only in a short interval......, and the TCL method aims to exploit this temporal structure. More specifically, it trains deep neural networks (DNNs) to discriminate temporal events obtained by uniformly segmenting speech signals, in contrast to existing DNN based BN feature extraction methods that train DNNs using labeled data...... to discriminate speakers or pass-phrases or phones or a combination of them. In the context of speaker verification, speech data of fixed pass-phrases are used for TCL-BN training, while the pass-phrases used for TCL-BN training are excluded from being used for SV, so that the learned features can be considered...

  20. The Development of the Virtual Learning Media of the Sacred Object Artwork

    Science.gov (United States)

    Nuanmeesri, Sumitra; Jamornmongkolpilai, Saran

    2018-01-01

    This research aimed to develop the virtual learning media of the sacred object artwork by applying the concept of the virtual technology in order to publicize knowledge on the cultural wisdom of the sacred object artwork. It was done by designing and developing the virtual learning media of the sacred object artwork for the virtual presentation.…

  1. Does the Arrangement of Embedded Text versus Linked Text in Homework Systems Make a Difference in Students Impressions, Attitudes, and Perceived Learning?

    Science.gov (United States)

    Zumalt, Caitlin J.; Williamson, Vickie M.

    2016-01-01

    Students in a first-semester general chemistry course at a large southwestern university completed a 3-week homework assignment using MindTap, a Cengage Learning product. MindTap is the first major electronic system that has homework questions embedded in the text, such that students read a short section of the textbook and then answer a question…

  2. Multi-agent system for Knowledge-based recommendation of Learning Objects

    Directory of Open Access Journals (Sweden)

    Paula Andrea RODRÍGUEZ MARÍN

    2015-12-01

    Full Text Available Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.

  3. Evaluation of a digital learning object (DLO) to support the learning process in radiographic dental diagnosis.

    Science.gov (United States)

    Busanello, F H; da Silveira, P F; Liedke, G S; Arús, N A; Vizzotto, M B; Silveira, H E D; Silveira, H L D

    2015-11-01

    Studies have shown that inappropriate therapeutic strategies may be adopted if crown and root changes are misdiagnosed, potentially leading to undesirable consequences. Therefore, the aim of this study was to evaluate a digital learning object, developed to improve skills in diagnosing radiographic dental changes. The object was developed using the Visual Basic Application (VBA) software and evaluated by 62 undergraduate students (male: 24 and female: 38) taking an imaging diagnosis course. Participants were divided in two groups: test group, which used the object and control group, which attended conventional classes. After 3 weeks, students answered a 10-question test and took a practice test to diagnose 20 changes in periapical radiographs. The results show that test group performed better that control group in both tests, with statistically significant difference (P = 0.004 and 0.003, respectively). In overall, female students were better than male students. Specific aspects of object usability were assessed using a structured questionnaire based on the System Usability Scale (SUS), with a score of 90.5 and 81.6 by male and female students, respectively. The results obtained in this study suggest that students who used the DLO performed better than those who used conventional methods. This suggests that the DLO may be a useful teaching tool for dentistry undergraduates, on distance learning courses and as a complementary tool in face-to-face teaching. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. The Initial Development of Object Knowledge by a Learning Robot.

    Science.gov (United States)

    Modayil, Joseph; Kuipers, Benjamin

    2008-11-30

    We describe how a robot can develop knowledge of the objects in its environment directly from unsupervised sensorimotor experience. The object knowledge consists of multiple integrated representations: trackers that form spatio-temporal clusters of sensory experience, percepts that represent properties for the tracked objects, classes that support efficient generalization from past experience, and actions that reliably change object percepts. We evaluate how well this intrinsically acquired object knowledge can be used to solve externally specified tasks including object recognition and achieving goals that require both planning and continuous control.

  5. Active learning in the lecture theatre using 3D printed objects [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    David P. Smith

    2016-06-01

    Full Text Available The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme’s active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student.

  6. Embedded or linked learning objects: Implications for content development, course design and classroom use

    Directory of Open Access Journals (Sweden)

    Gail Kopp

    2007-06-01

    Full Text Available This research explores the idea of embedding and linking to existing content in learning object repositories and investigates teacher-designer use of learning objects within one high school mathematics course in an online school. This qualitative case study supports and extends the learning object literature, and brings forward context-specific examples of issues around repository design, autonomy and self-containment, technical support and granularity. Moreover, these findings have implications for building learning objects and repositories that could better support teachers in their instructional design and pedagogical decision-making. Résumé : La présente recherche étudie la possibilité d’effectuer un emboîtement et d’établir des liens avec le contenu existant dans les référentiels sur les objets d’apprentissage et explore l’utilisation par les enseignants-concepteurs des objets d’apprentissage au sein d’un cours de mathématique du secondaire donné dans une école en ligne. Cette étude de cas qualitative appuie et vise la littérature sur les objets d’apprentissage et met en avant plan des exemples de questions touchant la conception de référentiels, l’autonomie et l’indépendance, le soutien technique et la granularité propres au contexte. De plus, ces conclusions ont des répercussions sur l’élaboration d’objets et de référentiels d’apprentissage qui pourraient mieux appuyer les enseignants dans le cadre de leur conception pédagogique et de leur prise de décision touchant l’enseignement.

  7. Active Prior Tactile Knowledge Transfer for Learning Tactual Properties of New Objects

    Directory of Open Access Journals (Sweden)

    Di Feng

    2018-02-01

    Full Text Available Reusing the tactile knowledge of some previously-explored objects (prior objects helps us to easily recognize the tactual properties of new objects. In this paper, we enable a robotic arm equipped with multi-modal artificial skin, like humans, to actively transfer the prior tactile exploratory action experiences when it learns the detailed physical properties of new objects. These experiences, or prior tactile knowledge, are built by the feature observations that the robot perceives from multiple sensory modalities, when it applies the pressing, sliding, and static contact movements on objects with different action parameters. We call our method Active Prior Tactile Knowledge Transfer (APTKT, and systematically evaluated its performance by several experiments. Results show that the robot improved the discrimination accuracy by around 10 % when it used only one training sample with the feature observations of prior objects. By further incorporating the predictions from the observation models of prior objects as auxiliary features, our method improved the discrimination accuracy by over 20 % . The results also show that the proposed method is robust against transferring irrelevant prior tactile knowledge (negative knowledge transfer.

  8. Object learning improves feature extraction but does not improve feature selection.

    Directory of Open Access Journals (Sweden)

    Linus Holm

    Full Text Available A single glance at your crowded desk is enough to locate your favorite cup. But finding an unfamiliar object requires more effort. This superiority in recognition performance for learned objects has at least two possible sources. For familiar objects observers might: 1 select more informative image locations upon which to fixate their eyes, or 2 extract more information from a given eye fixation. To test these possibilities, we had observers localize fragmented objects embedded in dense displays of random contour fragments. Eight participants searched for objects in 600 images while their eye movements were recorded in three daily sessions. Performance improved as subjects trained with the objects: The number of fixations required to find an object decreased by 64% across the 3 sessions. An ideal observer model that included measures of fragment confusability was used to calculate the information available from a single fixation. Comparing human performance to the model suggested that across sessions information extraction at each eye fixation increased markedly, by an amount roughly equal to the extra information that would be extracted following a 100% increase in functional field of view. Selection of fixation locations, on the other hand, did not improve with practice.

  9. Special issue on multi-objective reinforcement learning

    NARCIS (Netherlands)

    Drugan, Madalina; Wiering, Marco; Vamplew, Peter; Chetty, Madhu

    2017-01-01

    Many real-life problems involve dealing with multiple objectives. For example, in network routing the criteria may consist of energy consumption, latency, and channel capacity, which are in essence conflicting objectives. As in many problems there may be multiple (conflicting) objectives, there

  10. Occlusion detection via structured sparse learning for robust object tracking

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra

    2014-01-01

    occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our

  11. Object tracking by occlusion detection via structured sparse learning

    KAUST Repository

    Zhang, Tianzhu; Ghanem, Bernard; Xu, Changsheng; Ahuja, Narendra

    2013-01-01

    occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that our tracker

  12. Exploring the Effects of Multimedia Learning on Pre-Service Teachers' Perceived and Actual Learning Performance: The Use of Embedded Summarized Texts in Educational Media

    Science.gov (United States)

    Wu, Leon Yufeng; Yamanaka, Akio

    2013-01-01

    In light of the increased usage of instructional media for teaching and learning, the design of these media as aids to convey the content for learning can be crucial for effective learning outcomes. In this vein, the literature has given attention to how concurrent on-screen text can be designed using these media to enhance learning performance.…

  13. Libraries in Second Life: New Approaches to Education, Information Sharing, Learning Object Implementation, User Interactions and Collaborations

    Directory of Open Access Journals (Sweden)

    Susan Smith Nash

    2009-10-01

    Full Text Available Three-dimensional virtual worlds such as Second Life continue to expand the way they provide information, learning activities, and educational applications. This paper explores the types of learning activities that take place in Second Life and discusses how learning takes place, with a view toward developing effective instructional strategies. As learning objects are being launched in Second Life, new approaches to collaboration, interactivity, and cognition are being developed. Many learning-centered islands appeal to individuals who benefit from interaction with peers and instructors, and who can access learning objects such as information repositories, simulations, and interactive animations. The key advantages that Second Life offers include engaging and meaningful interaction with fellow learners, media-rich learning environments with embedded video, graphics, and interactive quizzes and assessments, an engaging environment for simulations such as virtual labs, and culturally inclusive immersive environments. However, because of the steep learning curve, technical difficulties, and cultural diversity, learners may become frustrated in Second Life. Since Second Life is social learning environment that emphasizes the creation of a self, effective learning requires step-by-step empowerment of that new, constructed self.

  14. Object Oriented Learning Objects in Online Education: A Framework and Example.

    Science.gov (United States)

    Rincon, Lilian; Parker, Drew

    Online learning is coming of age in both postsecondary education and industry. The courses now offered online range from kinesiology to mathematics to complete M.B.A. programs. The growing popularity of online education has created a need to reduce costs without diminishing the value of the edification. In response to this need, an instructional…

  15. Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

    Directory of Open Access Journals (Sweden)

    Ming Xue

    2014-02-01

    Full Text Available To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks.

  16. Text conception(s in context of semi-present Distance Learning (DL

    Directory of Open Access Journals (Sweden)

    Fabiana Komesu

    2013-02-01

    Full Text Available By following the example proposed by Corrêa (2011 in the investigation of texts produced by undergraduate and pre-undergraduate students in two different assessment, this work aims to approach “hidden” aspects in the teaching of writing at the university (Street, 2009, to reflections produced in the language field, in particular the ones referred as “socially assumed”, proposed by Voloshinov/Bakhtin (s/d: 1926. It is particularly important to investigate the conception of text in digital context, by means of the study of updated semiotic resources in the production of undergraduate students using a computer with internet access in the process of semi-present Distance Learning (DL. The collected material comprises 29 (twenty nine texts which were produced by students of the semi-present Pedagogy Course from Univesp (Universidade Virtual do Estado de São Paulo – Virtual University from the state of São Paulo, who were studying “Education and Language”, in 2010. This qualitative analysis aims to show that regarding the institution there is a prevalence of structural and procedural aspects for the accomplishment of the proposed activity and, regarding the undergraduate student it is noticed that the production is characterized by a traditional conception of text, mainly recognized by written verbal text, although the proposal prioritized the relation between verbal and non verbal language. Regarding discursive-linguistic studies, it is important to reflect about a text conception that privileges the integration of multiple semiosis by taking into account the socio-historical interlocution character established within utterances of others.

  17. Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy.

    Science.gov (United States)

    Gibbons, Chris; Richards, Suzanne; Valderas, Jose Maria; Campbell, John

    2017-03-15

    Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor's activity for the purposes of quality assurance, safety, and continuing professional development. The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors' professional performance in the United Kingdom. We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians' colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to "popular" (recall=.97), "innovator" (recall=.98), and "respected" (recall=.87) codes and was lower for the "interpersonal" (recall=.80) and "professional" (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as "respected," "professional," and "interpersonal" related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P.05). Machine learning algorithms can classify open-text feedback of doctor performance into multiple themes derived by human raters with high

  18. A Cognitive Skill Classification Based on Multi Objective Optimization Using Learning Vector Quantization for Serious Games

    Directory of Open Access Journals (Sweden)

    Moh. Aries Syufagi

    2013-09-01

    Full Text Available Nowadays, serious games and game technology are poised to transform the way of educating and training students at all levels. However, pedagogical value in games do not help novice students learn, too many memorizing and reduce learning process due to no information of player’s ability. To asses the cognitive level of player ability, we propose a Cognitive Skill Game (CSG. CSG improves this cognitive concept to monitor how players interact with the game. This game employs Learning Vector Quantization (LVQ for optimizing the cognitive skill input classification of the player. CSG is using teacher’s data to obtain the neuron vector of cognitive skill pattern supervise. Three clusters multi objective XE "multi objective"  target will be classified as; trial and error, carefully and, expert cognitive skill. In the game play experiments employ 33 respondent players demonstrates that 61% of players have high trial and error, 21% have high carefully, and 18% have high expert cognitive skill. CSG may provide information to game engine when a player needs help or when wanting a formidable challenge. The game engine will provide the appropriate tasks according to players’ ability. CSG will help balance the emotions of players, so players do not get bored and frustrated. 

  19. Cognitive diffusion model with user-oriented context-to-text recognition for learning to promote high level cognitive processes

    Directory of Open Access Journals (Sweden)

    Wu-Yuin Hwang

    2014-03-01

    Full Text Available There is a large number of studies on how to promote students’ cognitive processes and learning achievements through various learning activities supported by advanced learning technologies. However, not many of them focus on applying the knowledge that students learn in school to solve authentic daily life problems. This study aims to propose a cognitive diffusion model called User-oriented Context-to-Text Recognition for Learning (U-CTRL to facilitate and improve students’ learning and cognitive processes from lower levels (i.e., Remember and Understand to higher levels (i.e., Apply and above through an innovative approach, called User-Oriented Context-to-Text Recognition for Learning (U-CTRL. With U-CTRL, students participate in learning activities in which they capture the learning context that can be scanned and recognized by a computer application as text. Furthermore, this study proposes the use of an innovative model, called Cognitive Diffusion Model, to investigate the diffusion and transition of students’ cognitive processes in different learning stages including pre-schooling, after-schooling, crossing the chasm, and higher cognitive processing. Finally, two cases are presented to demonstrate how the U-CTRL approach can be used to facilitate student cognition in their learning of English and Natural science.

  20. Learning object-to-class kernels for scene classification.

    Science.gov (United States)

    Zhang, Lei; Zhen, Xiantong; Shao, Ling

    2014-08-01

    High-level image representations have drawn increasing attention in visual recognition, e.g., scene classification, since the invention of the object bank. The object bank represents an image as a response map of a large number of pretrained object detectors and has achieved superior performance for visual recognition. In this paper, based on the object bank representation, we propose the object-to-class (O2C) distances to model scene images. In particular, four variants of O2C distances are presented, and with the O2C distances, we can represent the images using the object bank by lower-dimensional but more discriminative spaces, called distance spaces, which are spanned by the O2C distances. Due to the explicit computation of O2C distances based on the object bank, the obtained representations can possess more semantic meanings. To combine the discriminant ability of the O2C distances to all scene classes, we further propose to kernalize the distance representation for the final classification. We have conducted extensive experiments on four benchmark data sets, UIUC-Sports, Scene-15, MIT Indoor, and Caltech-101, which demonstrate that the proposed approaches can significantly improve the original object bank approach and achieve the state-of-the-art performance.

  1. Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

    Science.gov (United States)

    Bravo, Àlex; Li, Tong Shu; Su, Andrew I; Good, Benjamin M; Furlong, Laura I

    2016-01-01

    Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources on drug adverse reactions. We present a new system for identification of drug side effects from the literature that combines three approaches: machine learning, rule- and knowledge-based approaches. This system has been developed to address the Task 3.B of Biocreative V challenge (BC5) dealing with Chemical-induced Disease (CID) relations. The first two approaches focus on identifying relations at the sentence-level, while the knowledge-based approach is applied both at sentence and abstract levels. The machine learning method is based on the BeFree system using two corpora as training data: the annotated data provided by the CID task organizers and a new CID corpus developed by crowdsourcing. Different combinations of results from the three strategies were selected for each run of the challenge. In the final evaluation setting, the system achieved the highest Recall of the challenge (63%). By performing an error analysis, we identified the main causes of misclassifications and areas for improving of our system, and highlighted the need of consistent gold standard data sets for advancing the state of the art in text mining of drug side effects.Database URL: https://zenodo.org/record/29887?ln¼en#.VsL3yDLWR_V. © The Author(s) 2016. Published by Oxford University Press.

  2. Refitting existing simulations to meet with new learning objectives

    DEFF Research Database (Denmark)

    Lainema, Timo; Henriksen, Thomas Duus; Saarinen, Eeli

    2012-01-01

    This paper discusses the application possibilities of business simulation games in teaching. By application possibilities we mean the different ways of arranging the learning sessions using the one and same simulation game. Thus, we are not discussing what kind of games should be built for certain...

  3. A Cognitive Skill Classification Based On Multi Objective Optimization Using Learning Vector Quantization for Serious Games

    Directory of Open Access Journals (Sweden)

    Moh. Aries Syufagi

    2011-12-01

    Full Text Available Nowadays, serious games and game technology are poised to transform the way of educating and training students at all levels. However, pedagogical value in games do not help novice students learn, too many memorizing and reduce learning process due to no information of player’s ability. To asses the cognitive level of player ability, we propose a Cognitive Skill Game (CSG. CSG improves this cognitive concept to monitor how players interact with the game. This game employs Learning Vector Quantization (LVQ for optimizing the cognitive skill input classification of the player. CSG is using teacher’s data to obtain the neuron vector of cognitive skill pattern supervise. Three clusters multi objective target will be classified as; trial and error, carefully and, expert cognitive skill. In the game play experiments using 33 respondent players demonstrates that 61% of players have high trial and error cognitive skill, 21% have high carefully cognitive skill, and 18% have high expert cognitive skill. CSG may provide information to game engine when a player needs help or when wanting a formidable challenge. The game engine will provide the appropriate tasks according to players’ ability. CSG will help balance the emotions of players, so players do not get bored and frustrated. Players have a high interest to finish the game if the player is emotionally stable. Interests in the players strongly support the procedural learning in a serious game.

  4. OBJECTIVE STRUCTURED PRACTICAL EXAMINATION AS A LEARNING AND EVALUATION TOOL FOR BIOCHEMISTRY- FIRST EXPERIENCE

    Directory of Open Access Journals (Sweden)

    Vidyabati Devi Rajkumari

    2017-06-01

    Full Text Available BACKGROUND Assessment plays an important role in helping learners identify their own learning needs. The objective structured practical examination assesses practical skills in an objective and structured manner with direct observation of the students’ performance during planned clinical test. The aim of the study is to evaluate OSPE as a method of learning and formative assessment to the practical skill and to explore faculty perception of OSPE as a learning and assessment tool. MATERIALS AND METHODS A total of 98 students of first year MBBS student admitted for 2015-16 batch of Jawaharlal Nehru Institute of Medical Sciences, Imphal, were the subjects for the study. Day one- Group A (1-50 students were evaluated by OSPE method of assessment. Day two- Group B (51-98 were evaluated by standard practical examination. To avoid examiners Bias on Day 3- Group C (51- 98 who were evaluated by SPE were evaluated by OSPE with minor variations. Group A underwent OSPE. Questionnaire was given to students after the assessment on the fourth day to get the feedback. RESULTS Independent sample t-test comparing mean percent scores of OSPE and SPE between the groups. There is no statistically significant difference in the mean percent scores for OSPE and SPE among the two groups. Paired sample t-test comparing mean percent scores of OSPE and SPE of group B students. The mean percentage score for OSPE is higher than the percentage scores obtained in SPE among the group B students, but the difference was not found to be statistically significant. The feedback from the students showed that more than 80% agreed that OSPE was less stressful to perform that it was a more objective assessment. CONCLUSION In conclusion, OSPE has several distinct advantages. From our first experience, we found that OSPE was more objective, measured practical skills better and eliminated examiner bias.

  5. Memory for Object Locations: Priority Effect and Sex Differences in Associative Spatial Learning

    Science.gov (United States)

    Cinan, Sevtap; Atalay, Deniz; Sisman, Simge; Basbug, Gokce; Dervent-Ozbek, Sevinc; Teoman, Dalga D.; Karagoz, Ayca; Karadeniz, A. Yezdan; Beykurt, Sinem; Suleyman, Hediye; Memis, H. Ozge; Yurtsever, Ozgur D.

    2007-01-01

    This paper reports two experiments conducted to examine priority effects and sex differences in object location memory. A new task of paired position-learning was designed, based on the A-B A-C paradigm, which was used in paired word learning. There were three different paired position-learning conditions: (1) positions of several different…

  6. The role of professional objects in technology-enhanced learning environments in higher education

    NARCIS (Netherlands)

    Zitter, I.I.; Bruijn, E. de; Simons, P.R.J.; Cate, Th.J. ten

    2010-01-01

    We study project-based, technology-enhanced learning environments in higher education, which should produce, by means of specific mechanisms, learning outcomes in terms of transferable knowledge and learning-, thinking-, collaboration- and regulation-skills. Our focus is on the role of objects from

  7. Analyzing the Quality of Students Interaction in a Distance Learning Object-Oriented Programming Discipline

    Science.gov (United States)

    Carvalho, Elizabeth Simão

    2015-01-01

    Teaching object-oriented programming to students in an in-classroom environment demands well-thought didactic and pedagogical strategies in order to guarantee a good level of apprenticeship. To teach it on a completely distance learning environment (e-learning) imposes possibly other strategies, besides those that the e-learning model of Open…

  8. 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,…

  9. INST7150 - Advanced Topics in Learning Object Design and Reuse, Fall 2005

    OpenAIRE

    Wiley, David

    2005-01-01

    This course is designed to help you understand and apply advanced topics in the design, creation, and reuse of learning objects. The course is structured around a practical, hands-on project using learning objects, intermingled with readings and discussion on a variety of topics.

  10. Cortical Dynamics of Contextually Cued Attentive Visual Learning and Search: Spatial and Object Evidence Accumulation

    Science.gov (United States)

    Huang, Tsung-Ren; Grossberg, Stephen

    2010-01-01

    How do humans use target-predictive contextual information to facilitate visual search? How are consistently paired scenic objects and positions learned and used to more efficiently guide search in familiar scenes? For example, humans can learn that a certain combination of objects may define a context for a kitchen and trigger a more efficient…

  11. The Sloan-C Pillars and Boundary Objects As a Framework for Evaluating Blended Learning

    Science.gov (United States)

    Laumakis, Mark; Graham, Charles; Dziuban, Chuck

    2009-01-01

    The authors contend that blended learning represents a boundary object; a construct that brings together constituencies from a variety of backgrounds with each of these cohorts defining the object somewhat differently. The Sloan-C Pillars (learning effectiveness, access, cost effectiveness, student satisfaction, and faculty satisfaction) provide…

  12. APA's Learning Objectives for Research Methods and Statistics in Practice: A Multimethod Analysis

    Science.gov (United States)

    Tomcho, Thomas J.; Rice, Diana; Foels, Rob; Folmsbee, Leah; Vladescu, Jason; Lissman, Rachel; Matulewicz, Ryan; Bopp, Kara

    2009-01-01

    Research methods and statistics courses constitute a core undergraduate psychology requirement. We analyzed course syllabi and faculty self-reported coverage of both research methods and statistics course learning objectives to assess the concordance with APA's learning objectives (American Psychological Association, 2007). We obtained a sample of…

  13. An Assistant for Loading Learning Object Metadata: An Ontology Based Approach

    Science.gov (United States)

    Casali, Ana; Deco, Claudia; Romano, Agustín; Tomé, Guillermo

    2013-01-01

    In the last years, the development of different Repositories of Learning Objects has been increased. Users can retrieve these resources for reuse and personalization through searches in web repositories. The importance of high quality metadata is key for a successful retrieval. Learning Objects are described with metadata usually in the standard…

  14. Teaching and Assessing Ethics as a Learning Objective: One School's Journey

    Science.gov (United States)

    Templin, Carl R.; Christensen, David

    2009-01-01

    This paper reports the results of a ten-year effort to establish ethics as a learning objective for all business students, to assess the effectiveness in achieving that learning objective and to incorporate ethical conduct as a part of the school's organizational culture. First, it addresses the importance of ethics instruction for all business…

  15. [Digital learning object for diagnostic reasoning in nursing applied to the integumentary system].

    Science.gov (United States)

    da Costa, Cecília Passos Vaz; Luz, Maria Helena Barros Araújo

    2015-12-01

    To describe the creation of a digital learning object for diagnostic reasoning in nursing applied to the integumentary system at a public university of Piaui. A methodological study applied to technological production based on the pedagogical framework of problem-based learning. The methodology for creating the learning object observed the stages of analysis, design, development, implementation and evaluation recommended for contextualized instructional design. The revised taxonomy of Bloom was used to list the educational goals. The four modules of the developed learning object were inserted into the educational platform Moodle. The theoretical assumptions allowed the design of an important online resource that promotes effective learning in the scope of nursing education. This study should add value to nursing teaching practices through the use of digital learning objects for teaching diagnostic reasoning applied to skin and skin appendages.

  16. Mirroring the Object of the Lesson: The Creative Process of Scriptural Rewriting as an Effective Practice for Teaching Sacred Texts

    Science.gov (United States)

    Palmer, Carmen

    2018-01-01

    This paper introduces Rewritten Scripture and scriptural rewriting as a creative process that, when mirrored in a teaching exercise, may serve as an effective practice in teaching sacred texts. Observing changes made between scripture and its rewriting may allow readers to identify different contexts among these texts. Furthermore, the act of…

  17. Construction and validation of clinical contents for development of learning objects

    Directory of Open Access Journals (Sweden)

    Flávia Tatiana Pedrolo Hortense

    Full Text Available ABSTRACT Objective: to describe the process of construction and validation of clinical contents for health learning objects, aimed at patients in the treatment of head and neck cancer. Method: descriptive, methodological study. The development of the script and the storyboard were based on scientific evidence and submitted to the appreciation of specialists for validation of content. The agreement index was checked quantitatively and the suggestions were qualitatively evaluated. Results: The items described in the roadmap were approved by 99% of expert experts. The suggestions for adjustments were inserted in their entirety in the final version. The free-marginal kappa statistical test, for multiple evaluators, presented value equal to 0.68%, granting a substantial agreement. Conclusion: The steps taken in the construction and validation of the content for the production of educational material for patients with head and neck cancer were adequate, relevant and suitable for use in other subjects.

  18. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

    Directory of Open Access Journals (Sweden)

    Jinmeng Rao

    2017-08-01

    Full Text Available The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

  19. "What is relevant in a text document?": An interpretable machine learning approach.

    Directory of Open Access Journals (Sweden)

    Leila Arras

    Full Text Available Text documents can be described by a number of abstract concepts such as semantic category, writing style, or sentiment. Machine learning (ML models have been trained to automatically map documents to these abstract concepts, allowing to annotate very large text collections, more than could be processed by a human in a lifetime. Besides predicting the text's category very accurately, it is also highly desirable to understand how and why the categorization process takes place. In this paper, we demonstrate that such understanding can be achieved by tracing the classification decision back to individual words using layer-wise relevance propagation (LRP, a recently developed technique for explaining predictions of complex non-linear classifiers. We train two word-based ML models, a convolutional neural network (CNN and a bag-of-words SVM classifier, on a topic categorization task and adapt the LRP method to decompose the predictions of these models onto words. Resulting scores indicate how much individual words contribute to the overall classification decision. This enables one to distill relevant information from text documents without an explicit semantic information extraction step. We further use the word-wise relevance scores for generating novel vector-based document representations which capture semantic information. Based on these document vectors, we introduce a measure of model explanatory power and show that, although the SVM and CNN models perform similarly in terms of classification accuracy, the latter exhibits a higher level of explainability which makes it more comprehensible for humans and potentially more useful for other applications.

  20. Objectivity

    CERN Document Server

    Daston, Lorraine

    2010-01-01

    Objectivity has a history, and it is full of surprises. In Objectivity, Lorraine Daston and Peter Galison chart the emergence of objectivity in the mid-nineteenth-century sciences--and show how the concept differs from its alternatives, truth-to-nature and trained judgment. This is a story of lofty epistemic ideals fused with workaday practices in the making of scientific images. From the eighteenth through the early twenty-first centuries, the images that reveal the deepest commitments of the empirical sciences--from anatomy to crystallography--are those featured in scientific atlases, the compendia that teach practitioners what is worth looking at and how to look at it. Galison and Daston use atlas images to uncover a hidden history of scientific objectivity and its rivals. Whether an atlas maker idealizes an image to capture the essentials in the name of truth-to-nature or refuses to erase even the most incidental detail in the name of objectivity or highlights patterns in the name of trained judgment is a...

  1. The company objects keep: Linking referents together during cross-situational word learning.

    Science.gov (United States)

    Zettersten, Martin; Wojcik, Erica; Benitez, Viridiana L; Saffran, Jenny

    2018-04-01

    Learning the meanings of words involves not only linking individual words to referents but also building a network of connections among entities in the world, concepts, and words. Previous studies reveal that infants and adults track the statistical co-occurrence of labels and objects across multiple ambiguous training instances to learn words. However, it is less clear whether, given distributional or attentional cues, learners also encode associations amongst the novel objects. We investigated the consequences of two types of cues that highlighted object-object links in a cross-situational word learning task: distributional structure - how frequently the referents of novel words occurred together - and visual context - whether the referents were seen on matching backgrounds. Across three experiments, we found that in addition to learning novel words, adults formed connections between frequently co-occurring objects. These findings indicate that learners exploit statistical regularities to form multiple types of associations during word learning.

  2. Applying CIPP Model for Learning-Object Management

    Science.gov (United States)

    Morgado, Erla M. Morales; Peñalvo, Francisco J. García; Martín, Carlos Muñoz; Gonzalez, Miguel Ángel Conde

    Although knowledge management process needs to receive some evaluation in order to determine their suitable functionality. There is not a clear definition about the stages where LOs need to be evaluated and the specific metrics to continuously promote their quality. This paper presents a proposal for LOs evaluation during their management for e-learning systems. To achieve this, we suggest specific steps for LOs design, implementation and evaluation into the four stages proposed by CIPP model (Context, Input, Process, Product).

  3. A Model for Semi-Automatic Composition of Educational Content from Open Repositories of Learning Objects

    Directory of Open Access Journals (Sweden)

    Paula Andrea Rodríguez Marín

    2014-04-01

    Full Text Available Learning objects (LOs repositories are important in building educational content and should allow search, retrieval and composition processes to be successfully developed to reach educational goals. However, such processes require so much time-consuming and not always provide the desired results. Thus, the aim of this paper is to propose a model for the semiautomatic composition of LOs, which are automatically recovered from open repositories. For the development of model, various text similarity measures are discussed, while for calibration and validation some comparison experiments were performed using the results obtained by teachers. Experimental results show that when using a value of k (number of LOs selected of at least 3, the percentage of similarities between the model and such made by experts exceeds 75%. To conclude, it can be established that the model proposed allows teachers to save time and effort for LOs selection by performing a pre-filter process.

  4. Exploring emerging learning needs: a UK-wide consultation on environmental sustainability learning objectives for medical education.

    Science.gov (United States)

    Walpole, Sarah C; Mortimer, Frances; Inman, Alice; Braithwaite, Isobel; Thompson, Trevor

    2015-12-24

    This study aimed to engage wide-ranging stakeholders and develop consensus learning objectives for undergraduate and postgraduate medical education. A UK-wide consultation garnered opinions of healthcare students, healthcare educators and other key stakeholders about environmental sustainability in medical education. The policy Delphi approach informed this study. Draft learning objectives were revised iteratively during three rounds of consultation: online questionnaire or telephone interview, face-to-face seminar and email consultation. Twelve draft learning objectives were developed based on review of relevant literature. In round one, 64 participants' median ratings of the learning objectives were 3.5 for relevance and 3.0 for feasibility on a Likert scale of one to four. Revisions were proposed, e.g. to highlight relevance to public health and professionalism. Thirty three participants attended round two. Conflicting opinions were explored. Added content areas included health benefits of sustainable behaviours. To enhance usability, restructuring provided three overarching learning objectives, each with subsidiary points. All participants from rounds one and two were contacted in round three, and no further edits were required. This is the first attempt to define consensus learning objectives for medical students about environmental sustainability. Allowing a wide range of stakeholders to comment on multiple iterations of the document stimulated their engagement with the issues raised and ownership of the resulting learning objectives.

  5. Exploring the impact of learning objects in middle school mathematics and science classrooms: A formative analysis

    Directory of Open Access Journals (Sweden)

    Robin H. Kay

    2008-12-01

    Full Text Available The current study offers a formative analysis of the impact of learning objects in middle school mathematics and science classrooms. Five reliable and valid measure of effectiveness were used to examine the impact of learning objects from the perspective of 262 students and 8 teachers (14 classrooms in science or mathematics. The results indicate that teachers typically spend 1-2 hours finding and preparing for learning-object based lesson plans that focus on the review of previous concepts. Both teachers and students are positive about the learning benefits, quality, and engagement value of learning objects, although teachers are more positive than students. Student performance increased significantly, over 40%, when learning objects were used in conjunction with a variety of teaching strategies. It is reasonable to conclude that learning objects have potential as a teaching tool in a middle school environment. L’impacte des objets d’apprentissage dans les classes de mathématique et de sciences à l’école intermédiaire : une analyse formative Résumé : Cette étude présente une analyse formative de l’impacte des objets d’apprentissage dans les classes de mathématique et de sciences à l’école intermédiaire. Cinq mesures de rendement fiables et valides ont été exploitées pour examiner l’effet des objets d’apprentissage selon 262 élèves et 8 enseignants (414 classes en science ou mathématiques. Les résultats indiquent que les enseignants passent typiquement 1-2 heures pour trouver des objets d’apprentissage et préparer les leçons associées qui seraient centrées sur la revue de concepts déjà vus en classe. Quoique les enseignants aient répondu de façon plus positive que les élèves, les deux groupes ont répondu positivement quant aux avantages au niveau de l’apprentissage, à la qualité ainsi qu’à la valeur motivationnelle des objets d’apprentissage. Le rendement des élèves aurait aussi augment

  6. Interactive Preference Learning of Utility Functions for Multi-Objective Optimization

    OpenAIRE

    Dewancker, Ian; McCourt, Michael; Ainsworth, Samuel

    2016-01-01

    Real-world engineering systems are typically compared and contrasted using multiple metrics. For practical machine learning systems, performance tuning is often more nuanced than minimizing a single expected loss objective, and it may be more realistically discussed as a multi-objective optimization problem. We propose a novel generative model for scalar-valued utility functions to capture human preferences in a multi-objective optimization setting. We also outline an interactive active learn...

  7. Using distant supervised learning to identify protein subcellular localizations from full-text scientific articles.

    Science.gov (United States)

    Zheng, Wu; Blake, Catherine

    2015-10-01

    Databases of curated biomedical knowledge, such as the protein-locations reflected in the UniProtKB database, provide an accurate and useful resource to researchers and decision makers. Our goal is to augment the manual efforts currently used to curate knowledge bases with automated approaches that leverage the increased availability of full-text scientific articles. This paper describes experiments that use distant supervised learning to identify protein subcellular localizations, which are important to understand protein function and to identify candidate drug targets. Experiments consider Swiss-Prot, the manually annotated subset of the UniProtKB protein knowledge base, and 43,000 full-text articles from the Journal of Biological Chemistry that contain just under 11.5 million sentences. The system achieves 0.81 precision and 0.49 recall at sentence level and an accuracy of 57% on held-out instances in a test set. Moreover, the approach identifies 8210 instances that are not in the UniProtKB knowledge base. Manual inspection of the 50 most likely relations showed that 41 (82%) were valid. These results have immediate benefit to researchers interested in protein function, and suggest that distant supervision should be explored to complement other manual data curation efforts. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Prognosis Essay Scoring and Article Relevancy Using Multi-Text Features and Machine Learning

    Directory of Open Access Journals (Sweden)

    Arif Mehmood

    2017-01-01

    Full Text Available This study develops a model for essay scoring and article relevancy. Essay scoring is a costly process when we consider the time spent by an evaluator. It may lead to inequalities of the effort by various evaluators to apply the same evaluation criteria. Bibliometric research uses the evaluation criteria to find relevancy of articles instead. Researchers mostly face relevancy issues while searching articles. Therefore, they classify the articles manually. However, manual classification is burdensome due to time needed for evaluation. The proposed model performs automatic essay evaluation using multi-text features and ensemble machine learning. The proposed method is implemented in two data sets: a Kaggle short answer data set for essay scoring that includes four ranges of disciplines (Science, Biology, English, and English language Arts, and a bibliometric data set having IoT (Internet of Things and non-IoT classes. The efficacy of the model is measured against the Tandalla and AutoP approach using Cohen’s kappa. The model achieves kappa values of 0.80 and 0.83 for the first and second data sets, respectively. Kappa values show that the proposed model has better performance than those of earlier approaches.

  9. Practicing doctors' perceptions on new learning objectives for Vietnamese medical schools

    Directory of Open Access Journals (Sweden)

    Dung Do Van

    2007-06-01

    Full Text Available Abstract Background As part of the process to develop more community-oriented medical teaching in Vietnam, eight medical schools prepared a set of standard learning objectives with attention to the needs of a doctor working with the community. Because they were prepared based on government documents and the opinions of the teachers, it was necessary to check them with doctors who had already graduated and were working at different sites in the community. Methods Each of the eight medical faculties asked 100 practising recent graduates to complete a questionnaire to check the relevance of the skills that the teachers considered most important. We used mean and standard deviation to summarize the scores rated by the respondents for each skill and percentile at four points: p50, p25, p10 and p5 to describe the variation of scores among the respondents. Correlation coefficient was used to measure the relationship between skill levels set by the teachers and the perception of practicing doctors regarding frequency of using skills and priority for each skill. Additional information was taken from the records of focus group discussions to clarify, explain or expand on the results from the quantitative data. Results In many cases the skills considered important by teachers were also rated as highly necessary and/or frequently used by the respondents. There were, however, discrepancies: some skills important to teachers were seldom used and not considered important by the doctors. In focus group discussions the doctors also identified skills that are not taught at all in the medical schools but would be needed by practising doctors. Conclusion Although most of the skills and skill levels included in the learning objectives by the teachers were consistent with the opinions of their graduates, the match was not perfect. The experience of the graduates and their additional comments should be included as inputs to the definition of learning objectives for

  10. Digital learning objects in nursing consultation: technology assessment by undergraduate students.

    Science.gov (United States)

    Silveira, DeniseTolfo; Catalan, Vanessa Menezes; Neutzling, Agnes Ludwig; Martinato, Luísa Helena Machado

    2010-01-01

    This study followed the teaching-learning process about the nursing consultation, based on digital learning objects developed through the active Problem Based Learning method. The goals were to evaluate the digital learning objects about nursing consultation, develop cognitive skills on the subject using problem based learning and identify the students' opinions on the use of technology. This is an exploratory and descriptive study with a quantitative approach. The sample consisted of 71 students in the sixth period of the nursing program at the Federal University of Rio Grande do Sul. The data was collected through a questionnaire to evaluate the learning objects. The results showed positive agreement (58%) on the content, usability and didactics of the proposed computer-mediated activity regarding the nursing consultation. The application of materials to the students is considered positive.

  11. Self-Regulated Learning from Illustrated Text: Eye Movement Modelling to Support Use and Regulation of Cognitive Processes during Learning from Multimedia

    Science.gov (United States)

    Scheiter, Katharina; Schubert, Carina; Schüler, Anne

    2018-01-01

    Background: When learning with text and pictures, learners often fail to adequately process the materials, which can be explained as a failure to self-regulate one's learning by choosing adequate cognitive learning processes. Eye movement modelling examples (EMME) showing how to process multimedia instruction have improved elementary school…

  12. Literacy Learning in a Digitally Rich Humanities Classroom: Embracing Multiple, Collaborative, and Simultaneous Texts

    Science.gov (United States)

    Buckley-Marudas, Mary Frances

    2016-01-01

    Understanding what happens when teachers embrace digital media for literacy learning is critical to realizing the potential of learning in the digital era. This article examines some of the ways that a high school teacher and his students leverage digital technologies for literacy learning in their humanities classrooms. The author introduces the…

  13. Incremental online object learning in a vehicular radar-vision fusion framework

    Energy Technology Data Exchange (ETDEWEB)

    Ji, Zhengping [Los Alamos National Laboratory; Weng, Juyang [Los Alamos National Laboratory; Luciw, Matthew [IEEE; Zeng, Shuqing [IEEE

    2010-10-19

    In this paper, we propose an object learning system that incorporates sensory information from an automotive radar system and a video camera. The radar system provides a coarse attention for the focus of visual analysis on relatively small areas within the image plane. The attended visual areas are coded and learned by a 3-layer neural network utilizing what is called in-place learning, where every neuron is responsible for the learning of its own signal processing characteristics within its connected network environment, through inhibitory and excitatory connections with other neurons. The modeled bottom-up, lateral, and top-down connections in the network enable sensory sparse coding, unsupervised learning and supervised learning to occur concurrently. The presented work is applied to learn two types of encountered objects in multiple outdoor driving settings. Cross validation results show the overall recognition accuracy above 95% for the radar-attended window images. In comparison with the uncoded representation and purely unsupervised learning (without top-down connection), the proposed network improves the recognition rate by 15.93% and 6.35% respectively. The proposed system is also compared with other learning algorithms favorably. The result indicates that our learning system is the only one to fit all the challenging criteria for the development of an incremental and online object learning system.

  14. Impact of Interactive Video Communication Versus Text-Based Feedback on Teaching, Social, and Cognitive Presence in Online Learning Communities.

    Science.gov (United States)

    Seckman, Charlotte

    A key element to online learning is the ability to create a sense of presence to improve learning outcomes. This quasi-experimental study evaluated the impact of interactive video communication versus text-based feedback and found a significant difference between the 2 groups related to teaching, social, and cognitive presence. Recommendations to enhance presence should focus on providing timely feedback, interactive learning experiences, and opportunities for students to establish relationships with peers and faculty.

  15. Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.

    Science.gov (United States)

    Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

    2017-08-01

    Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.

  16. Teaching tools in Evidence Based Practice: evaluation of reusable learning objects (RLOs for learning about Meta-analysis

    Directory of Open Access Journals (Sweden)

    Wharrad Heather

    2011-05-01

    Full Text Available Abstract Background All healthcare students are taught the principles of evidence based practice on their courses. The ability to understand the procedures used in systematically reviewing evidence reported in studies, such as meta-analysis, are an important element of evidence based practice. Meta-analysis is a difficult statistical concept for healthcare students to understand yet it is an important technique used in systematic reviews to pool data from studies to look at combined effectiveness of treatments. In other areas of the healthcare curricula, by supplementing lectures, workbooks and workshops with pedagogically designed, multimedia learning objects (known as reusable learning objects or RLOs we have shown an improvement in students' perceived understanding in subjects they found difficult. In this study we describe the development and evaluation of two RLOs on meta-analysis. The RLOs supplement associated lectures and aim to improve students' understanding of meta-analysis in healthcare students. Methods Following a quality controlled design process two RLOs were developed and delivered to two cohorts of students, a Master in Public Health course and Postgraduate diploma in nursing course. Students' understanding of five key concepts of Meta-analysis were measured before and after a lecture and again after RLO use. RLOs were also evaluated for their educational value, learning support, media attributes and usability using closed and open questions. Results Students rated their understanding of meta-analysis as improved after a lecture and further improved after completing the RLOs (Wilcoxon paired test, p Conclusions Meta-analysis RLOs that are openly accessible and unrestricted by usernames and passwords provide flexible support for students who find the process of meta-analysis difficult.

  17. Effect of tDCS on task relevant and irrelevant perceptual learning of complex objects.

    Science.gov (United States)

    Van Meel, Chayenne; Daniels, Nicky; de Beeck, Hans Op; Baeck, Annelies

    2016-01-01

    During perceptual learning the visual representations in the brain are altered, but these changes' causal role has not yet been fully characterized. We used transcranial direct current stimulation (tDCS) to investigate the role of higher visual regions in lateral occipital cortex (LO) in perceptual learning with complex objects. We also investigated whether object learning is dependent on the relevance of the objects for the learning task. Participants were trained in two tasks: object recognition using a backward masking paradigm and an orientation judgment task. During both tasks, an object with a red line on top of it were presented in each trial. The crucial difference between both tasks was the relevance of the object: the object was relevant for the object recognition task, but not for the orientation judgment task. During training, half of the participants received anodal tDCS stimulation targeted at the lateral occipital cortex (LO). Afterwards, participants were tested on how well they recognized the trained objects, the irrelevant objects presented during the orientation judgment task and a set of completely new objects. Participants stimulated with tDCS during training showed larger improvements of performance compared to participants in the sham condition. No learning effect was found for the objects presented during the orientation judgment task. To conclude, this study suggests a causal role of LO in relevant object learning, but given the rather low spatial resolution of tDCS, more research on the specificity of this effect is needed. Further, mere exposure is not sufficient to train object recognition in our paradigm.

  18. Pareto Optimal Solutions for Network Defense Strategy Selection Simulator in Multi-Objective Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Yang Sun

    2018-01-01

    Full Text Available Using Pareto optimization in Multi-Objective Reinforcement Learning (MORL leads to better learning results for network defense games. This is particularly useful for network security agents, who must often balance several goals when choosing what action to take in defense of a network. If the defender knows his preferred reward distribution, the advantages of Pareto optimization can be retained by using a scalarization algorithm prior to the implementation of the MORL. In this paper, we simulate a network defense scenario by creating a multi-objective zero-sum game and using Pareto optimization and MORL to determine optimal solutions and compare those solutions to different scalarization approaches. We build a Pareto Defense Strategy Selection Simulator (PDSSS system for assisting network administrators on decision-making, specifically, on defense strategy selection, and the experiment results show that the Satisficing Trade-Off Method (STOM scalarization approach performs better than linear scalarization or GUESS method. The results of this paper can aid network security agents attempting to find an optimal defense policy for network security games.

  19. Deep Learning for Detection of Object-Based Forgery in Advanced Video

    Directory of Open Access Journals (Sweden)

    Ye Yao

    2017-12-01

    Full Text Available Passive video forensics has drawn much attention in recent years. However, research on detection of object-based forgery, especially for forged video encoded with advanced codec frameworks, is still a great challenge. In this paper, we propose a deep learning-based approach to detect object-based forgery in the advanced video. The presented deep learning approach utilizes a convolutional neural network (CNN to automatically extract high-dimension features from the input image patches. Different from the traditional CNN models used in computer vision domain, we let video frames go through three preprocessing layers before being fed into our CNN model. They include a frame absolute difference layer to cut down temporal redundancy between video frames, a max pooling layer to reduce computational complexity of image convolution, and a high-pass filter layer to enhance the residual signal left by video forgery. In addition, an asymmetric data augmentation strategy has been established to get a similar number of positive and negative image patches before the training. The experiments have demonstrated that the proposed CNN-based model with the preprocessing layers has achieved excellent results.

  20. Is an Illustration Always Worth Ten Thousand Words? Effects of Prior Knowledge, Learning Style and Multimedia Illustrations on Text Comprehension.

    Science.gov (United States)

    Ollerenshaw, Alison; Aidman, Eugene; Kidd, Garry

    1997-01-01

    This study examined comprehension in four groups of undergraduates under text only, multimedia, and two diagram conditions of text supplementation. Results indicated that effects of text supplementation are mediated by prior knowledge and learning style: multimedia appears more beneficial to surface learners with little prior knowledge and makes…

  1. Learning about Probability from Text and Tables: Do Color Coding and Labeling through an Interactive-User Interface Help?

    Science.gov (United States)

    Clinton, Virginia; Morsanyi, Kinga; Alibali, Martha W.; Nathan, Mitchell J.

    2016-01-01

    Learning from visual representations is enhanced when learners appropriately integrate corresponding visual and verbal information. This study examined the effects of two methods of promoting integration, color coding and labeling, on learning about probabilistic reasoning from a table and text. Undergraduate students (N = 98) were randomly…

  2. The Role of Working Memory in Multimedia Instruction: Is Working Memory Working during Learning from Text and Pictures?

    Science.gov (United States)

    Schuler, Anne; Scheiter, Katharina; van Genuchten, Erlijn

    2011-01-01

    A lot of research has focused on the beneficial effects of using multimedia, that is, text and pictures, for learning. Theories of multimedia learning are based on Baddeley's working memory model (Baddeley 1999). Despite this theoretical foundation, there is only little research that aims at empirically testing whether and more importantly how…

  3. Using SMART Board Technology to Teach Young Students with Disabilities and Limited Group Learning Experience to Read Environmental Text

    Science.gov (United States)

    Shepley, Collin; Lane, Justin D.; Gast, David L.

    2016-01-01

    A multiple probe design across behaviors was used to evaluate the effectiveness of a SMART Board used in conjunction with teacher delivered constant time delay (CTD) to teach environmental text to three young students with disabilities and minimal group learning experience during small group direct instruction. Observational learning, instructive…

  4. Differences in Strategy Use in the Reading Comprehension of Narrative and Science Texts among Students with and without Learning Disabilities

    Science.gov (United States)

    Botsas, George

    2017-01-01

    The aim of the study was to investigate differences in cognitive and metacognitive strategy use in the reading comprehension of narrative and expository texts among students with learning disabilities (SLD) and without learning disabilities (SWOLD). A total of 122 fifth and sixth graders took part in the study. Half of them (n = 61) were SLD…

  5. 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.

  6. Occlusion detection via structured sparse learning for robust object tracking

    KAUST Repository

    Zhang, Tianzhu

    2014-01-01

    Sparse representation based methods have recently drawn much attention in visual tracking due to good performance against illumination variation and occlusion. They assume the errors caused by image variations can be modeled as pixel-wise sparse. However, in many practical scenarios, these errors are not truly pixel-wise sparse but rather sparsely distributed in a structured way. In fact, pixels in error constitute contiguous regions within the object’s track. This is the case when significant occlusion occurs. To accommodate for nonsparse occlusion in a given frame, we assume that occlusion detected in previous frames can be propagated to the current one. This propagated information determines which pixels will contribute to the sparse representation of the current track. In other words, pixels that were detected as part of an occlusion in the previous frame will be removed from the target representation process. As such, this paper proposes a novel tracking algorithm that models and detects occlusion through structured sparse learning. We test our tracker on challenging benchmark sequences, such as sports videos, which involve heavy occlusion, drastic illumination changes, and large pose variations. Extensive experimental results show that our proposed tracker consistently outperforms the state-of-the-art trackers.

  7. READING AUTHENTIC EFL TEXT USING VISUALIZATION AND ADVANCE ORGANIZERS IN A MULTIMEDIA LEARNING ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Tsuiping Chen

    2007-02-01

    Full Text Available The purpose of this experimental study was to compare the effects of different types of computer-generated visuals (static versus animated and advance organizers (descriptive versus question in enhancing comprehension and retention of a content-based lesson for learning English as a Foreign Language (EFL. Additionally, the study investigated the interactive effect of students’ existing reading proficiency level and the above-mentioned treatments on their reading comprehension achievement. Students from two EFL reading sections (N = 115 were tested on their reading proficiency and then randomly assigned to one of four computer-based instructional modules—static visual alone, animation alone, animation plus descriptive advance organizer, and animation plus question advance organizer. Once having interacted with their respective instructional materials, students then took four criterion tests immediately afterward and again four weeks later. The results showed that the animation group outperformed the static visual group in one of the four tests, and that animation embedded with a question advance organizer had a marginal effect among the four treatments in facilitating the acquisition of L2 reading comprehension both for the immediate and the delayed posttests.

  8. Different Modes of Digital Learning Object Use in School Settings: Do We Design for Individual or Collaborative Learning?

    Science.gov (United States)

    Akpinar, Yavuz

    2014-01-01

    The aim of the studies reported in this paper is to gain classroom based empirical evidence on the learning effectiveness of learning objects used in two types of study settings: Collaborative and individual. A total of 127 seventh and ninth grade students participated in the experiments. They were assigned into one of the study modes and worked…

  9. Early age-dependent impairments of context-dependent extinction learning, object recognition, and object-place learning occur in rats.

    Science.gov (United States)

    Wiescholleck, Valentina; Emma André, Marion Agnès; Manahan-Vaughan, Denise

    2014-03-01

    The hippocampus is vulnerable to age-dependent memory decline. Multiple forms of memory depend on adequate hippocampal function. Extinction learning comprises active inhibition of no longer relevant learned information concurrent with suppression of a previously learned reaction. It is highly dependent on context, and evidence exists that it requires hippocampal activation. In this study, we addressed whether context-based extinction as well as hippocampus-dependent tasks, such as object recognition and object-place recognition, are equally affected by moderate aging. Young (7-8 week old) and older (7-8 month old) Wistar rats were used. For the extinction study, animals learned that a particular floor context indicated that they should turn into one specific arm (e.g., left) to receive a food reward. On the day after reaching the learning criterion of 80% correct choices, the floor context was changed, no reward was given and animals were expected to extinguish the learned response. Both, young and older rats managed this first extinction trial in the new context with older rats showing a faster extinction performance. One day later, animals were returned to the T-maze with the original floor context and renewal effects were assessed. In this case, only young but not older rats showed the expected renewal effect (lower extinction ratio as compared to the day before). To assess general memory abilities, animals were tested in the standard object recognition and object-place memory tasks. Evaluations were made at 5 min, 1 h and 7 day intervals. Object recognition memory was poor at short-term and intermediate time-points in older but not young rats. Object-place memory performance was unaffected at 5 min, but impaired at 1 h in older but not young rats. Both groups were impaired at 7 days. These findings support that not only aspects of general memory, but also context-dependent extinction learning, are affected by moderate aging. This may reflect less flexibility in

  10. Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning

    Directory of Open Access Journals (Sweden)

    HU Gensheng

    2018-03-01

    Full Text Available Ground object information of remote sensing images covered with thin clouds is obscure. An information recovery algorithm for ground objects in thin cloud images is proposed by fusing guide filter and transfer learning. Firstly, multi-resolution decomposition of thin cloud target images and cloud-free guidance images is performed by using multi-directional nonsubsampled dual-tree complex wavelet transform. Then the decomposed low frequency subbands are processed by using support vector guided filter and transfer learning respectively. The decomposed high frequency subbands are enhanced by using modified Laine enhancement function. The low frequency subbands output by guided filter and those predicted by transfer learning model are fused by the method of selection and weighting based on regional energy. Finally, the enhanced high frequency subbands and the fused low frequency subbands are reconstructed by using inverse multi-directional nonsubsampled dual-tree complex wavelet transform to obtain the ground object information recovery images. Experimental results of Landsat-8 OLI multispectral images show that, support vector guided filter can effectively preserve the detail information of the target images, domain adaptive transfer learning can effectively extend the range of available multi-source and multi-temporal remote sensing images, and good effects for ground object information recover are obtained by fusing guide filter and transfer learning to remove thin cloud on the remote sensing images.

  11. Efficient Exact Inference With Loss Augmented Objective in Structured Learning.

    Science.gov (United States)

    Bauer, Alexander; Nakajima, Shinichi; Muller, Klaus-Robert

    2016-08-19

    Structural support vector machine (SVM) is an elegant approach for building complex and accurate models with structured outputs. However, its applicability relies on the availability of efficient inference algorithms--the state-of-the-art training algorithms repeatedly perform inference to compute a subgradient or to find the most violating configuration. In this paper, we propose an exact inference algorithm for maximizing nondecomposable objectives due to special type of a high-order potential having a decomposable internal structure. As an important application, our method covers the loss augmented inference, which enables the slack and margin scaling formulations of structural SVM with a variety of dissimilarity measures, e.g., Hamming loss, precision and recall, Fβ-loss, intersection over union, and many other functions that can be efficiently computed from the contingency table. We demonstrate the advantages of our approach in natural language parsing and sequence segmentation applications.

  12. Geoparsing text for characterizing urban operational environments through machine learning techniques

    Science.gov (United States)

    Garfinkle, Noah W.; Selig, Lucas; Perkins, Timothy K.; Calfas, George W.

    2017-05-01

    Increasing worldwide internet connectivity and access to sources of print and open social media has increased near realtime availability of textual information. Capabilities to structure and integrate textual data streams can contribute to more meaningful representations of operational environment factors (i.e., Political, Military, Economic, Social, Infrastructure, Information, Physical Environment, and Time [PMESII-PT]) and tactical civil considerations (i.e., Areas, Structures, Capabilities, Organizations, People and Events [ASCOPE]). However, relying upon human analysts to encode this information as it arrives quickly proves intractable. While human analysts possess an ability to comprehend context in unstructured text far beyond that of computers, automated geoparsing (the extraction of locations from unstructured text) can empower analysts to automate sifting through datasets for areas of interest. This research evaluates existing approaches to geoprocessing as well as initiating the research and development of locally-improved methods of tagging parts of text as possible locations, resolving possible locations into coordinates, and interfacing such results with human analysts. The objective of this ongoing research is to develop a more contextually-complete picture of an area of interest (AOI) including human-geographic context for events. In particular, our research is working to make improvements to geoparsing (i.e., the extraction of spatial context from documents), which requires development, integration, and validation of named-entity recognition (NER) tools, gazetteers, and entity-attribution. This paper provides an overview of NER models and methodologies as applied to geoparsing, explores several challenges encountered, presents preliminary results from the creation of a flexible geoparsing research pipeline, and introduces ongoing and future work with the intention of contributing to the efficient geocoding of information containing valuable

  13. Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics.

    Science.gov (United States)

    Chen, Chi-Hsin; Zhang, Yayun; Yu, Chen

    2018-05-01

    Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co-occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected the learning of individual object labels, but not the learning of category labels. Learners' subsequent generalization of category labels indicated sensitivity to the structure of statistical input. Copyright © 2017 Cognitive Science Society, Inc.

  14. Duo: A Human/Wearable Hybrid for Learning About Common Manipulate Objects

    National Research Council Canada - National Science Library

    Kemp, Charles C

    2002-01-01

    ... with them. Duo is a human/wearable hybrid that is designed to learn about this important domain of human intelligence by interacting with natural manipulable objects in unconstrained environments...

  15. Using Epistemic Network Analysis to understand core topics as planned learning objectives

    DEFF Research Database (Denmark)

    Allsopp, Benjamin Brink; Dreyøe, Jonas; Misfeldt, Morten

    Epistemic Network Analysis is a tool developed by the epistemic games group at the University of Wisconsin Madison for tracking the relations between concepts in students discourse (Shaffer 2017). In our current work we are applying this tool to learning objectives in teachers digital preparation....... The danish mathematics curriculum is organised in six competencies and three topics. In the recently implemented learning platforms teacher choose which of the mathematical competencies that serves as objective for a specific lesson or teaching sequence. Hence learning objectives for lessons and teaching...... sequences are defining a network of competencies, where two competencies are closely related of they often are part of the same learning objective or teaching sequence. We are currently using Epistemic Network Analysis to study these networks. In the poster we will include examples of different networks...

  16. Data quality objectives lessons learned for tank waste characterization

    International Nuclear Information System (INIS)

    Eberlein, S.J.; Banning, D.L.

    1996-01-01

    The tank waste characterization process is an integral part of the overall effort to control the hazards associated with radioactive wastes stored in underground tanks at the Hanford Reservation. The programs involved in the characterization of the waste are employing the Data Quality Objective (DQO) process in all information and data collection activities. The DQO process is used by the programs to address an issue or problem rather than a specific sampling event. Practical limits (e.g., limited number and location of sampling points) do not always allow for precise characterization of a tank or the full implementation of the DQO process. Because of the flexibility of the DQO process, it can be used as a planning tool for sampling and analysis of the underground waste storage tanks. The iterative nature of the DQO process allows it to be used as additional information is obtained or open-quotes lessons are learnedclose quotes concerning an issue or problem requiring sampling and analysis of tank waste. In addition, the application of the DQO process forces alternative actions to be considered when precise characterization of a tank or the fall implementation of the DQO process is not practical

  17. A Constrained Multi-Objective Learning Algorithm for Feed-Forward Neural Network Classifiers

    Directory of Open Access Journals (Sweden)

    M. Njah

    2017-06-01

    Full Text Available This paper proposes a new approach to address the optimal design of a Feed-forward Neural Network (FNN based classifier. The originality of the proposed methodology, called CMOA, lie in the use of a new constraint handling technique based on a self-adaptive penalty procedure in order to direct the entire search effort towards finding only Pareto optimal solutions that are acceptable. Neurons and connections of the FNN Classifier are dynamically built during the learning process. The approach includes differential evolution to create new individuals and then keeps only the non-dominated ones as the basis for the next generation. The designed FNN Classifier is applied to six binary classification benchmark problems, obtained from the UCI repository, and results indicated the advantages of the proposed approach over other existing multi-objective evolutionary neural networks classifiers reported recently in the literature.

  18. Moving object detection in video satellite image based on deep learning

    Science.gov (United States)

    Zhang, Xueyang; Xiang, Junhua

    2017-11-01

    Moving object detection in video satellite image is studied. A detection algorithm based on deep learning is proposed. The small scale characteristics of remote sensing video objects are analyzed. Firstly, background subtraction algorithm of adaptive Gauss mixture model is used to generate region proposals. Then the objects in region proposals are classified via the deep convolutional neural network. Thus moving objects of interest are detected combined with prior information of sub-satellite point. The deep convolution neural network employs a 21-layer residual convolutional neural network, and trains the network parameters by transfer learning. Experimental results about video from Tiantuo-2 satellite demonstrate the effectiveness of the algorithm.

  19. Ego-Motion and Tracking for Continuous Object Learning: A Brief Survey

    Science.gov (United States)

    2017-09-01

    past research related to the tasks of ego-motion estimation and object tracking from the viewpoint of their role in continuous object learning...in visual object tracking, competitions are held each year to identify the most accurate and robust tracking implementations. Over recent competitions...information should they share) or vice versa? These are just some of the questions that must be addressed in future research toward continuous object

  20. Improving Collaborative Learning in the Classroom: Text Mining Based Grouping and Representing

    Science.gov (United States)

    Erkens, Melanie; Bodemer, Daniel; Hoppe, H. Ulrich

    2016-01-01

    Orchestrating collaborative learning in the classroom involves tasks such as forming learning groups with heterogeneous knowledge and making learners aware of the knowledge differences. However, gathering information on which the formation of appropriate groups and the creation of graphical knowledge representations can be based is very effortful…

  1. Tool Support for Collaborative Teaching and Learning of Object-Oriented Modelling

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Ratzer, Anne Vinter

    2002-01-01

    Modeling is central to doing and learning object-oriented development. We present a new tool, Ideogramic UML, for gesture-based collaborative modeling with the Unified Modeling Language (UML), which can be used to collaboratively teach and learn modeling. Furthermore, we discuss how we have...

  2. A Meta-Relational Approach for the Definition and Management of Hybrid Learning Objects

    Science.gov (United States)

    Navarro, Antonio; Fernandez-Pampillon, Ana Ma.; Fernandez-Chamizo, Carmen; Fernandez-Valmayor, Alfredo

    2013-01-01

    Electronic learning objects (LOs) are commonly conceived of as digital units of information used for teaching and learning. To facilitate their classification for pedagogical planning and retrieval purposes, LOs are complemented with metadata (e.g., the author). These metadata are usually restricted by a set of predetermined tags to which the…

  3. iLOG: A Framework for Automatic Annotation of Learning Objects with Empirical Usage Metadata

    Science.gov (United States)

    Miller, L. D.; Soh, Leen-Kiat; Samal, Ashok; Nugent, Gwen

    2012-01-01

    Learning objects (LOs) are digital or non-digital entities used for learning, education or training commonly stored in repositories searchable by their associated metadata. Unfortunately, based on the current standards, such metadata is often missing or incorrectly entered making search difficult or impossible. In this paper, we investigate…

  4. An Achievement Degree Analysis Approach to Identifying Learning Problems in Object-Oriented Programming

    Science.gov (United States)

    Allinjawi, Arwa A.; Al-Nuaim, Hana A.; Krause, Paul

    2014-01-01

    Students often face difficulties while learning object-oriented programming (OOP) concepts. Many papers have presented various assessment methods for diagnosing learning problems to improve the teaching of programming in computer science (CS) higher education. The research presented in this article illustrates that although max-min composition is…

  5. Simplified production of multimedia based radiological learning objects using the flash format

    International Nuclear Information System (INIS)

    Jedrusik, P.; Preisack, M.; Dammann, F.

    2005-01-01

    Purpose: evaluation of the applicability of the flash format for the production of radiological learning objects used in an e-learning environment. Material and methods: five exemplary learning objects with different didactic purposes referring to radiological diagnostics are presented. They have been intended for the use within the multimedia, internet-based e-learning environment LaMedica. Interactive learning objects were composed using the Flash 5.0 software (Macromedia, San Francisco, USA) on the basis of digital CT and MR images, digitized conventional radiographs and different graphical elements prepared as TIFF files or in a vector graphics format. Results: after a short phase of initial skill adaptation training, a radiologist author was soon able to create independently all learning objects. The import of different types of images and graphical elements was carried out without complications. Despite manifold design options, handling of the program is easy due to clear arrangement and structure, thus enabling the creation of simple as well as complex learning objects that provided a high degree of attractiveness and interaction. Data volume and bandwidth demand for online use was significantly reduced by the flash format compression without a substantial loss of visual quality. (orig.)

  6. Towards Self-Learning Based Hypotheses Generation in Biomedical Text Domain.

    Science.gov (United States)

    Gopalakrishnan, Vishrawas; Jha, Kishlay; Xun, Guangxu; Ngo, Hung Q; Zhang, Aidong

    2017-12-26

    The overwhelming amount of research articles in the domain of bio-medicine might cause important connections to remain unnoticed. Literature Based Discovery is a sub-field within biomedical text mining that peruses these articles to formulate high confident hypotheses on possible connections between medical concepts. Although many alternate methodologies have been proposed over the last decade, they still suffer from scalability issues. The primary reason, apart from the dense inter-connections between biological concepts, is the absence of information on the factors that lead to the edge-formation. In this work, we formulate this problem as a collaborative filtering task and leverage a relatively new concept of word-vectors to learn and mimic the implicit edge-formation process. Along with single-class classifier, we prune the search-space of redundant and irrelevant hypotheses to increase the efficiency of the system and at the same time maintaining and in some cases even boosting the overall accuracy. We show that our proposed framework is able to prune up to 90% of the hypotheses while still retaining high recall in top-K results. This level of efficiency enables the discovery algorithm to look for higher-order hypotheses, something that was infeasible until now. Furthermore, the generic formulation allows our approach to be agile to performboth open and closed discovery.We also experimentally validate that the core data-structures upon which the system bases its decision has a high concordance with the opinion of the experts.This coupled with the ability to understand the edge formation process provides us with interpretable results without any manual intervention. The relevant JAVA codes are available at: https://github.com/vishrawas/Medline-Code_v2. vishrawa@buffalo.edukishlayj@buffalo.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email

  7. Learn Objective-C on the Mac for OS X and iOS

    CERN Document Server

    Knaster, Scott; Malik, Waqar

    2012-01-01

    Learn to write apps for some of today's hottest technologies, including the iPhone and iPad (using iOS), as well as the Mac (using OS X). It starts with Objective-C, the base language on which the native iOS software development kit (SDK) and the OS X are based. Learn Objective-C on the Mac: For OS X and iOS, Second Edition updates a best selling book and is an extensive, newly updated guide to Objective-C. Objective-C is a powerful, object-oriented extension of C, making this update the perfect follow-up to Dave Mark's bestselling Learn C on the Mac. Whether you're an experienced C programmer

  8. 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…

  9. Rapid e-Learning Tools Selection Process for Cognitive and Psychomotor Learning Objectives

    Science.gov (United States)

    Ku, David Tawei; Huang, Yung-Hsin

    2012-01-01

    This study developed a decision making process for the selection of rapid e-learning tools that could match different learning domains. With the development of the Internet, the speed of information updates has become faster than ever. E-learning has rapidly become the mainstream for corporate training and academic instruction. In order to reduce…

  10. Investigating an Application of Speech-to-Text Recognition: A Study on Visual Attention and Learning Behaviour

    Science.gov (United States)

    Huang, Y-M.; Liu, C-J.; Shadiev, Rustam; Shen, M-H.; Hwang, W-Y.

    2015-01-01

    One major drawback of previous research on speech-to-text recognition (STR) is that most findings showing the effectiveness of STR for learning were based upon subjective evidence. Very few studies have used eye-tracking techniques to investigate visual attention of students on STR-generated text. Furthermore, not much attention was paid to…

  11. Learning from Expository Text in L2 Reading: Memory for Causal Relations and L2 Reading Proficiency

    Science.gov (United States)

    Hosoda, Masaya

    2017-01-01

    This study explored the relation between second-language (L2) readers' memory for causal relations and their learning outcomes from expository text. Japanese students of English as a foreign language (EFL) with high and low L2 reading proficiency read an expository text. They completed a causal question and a problem-solving test as measures of…

  12. An Argument for Learning. Science Teachers and Students Build Literacy through Text-Based Investigations

    Science.gov (United States)

    Greenleaf, Cynthia; Brown, Willard R.

    2017-01-01

    This article describes how participants in the California Teacher Inquiry Network learn the art of making their invisible thinking processes visible, helping them see more clearly that they have internal resources to help students master similar kinds of thinking processes.

  13. La interfaz del objeto de aprendizaje/ The interface of the Learning Object

    Directory of Open Access Journals (Sweden)

    Pilar Hernandez

    2007-01-01

    Full Text Available Este artículo hace parte del proceso de investigación documental y teórico, que se realizó en el marco de la investigación mencionada, con el fin de dar soporte conceptual a los importantes aportes que hace el diseño gráfico al proceso de construcción de objetos de aprendizaje. Se presenta a continuación un breve recorrido por las diferentes concepciones de los conceptos de interfaz y usabilidad, en tanto fundamentales en el logro, en primera instancia, de la comunicación y, en segunda instancia, la potenciación de los aprendizajes. This article is a part of the documental and theoretical process of investigation, of the project mention before, this has as a purpose to give a conceptual support to the important contributions from the graphic design to the process of construction of learning objects. In this is presented a brief journey about the different conceptions of the notion of interface and usability, as well as they are fundamental to consolidate of, in first place, the communication and, in second place, the promotion of the learning process.

  14. Personalización del proceso de aprendizaje usando learning objects reutilizables

    Directory of Open Access Journals (Sweden)

    J. Minguillón

    2005-01-01

    Full Text Available En este artículo se describe el diseño de una plataforma de e-learning que integra el uso de learning objects (objetos de aprendizaje reutilizables como elementos básicos para la construcción de itinerarios que permiten la personalización del proceso de aprendizaje en función de las características especiales de cada curso y de cada perfil de estudiante. El objetivo es describir las características deseadas de tal plataforma y las problemáticas que se presentan cuando se integran diferentes tecnologías, especialmente el salto existente entre las definiciones de metadatos proporcionadas por los estándares de marcado de objetos de aprendizaje, y la aplicación de un modelo de diseño instruccional adecuado a este nuevo escenario. La plataforma propuesta apuesta por el uso del estándard SCORM y, por extensión, del estándar LOM para el marcado de los objetos de aprendizaje, teniendo en cuenta que el objetivo central es el seguimiento del proceso de aprendizaje y la personalización del mismo.

  15. Multi-objective group scheduling with learning effect in the cellular manufacturing system

    Directory of Open Access Journals (Sweden)

    Mohammad Taghi Taghavi-fard

    2011-01-01

    Full Text Available Group scheduling problem in cellular manufacturing systems consists of two major steps. Sequence of parts in each part-family and the sequence of part-family to enter the cell to be processed. This paper presents a new method for group scheduling problems in flow shop systems where it minimizes makespan (Cmax and total tardiness. In this paper, a position-based learning model in cellular manufacturing system is utilized where processing time for each part-family depends on the entrance sequence of that part. The problem of group scheduling is modeled by minimizing two objectives of position-based learning effect as well as the assumption of setup time depending on the sequence of parts-family. Since the proposed problem is NP-hard, two meta heuristic algorithms are presented based on genetic algorithm, namely: Non-dominated sorting genetic algorithm (NSGA-II and non-dominated rank genetic algorithm (NRGA. The algorithms are tested using randomly generated problems. The results include a set of Pareto solutions and three different evaluation criteria are used to compare the results. The results indicate that the proposed algorithms are quite efficient to solve the problem in a short computational time.

  16. A Mobile Service Oriented Multiple Object Tracking Augmented Reality Architecture for Education and Learning Experiences

    Science.gov (United States)

    Rattanarungrot, Sasithorn; White, Martin; Newbury, Paul

    2014-01-01

    This paper describes the design of our service-oriented architecture to support mobile multiple object tracking augmented reality applications applied to education and learning scenarios. The architecture is composed of a mobile multiple object tracking augmented reality client, a web service framework, and dynamic content providers. Tracking of…

  17. Autonomous learning of robust visual object detection and identification on a humanoid

    NARCIS (Netherlands)

    Leitner, J.; Chandrashekhariah, P.; Harding, S.; Frank, M.; Spina, G.; Förster, A.; Triesch, J.; Schmidhuber, J.

    2012-01-01

    In this work we introduce a technique for a humanoid robot to autonomously learn the representations of objects within its visual environment. Our approach involves an attention mechanism in association with feature based segmentation that explores the environment and provides object samples for

  18. Large-scale weakly supervised object localization via latent category learning.

    Science.gov (United States)

    Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

    2015-04-01

    Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

  19. Behavioral Objectives, the Cult of Efficiency, and Foreign Language Learning: Are They Compatible?

    Science.gov (United States)

    Tumposky, Nancy Rennau

    1984-01-01

    Surveys the literature regarding the use of behavioral objectives in education and in foreign language instruction and examines the roots of the behavioral objectives movement in behaviorist psychology and the scientific management movement of the 1920s. Discusses implications for foreign and second language learning and provides suggestions for…

  20. Aspects on Teaching/Learning with Object Oriented Programming for Entry Level Courses of Engineering.

    Science.gov (United States)

    de Oliveira, Clara Amelia; Conte, Marcos Fernando; Riso, Bernardo Goncalves

    This work presents a proposal for Teaching/Learning, on Object Oriented Programming for Entry Level Courses of Engineering and Computer Science, on University. The philosophy of Object Oriented Programming comes as a new pattern of solution for problems, where flexibility and reusability appears over the simple data structure and sequential…

  1. 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

  2. Analyzing discourse and text complexity for learning and collaborating a cognitive approach based on natural language processing

    CERN Document Server

    Dascălu, Mihai

    2014-01-01

    With the advent and increasing popularity of Computer Supported Collaborative Learning (CSCL) and e-learning technologies, the need of automatic assessment and of teacher/tutor support for the two tightly intertwined activities of comprehension of reading materials and of collaboration among peers has grown significantly. In this context, a polyphonic model of discourse derived from Bakhtin’s work as a paradigm is used for analyzing both general texts and CSCL conversations in a unique framework focused on different facets of textual cohesion. As specificity of our analysis, the individual learning perspective is focused on the identification of reading strategies and on providing a multi-dimensional textual complexity model, whereas the collaborative learning dimension is centered on the evaluation of participants’ involvement, as well as on collaboration assessment. Our approach based on advanced Natural Language Processing techniques provides a qualitative estimation of the learning process and enhance...

  3. Improving learning with science and social studies text using computer-based concept maps for students with disabilities.

    Science.gov (United States)

    Ciullo, Stephen; Falcomata, Terry S; Pfannenstiel, Kathleen; Billingsley, Glenna

    2015-01-01

    Concept maps have been used to help students with learning disabilities (LD) improve literacy skills and content learning, predominantly in secondary school. However, despite increased access to classroom technology, no previous studies have examined the efficacy of computer-based concept maps to improve learning from informational text for students with LD in elementary school. In this study, we used a concurrent delayed multiple probe design to evaluate the interactive use of computer-based concept maps on content acquisition with science and social studies texts for Hispanic students with LD in Grades 4 and 5. Findings from this study suggest that students improved content knowledge during intervention relative to a traditional instruction baseline condition. Learning outcomes and social validity information are considered to inform recommendations for future research and the feasibility of classroom implementation. © The Author(s) 2014.

  4. Attribute conjunctions and the part configuration advantage in object category learning.

    Science.gov (United States)

    Saiki, J; Hummel, J E

    1996-07-01

    Five experiments demonstrated that in object category learning people are particularly sensitive to conjunctions of part shapes and relative locations. Participants learned categories defined by a part's shape and color (part-color conjunctions) or by a part's shape and its location relative to another part (part-location conjunctions). The statistical properties of the categories were identical across these conditions, as were the salience of color and relative location. Participants were better at classifying objects defined by part-location conjunctions than objects defined by part-color conjunctions. Subsequent experiments revealed that this effect was not due to the specific color manipulation or the role of location per se. These results suggest that the shape bias in object categorization is at least partly due to sensitivity to part-location conjunctions and suggest a new processing constraint on category learning.

  5. Reinforcement learning modulates the stability of cognitive control settings for object selection

    Directory of Open Access Journals (Sweden)

    Anthony William Sali

    2013-12-01

    Full Text Available Cognitive flexibility reflects both a trait that reliably differs between individuals and a state that can fluctuate moment-to-moment. Whether individuals can undergo persistent changes in cognitive flexibility as a result of reward learning is less understood. Here, we investigated whether reinforcing a periodic shift in an object selection strategy can make an individual more prone to switch strategies in a subsequent unrelated task. Participants completed two different choice tasks in which they selected one of four objects in an attempt to obtain a hidden reward on each trial. During a training phase, objects were defined by color. Participants received either consistent reward contingencies in which one color was more often rewarded, or contingencies in which the color that was more often rewarded changed periodically and without warning. Following the training phase, all participants completed a test phase in which reward contingencies were defined by spatial location and the location that was more often rewarded remained constant across the entire task. Those participants who received inconsistent contingencies during training continued to make more variable selections during the test phase in comparison to those who received the consistent training. Furthermore, a difference in the likelihood to switch selections on a trial-by-trial basis emerged between training groups: participants who received consistent contingencies during training were less likely to switch object selections following an unrewarded trial and more likely to repeat a selection following reward. Our findings provide evidence that the extent to which priority shifting is reinforced modulates the stability of cognitive control settings in a persistent manner, such that individuals become generally more or less prone to shifting priorities in the future.

  6. ROBUSTNESS AND PREDICTION ACCURACY OF MACHINE LEARNING FOR OBJECTIVE VISUAL QUALITY ASSESSMENT

    OpenAIRE

    Hines, Andrew; Kendrick, Paul; Barri, Adriaan; Narwaria, Manish; Redi, Judith A.

    2014-01-01

    Machine Learning (ML) is a powerful tool to support the development of objective visual quality assessment metrics, serving as a substitute model for the perceptual mechanisms acting in visual quality appreciation. Nevertheless, the reliability of ML-based techniques within objective quality assessment metrics is often questioned. In this study, the robustness of ML in supporting objective quality assessment is investigated, specifically when the feature set adopted for prediction is suboptim...

  7. Robustness and prediction accuracy of machine learning for objective visual quality assessment

    OpenAIRE

    HINES, ANDREW

    2014-01-01

    PUBLISHED Lisbon, Portugal Machine Learning (ML) is a powerful tool to support the development of objective visual quality assessment metrics, serving as a substitute model for the perceptual mechanisms acting in visual quality appreciation. Nevertheless, the reli- ability of ML-based techniques within objective quality as- sessment metrics is often questioned. In this study, the ro- bustness of ML in supporting objective quality assessment is investigated, specific...

  8. Rasgos Pedagógicos de los Objetos de Aprendizaje Pedagogical Features of Learning Objects

    Directory of Open Access Journals (Sweden)

    Chiappe Laverde Andres

    2008-07-01

    Full Text Available Los objetos de aprendizaje (OA son considerados hoy como una alternativa viable e interesante para el desarrollo de contenidos para programas educativos mediados por las Tecnologías de la Información y la Comunicación (TIC. No obstante la pertinencia del tema para el momento actual de la educación superior en toda Latinoamérica, es preciso reflexionar más en profundidad acerca de lo que significan los OA y su impacto en el proceso educativo. El estudio de los rasgos pedagógicos de los objetos de aprendizaje coloca a la comunidad académica frente a un escenario que requiere la pronta identificación de sus retos y limitaciones de cara a la inminente ejecución de procesos de incorporación de los OA en las dinámicas de las instituciones educativas. Learning objects (LO are regarded today as a viable and interesting alternative for development of content for educational programs mediated by information and communication technologies (ICT. Attending the relevance of this topic just for this historic moment of higher education throughout Latin America, we need to think more deeply about what LO means and its impact on the educational process. The study of the pedagogical features of learning objects placed to the academic community in front of a scenario that requires prompt identification of their challenges and constraints facing the imminent execution of incorporation processes of LO in educational institutions dynamics.

  9. A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

    Directory of Open Access Journals (Sweden)

    James N Ingram

    2011-09-01

    Full Text Available Motor learning has been extensively studied using dynamic (force-field perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar

  10. Selective bilateral amygdala lesions in rhesus monkeys fail to disrupt object reversal learning.

    Science.gov (United States)

    Izquierdo, Alicia; Murray, Elisabeth A

    2007-01-31

    Neuropsychological studies in nonhuman primates have led to the view that the amygdala plays an essential role in stimulus-reward association. The main evidence in support of this idea is that bilateral aspirative or radiofrequency lesions of the amygdala yield severe impairments on object reversal learning, a task that assesses the ability to shift choices of objects based on the presence or absence of food reward (i.e., reward contingency). The behavioral effects of different lesion techniques, however, can vary. The present study therefore evaluated the effects of selective, excitotoxic lesions of the amygdala in rhesus monkeys on object reversal learning. For comparison, we tested the same monkeys on a task known to be sensitive to amygdala damage, the reinforcer devaluation task. Contrary to previous results based on less selective lesion techniques, monkeys with complete excitotoxic amygdala lesions performed object reversal learning as quickly as controls. As predicted, however, the same operated monkeys were impaired in making object choices after devaluation of the associated food reinforcer. The results suggest two conclusions. First, the results demonstrate that the amygdala makes a selective contribution to stimulus-reward association; the amygdala is critical for guiding object choices after changes in reward value but not after changes in reward contingency. Second, the results implicate a critical contribution to object reversal learning of structures nearby the amygdala, perhaps the subjacent rhinal cortex.

  11. Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

    Science.gov (United States)

    Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

    2017-06-09

    In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

  12. Reading Authentic EFL Text Using Visualization and Advance Organizers in a Multimedia Learning Environment

    Science.gov (United States)

    Lin, Huifen; Chen, Tsuiping

    2007-01-01

    The purpose of this experimental study was to compare the effects of different types of computer-generated visuals (static versus animated) and advance organizers (descriptive versus question) in enhancing comprehension and retention of a content-based lesson for learning English as a Foreign Language (EFL). Additionally, the study investigated…

  13. Effects of Multimedia Vocabulary Annotations on Vocabulary Learning and Text Comprehension in ESP Classrooms

    Science.gov (United States)

    Lin, Huifen

    2012-01-01

    For the past few decades, instructional materials enriched with multimedia elements have enjoyed increasing popularity. Multimedia-based instruction incorporating stimulating visuals, authentic audios, and interactive animated graphs of different kinds all provide additional and valuable opportunities for students to learn beyond what conventional…

  14. Examining the Conditions of Using an On-Line Dictionary to Learn Words and Comprehend Texts

    Science.gov (United States)

    Dilenschneider, Robert Francis

    2018-01-01

    This study investigated three look-up conditions for language learners to learn unknown target words and comprehend a reading passage when their attention is transferred away to an on-line dictionary. The research questions focused on how each look-up condition impacted the recall and recognition of word forms, word meanings, and passage…

  15. Learning How to Simplify From Explicit Labeling of Complex-Simplified Text Pairs

    DEFF Research Database (Denmark)

    Alva-Manchego, Fernando; Bingel, Joachim; Paetzold, Gustavo H.

    2017-01-01

    that generalization becomes difficult. End-to-end models also make it hard to interpret what is actually learned from data. We propose a method that decomposes the task of TS into its sub-problems. We devise a way to automatically identify operations in a parallel corpus and introduce a sequence-labeling approach...

  16. Maximising meaning : Creating a learning environment for reading comprehension of informative texts from a Vygotskian perspective

    NARCIS (Netherlands)

    van Rijk, Y.; Volman, M.; de Haan, D.; van Oers, B.

    Sociocultural theories based on the work of Vygotsky have been increasingly influential in educational sciences. Developmental education (DE) is a pedagogical approach based on Vygotskian theory that has inspired primary schools in the Netherlands to change the learning environment innovatively in a

  17. Reflexive Texts: Issues of Knowledge, Power, and Discourse in Researching Gender and Learning

    Science.gov (United States)

    English, Leona M.; Irving, Catherine J.

    2008-01-01

    This article provides a feminist poststructural analysis of the authors' academic labor during a State of the Field Literature Review of Gender and Adult Learning for a government-funded educational body. Drawing on Foucault and feminist theorists, the authors pay particular attention to how power seeps down through the system to our bodies in our…

  18. A Study of Readability of Texts in Bangla through Machine Learning Approaches

    Science.gov (United States)

    Sinha, Manjira; Basu, Anupam

    2016-01-01

    In this work, we have investigated text readability in Bangla language. Text readability is an indicator of the suitability of a given document with respect to a target reader group. Therefore, text readability has huge impact on educational content preparation. The advances in the field of natural language processing have enabled the automatic…

  19. An Interactive Learning Environment for Teaching the Imperative and Object-Oriented Programming Techniques in Various Learning Contexts

    Science.gov (United States)

    Xinogalos, Stelios

    The acquisition of problem-solving and programming skills in the era of knowledge society seems to be particularly important. Due to the intrinsic difficulty of acquiring such skills various educational tools have been developed. Unfortunately, most of these tools are not utilized. In this paper we present the programming microworlds Karel and objectKarel that support the procedural-imperative and Object-Oriented Programming (OOP) techniques and can be used for supporting the teaching and learning of programming in various learning contexts and audiences. The paper focuses on presenting the pedagogical features that are common to both environments and mainly on presenting the potential uses of these environments.

  20. It's all connected: Pathways in visual object recognition and early noun learning.

    Science.gov (United States)

    Smith, Linda B

    2013-11-01

    A developmental pathway may be defined as the route, or chain of events, through which a new structure or function forms. For many human behaviors, including object name learning and visual object recognition, these pathways are often complex and multicausal and include unexpected dependencies. This article presents three principles of development that suggest the value of a developmental psychology that explicitly seeks to trace these pathways and uses empirical evidence on developmental dependencies among motor development, action on objects, visual object recognition, and object name learning in 12- to 24-month-old infants to make the case. The article concludes with a consideration of the theoretical implications of this approach. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

  1. Internal attention to features in visual short-term memory guides object learning.

    Science.gov (United States)

    Fan, Judith E; Turk-Browne, Nicholas B

    2013-11-01

    Attending to objects in the world affects how we perceive and remember them. What are the consequences of attending to an object in mind? In particular, how does reporting the features of a recently seen object guide visual learning? In three experiments, observers were presented with abstract shapes in a particular color, orientation, and location. After viewing each object, observers were cued to report one feature from visual short-term memory (VSTM). In a subsequent test, observers were cued to report features of the same objects from visual long-term memory (VLTM). We tested whether reporting a feature from VSTM: (1) enhances VLTM for just that feature (practice-benefit hypothesis), (2) enhances VLTM for all features (object-based hypothesis), or (3) simultaneously enhances VLTM for that feature and suppresses VLTM for unreported features (feature-competition hypothesis). The results provided support for the feature-competition hypothesis, whereby the representation of an object in VLTM was biased towards features reported from VSTM and away from unreported features (Experiment 1). This bias could not be explained by the amount of sensory exposure or response learning (Experiment 2) and was amplified by the reporting of multiple features (Experiment 3). Taken together, these results suggest that selective internal attention induces competitive dynamics among features during visual learning, flexibly tuning object representations to align with prior mnemonic goals. Copyright © 2013 Elsevier B.V. All rights reserved.

  2. Development of Learning Virtual Objects as a Strategy to Foster Student Retention in Higher Education

    OpenAIRE

    Yois S. Pascuas Rengifo; César Omar Jaramillo Morales; Fredy Antonio Verástegui González

    2015-01-01

    Rev.esc.adm.neg One of the problems that the Colombian higher education system is facing is the problem of student desertion, shwoing that a great amount of students leave their university studies during the first semesters. For this reason, the National Education Ministry and Universidad de la Amazonia implement a new strategy to foster student retention and graduation through academic levelling. This paper shows eight learning virtual objects from different learning áreas, applying tech...

  3. Storytelling in the digital world: achieving higher-level learning objectives.

    Science.gov (United States)

    Schwartz, Melissa R

    2012-01-01

    Nursing students are not passive media consumers but instead live in a technology ecosystem where digital is the language they speak. To prepare the next generation of nurses, educators must incorporate multiple technologies to improve higher-order learning. The author discusses the evolution and use of storytelling as part of the digital world and how digital stories can be aligned with Bloom's Taxonomy so that students achieve higher-level learning objectives.

  4. Creative Generation of 3D Objects with Deep Learning and Innovation Engines

    DEFF Research Database (Denmark)

    Lehman, Joel Anthony; Risi, Sebastian; Clune, Jeff

    2016-01-01

    Advances in supervised learning with deep neural networks have enabled robust classification in many real world domains. An interesting question is if such advances can also be leveraged effectively for computational creativity. One insight is that because evolutionary algorithms are free from st...... creativity. The results of this automated process are interesting and recognizable 3D-printable objects, demonstrating the creative potential for combining evolutionary computation and deep learning in this way....

  5. Integrating language and content learning objectives : the Bilkent University adjunct model

    OpenAIRE

    Doğan, Egemen Barış

    2003-01-01

    Cataloged from PDF version of article. In response to a global interest in learning English, many instructional approaches, methods, and techniques have been developed. Some have been short-lived, and others have sustained themselves for longer periods of time. Content-based instruction (CBI) — a particular approach to CBI involving a pairing of language and content classes with shared language and content learning objectives — have been considered as viable ways to teach la...

  6. READING AUTHENTIC EFL TEXT USING VISUALIZATION AND ADVANCE ORGANIZERS IN A MULTIMEDIA LEARNING ENVIRONMENT

    OpenAIRE

    Tsuiping Chen; Huifen Lin

    2007-01-01

    The purpose of this experimental study was to compare the effects of different types of computer-generated visuals (static versus animated) and advance organizers (descriptive versus question) in enhancing comprehension and retention of a content-based lesson for learning English as a Foreign Language (EFL). Additionally, the study investigated the interactive effect of students’ existing reading proficiency level and the above-mentioned treatments on their reading comprehension achievement. ...

  7. The perceptual effects of learning object categories that predict perceptual goals

    Science.gov (United States)

    Van Gulick, Ana E.; Gauthier, Isabel

    2014-01-01

    In classic category learning studies, subjects typically learn to assign items to one of two categories, with no further distinction between how items on each side of the category boundary should be treated. In real life, however, we often learn categories that dictate further processing goals, for instance with objects in only one category requiring further individuation. Using methods from category learning and perceptual expertise, we studied the perceptual consequences of experience with objects in tasks that rely on attention to different dimensions in different parts of the space. In two experiments, subjects first learned to categorize complex objects from a single morphspace into two categories based on one morph dimension, and then learned to perform a different task, either naming or a local feature judgment, for each of the two categories. A same-different discrimination test before and after each training measured sensitivity to feature dimensions of the space. After initial categorization, sensitivity increased along the category-diagnostic dimension. After task association, sensitivity increased more for the category that was named, especially along the non-diagnostic dimension. The results demonstrate that local attentional weights, associated with individual exemplars as a function of task requirements, can have lasting effects on perceptual representations. PMID:24820671

  8. Multi-documents summarization based on clustering of learning object using hierarchical clustering

    Science.gov (United States)

    Mustamiin, M.; Budi, I.; Santoso, H. B.

    2018-03-01

    The Open Educational Resources (OER) is a portal of teaching, learning and research resources that is available in public domain and freely accessible. Learning contents or Learning Objects (LO) are granular and can be reused for constructing new learning materials. LO ontology-based searching techniques can be used to search for LO in the Indonesia OER. In this research, LO from search results are used as an ingredient to create new learning materials according to the topic searched by users. Summarizing-based grouping of LO use Hierarchical Agglomerative Clustering (HAC) with the dependency context to the user’s query which has an average value F-Measure of 0.487, while summarizing by K-Means F-Measure only has an average value of 0.336.

  9. Using text messages to bridge the intention-behavior gap? A pilot study on the use of text message reminders to increase objectively assessed physical activity in daily life

    Directory of Open Access Journals (Sweden)

    Andreas Richard Schwerdtfeger

    2012-08-01

    Full Text Available Sedentarism is a serious health concern in industrialized countries throughout the world. We examined whether a text message-based intervention, targeted at increasing daily levels of physical activity, would be more effective than a standard psychoeducational intervention and a control condition. Sixty-three individuals (43 women with a mean age of 23.7 years participated in the study. They were randomly assigned to a psychoeducational standard intervention; an augmented intervention with additional short text messages sent to the mobile phones to remind participants of their action plans, and a control condition. Objectively assessed physical activity and self-efficacy were assessed pre- and post-intervention. Participants in the control condition showed a significant decline in physical activity from pre- assessment to post-assessment, whereas participants in both intervention arms exhibited a slight increase. Moreover, the augmented intervention resulted in a marginally significant increase in self-efficacy, whereas the standard intervention resulted in a significant decrease. The findings suggest that short text messages reminding individuals of their action plans are not more effective than an intervention without text messages, although there seems to be a beneficial effect on self-efficacy, which might facilitate behavior change in the long-term. Challenging aspects of the research design (e.g., reactivity of the assessment protocol are discussed and suggestions for future research are highlighted.

  10. Audio-visual synchronization in reading while listening to texts: Effects on visual behavior and verbal learning

    OpenAIRE

    Gerbier , Emilie; Bailly , Gérard; Bosse , Marie-Line

    2018-01-01

    International audience; Reading while listening to texts (RWL) is a promising way to improve the learning benefits provided by a reading experience. In an exploratory study, we investigated the effect of synchronizing the highlighting of words (visual) with their auditory (speech) counterpart during a RWL task. Forty French children from 3rd to 5th grade read short stories in their native language while hearing the story spoken by a narrator. In the non-synchronized (S-) condition the text wa...

  11. A Machine Learning Approach to Measurement of Text Readability for EFL Learners Using Various Linguistic Features

    Science.gov (United States)

    Kotani, Katsunori; Yoshimi, Takehiko; Isahara, Hitoshi

    2011-01-01

    The present paper introduces and evaluates a readability measurement method designed for learners of EFL (English as a foreign language). The proposed readability measurement method (a regression model) estimates the text readability based on linguistic features, such as lexical, syntactic and discourse features. Text readability refers to the…

  12. Examining Mobile Learning Trends 2003-2008: A Categorical Meta-Trend Analysis Using Text Mining Techniques

    Science.gov (United States)

    Hung, Jui-Long; Zhang, Ke

    2012-01-01

    This study investigated the longitudinal trends of academic articles in Mobile Learning (ML) using text mining techniques. One hundred and nineteen (119) refereed journal articles and proceedings papers from the SCI/SSCI database were retrieved and analyzed. The taxonomies of ML publications were grouped into twelve clusters (topics) and four…

  13. Effects of Gloss Type on Text Recall and Incidental Vocabulary Learning in Mobile-Assisted L2 Listening

    Science.gov (United States)

    Çakmak, Fidel; Erçetin, Gülcan

    2018-01-01

    This study investigates the effects of multimedia glosses on text recall and incidental vocabulary learning in a mobile-assisted L2 listening task. A total of 88 participants with a low level of proficiency in English were randomly assigned to one of four conditions that involved single channel (textual-only, pictorial-only) and dual-channel…

  14. The Effects of Text Density Levels and the Cognitive Style of Field Dependence on Learning from a CBI Tutorial

    Science.gov (United States)

    Ipek, Ismail

    2011-01-01

    The purpose of this study was to investigate the effects of variations in text density levels and the cognitive style of field dependence on learning from a CBI tutorial, based on the dependent measures of achievement, reading comprehension, and reading rate, and of lesson completion time. Eighty college undergraduate students were randomly…

  15. Toward Self-Referential Autonomous Learning of Object and Situation Models.

    Science.gov (United States)

    Damerow, Florian; Knoblauch, Andreas; Körner, Ursula; Eggert, Julian; Körner, Edgar

    2016-01-01

    Most current approaches to scene understanding lack the capability to adapt object and situation models to behavioral needs not anticipated by the human system designer. Here, we give a detailed description of a system architecture for self-referential autonomous learning which enables the refinement of object and situation models during operation in order to optimize behavior. This includes structural learning of hierarchical models for situations and behaviors that is triggered by a mismatch between expected and actual action outcome. Besides proposing architectural concepts, we also describe a first implementation of our system within a simulated traffic scenario to demonstrate the feasibility of our approach.

  16. Smart learning objects for smart education in computer science theory, methodology and robot-based implementation

    CERN Document Server

    Stuikys, Vytautas

    2015-01-01

    This monograph presents the challenges, vision and context to design smart learning objects (SLOs) through Computer Science (CS) education modelling and feature model transformations. It presents the latest research on the meta-programming-based generative learning objects (the latter with advanced features are treated as SLOs) and the use of educational robots in teaching CS topics. The introduced methodology includes the overall processes to develop SLO and smart educational environment (SEE) and integrates both into the real education setting to provide teaching in CS using constructivist a

  17. Learning of perceptual grouping for object segmentation on RGB-D data.

    Science.gov (United States)

    Richtsfeld, Andreas; Mörwald, Thomas; Prankl, Johann; Zillich, Michael; Vincze, Markus

    2014-01-01

    Object segmentation of unknown objects with arbitrary shape in cluttered scenes is an ambitious goal in computer vision and became a great impulse with the introduction of cheap and powerful RGB-D sensors. We introduce a framework for segmenting RGB-D images where data is processed in a hierarchical fashion. After pre-clustering on pixel level parametric surface patches are estimated. Different relations between patch-pairs are calculated, which we derive from perceptual grouping principles, and support vector machine classification is employed to learn Perceptual Grouping. Finally, we show that object hypotheses generation with Graph-Cut finds a globally optimal solution and prevents wrong grouping. Our framework is able to segment objects, even if they are stacked or jumbled in cluttered scenes. We also tackle the problem of segmenting objects when they are partially occluded. The work is evaluated on publicly available object segmentation databases and also compared with state-of-the-art work of object segmentation.

  18. Learning based particle filtering object tracking for visible-light systems.

    Science.gov (United States)

    Sun, Wei

    2015-10-01

    We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

  19. Real-world visual statistics and infants' first-learned object names.

    Science.gov (United States)

    Clerkin, Elizabeth M; Hart, Elizabeth; Rehg, James M; Yu, Chen; Smith, Linda B

    2017-01-05

    We offer a new solution to the unsolved problem of how infants break into word learning based on the visual statistics of everyday infant-perspective scenes. Images from head camera video captured by 8 1/2 to 10 1/2 month-old infants at 147 at-home mealtime events were analysed for the objects in view. The images were found to be highly cluttered with many different objects in view. However, the frequency distribution of object categories was extremely right skewed such that a very small set of objects was pervasively present-a fact that may substantially reduce the problem of referential ambiguity. The statistical structure of objects in these infant egocentric scenes differs markedly from that in the training sets used in computational models and in experiments on statistical word-referent learning. Therefore, the results also indicate a need to re-examine current explanations of how infants break into word learning.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

  20. Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences.

    Science.gov (United States)

    Bhat, Ajaz Ahmad; Mohan, Vishwanathan; Sandini, Giulio; Morasso, Pietro

    2016-07-01

    Emerging studies indicate that several species such as corvids, apes and children solve 'The Crow and the Pitcher' task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause-effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended 'learning-prediction-abstraction' loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration. © 2016 The Author(s).

  1. The effects of captioning texts and caption ordering on L2 listening comprehension and vocabulary learning

    Directory of Open Access Journals (Sweden)

    Fatemeh Alikhani

    2013-07-01

    Full Text Available This study investigated the effects of captioned texts on second/foreign (L2 listening comprehension and vocabulary gains using a computer multimedia program. Additionally, it explored the caption ordering effect (i.e. captions displayed during the first or second listening, and the interaction of captioning order with the L2 proficiency level of language learners in listening comprehension and vocabulary performance. To these ends, a computer software program was designed and 200 EFL learners (100 high-intermediate and 100 low-intermediate level students were asked to participate in the experiment. They were randomly assigned into four groups: captioned (listening to texts twice with captions, noncaptioned (listening to texts twice without captions, first captioned (listening to texts first with captions and then without captions, and second captioned (listening to texts first without captions and then with captions groups. They listened to four audio texts (i.e. short stories twice and took the listening and vocabulary tests, administered through the software. Results from t-tests and two-way ANOVAs showed that the captioned stories were more effective than the non-captioned ones. Moreover, the caption ordering had no significant effect on the participants' L2 listening comprehension and vocabulary performance. Finally, L2 proficiency level differences did not affect performance derived from caption ordering.

  2. Intelligent system for topic survey in MEDLINE by keyword recommendation and learning text characteristics.

    Science.gov (United States)

    Tanaka, M; Nakazono, S; Matsuno, H; Tsujimoto, H; Kitamura, Y; Miyano, S

    2000-01-01

    We have implemented a system for assisting experts in selecting MEDLINE records for database construction purposes. This system has two specific features: The first is a learning mechanism which extracts characteristics in the abstracts of MEDLINE records of interest as patterns. These patterns reflect selection decisions by experts and are used for screening the records. The second is a keyword recommendation system which assists and supplements experts' knowledge in unexpected cases. Combined with a conventional keyword-based information retrieval system, this system may provide an efficient and comfortable environment for MEDLINE record selection by experts. Some computational experiments are provided to prove that this idea is useful.

  3. Assuring the Quality of Agricultural Learning Repositories: Issues for the Learning Object Metadata Creation Process of the CGIAR

    Science.gov (United States)

    Zschocke, Thomas; Beniest, Jan

    The Consultative Group on International Agricultural Re- search (CGIAR) has established a digital repository to share its teaching and learning resources along with descriptive educational information based on the IEEE Learning Object Metadata (LOM) standard. As a critical component of any digital repository, quality metadata are critical not only to enable users to find more easily the resources they require, but also for the operation and interoperability of the repository itself. Studies show that repositories have difficulties in obtaining good quality metadata from their contributors, especially when this process involves many different stakeholders as is the case with the CGIAR as an international organization. To address this issue the CGIAR began investigating the Open ECBCheck as well as the ISO/IEC 19796-1 standard to establish quality protocols for its training. The paper highlights the implications and challenges posed by strengthening the metadata creation workflow for disseminating learning objects of the CGIAR.

  4. Gaming, texting, learning? Teaching engineering ethics through students' lived experiences with technology.

    Science.gov (United States)

    Voss, Georgina

    2013-09-01

    This paper examines how young peoples' lived experiences with personal technologies can be used to teach engineering ethics in a way which facilitates greater engagement with the subject. Engineering ethics can be challenging to teach: as a form of practical ethics, it is framed around future workplace experience in a professional setting which students are assumed to have no prior experience of. Yet the current generations of engineering students, who have been described as 'digital natives', do however have immersive personal experience with digital technologies; and experiential learning theory describes how students learn ethics more successfully when they can draw on personal experience which give context and meaning to abstract theories. This paper reviews current teaching practices in engineering ethics; and examines young people's engagement with technologies including cell phones, social networking sites, digital music and computer games to identify social and ethical elements of these practices which have relevance for the engineering ethics curricula. From this analysis three case studies are developed to illustrate how facets of the use of these technologies can be drawn on to teach topics including group work and communication; risk and safety; and engineering as social experimentation. Means for bridging personal experience and professional ethics when teaching these cases are discussed. The paper contributes to research and curriculum development in engineering ethics education, and to wider education research about methods of teaching 'the net generation'.

  5. The Application of Machine Learning Algorithms for Text Mining based on Sentiment Analysis Approach

    Directory of Open Access Journals (Sweden)

    Reza Samizade

    2018-06-01

    Full Text Available Classification of the cyber texts and comments into two categories of positive and negative sentiment among social media users is of high importance in the research are related to text mining. In this research, we applied supervised classification methods to classify Persian texts based on sentiment in cyber space. The result of this research is in a form of a system that can decide whether a comment which is published in cyber space such as social networks is considered positive or negative. The comments that are published in Persian movie and movie review websites from 1392 to 1395 are considered as the data set for this research. A part of these data are considered as training and others are considered as testing data. Prior to implementing the algorithms, pre-processing activities such as tokenizing, removing stop words, and n-germs process were applied on the texts. Naïve Bayes, Neural Networks and support vector machine were used for text classification in this study. Out of sample tests showed that there is no evidence indicating that the accuracy of SVM approach is statistically higher than Naïve Bayes or that the accuracy of Naïve Bayes is not statistically higher than NN approach. However, the researchers can conclude that the accuracy of the classification using SVM approach is statistically higher than the accuracy of NN approach in 5% confidence level.

  6. Building a protein name dictionary from full text: a machine learning term extraction approach

    Directory of Open Access Journals (Sweden)

    Campagne Fabien

    2005-04-01

    Full Text Available Abstract Background The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature. Results We present an approach to recognize named entities in full text. The approach collects high frequency terms in an article, and uses support vector machines (SVM to identify biological entity names. It is also computationally efficient and robust to noise commonly found in full text material. We use the method to create a protein name dictionary from a set of 80,528 full text articles. Only 8.3% of the names in this dictionary match SwissProt description lines. We assess the quality of the dictionary by studying its protein name recognition performance in full text. Conclusion This dictionary term lookup method compares favourably to other published methods, supporting the significance of our direct extraction approach. The method is strong in recognizing name variants not found in SwissProt.

  7. Semantic Web, Reusable Learning Objects, Personal Learning Networks in Health: Key Pieces for Digital Health Literacy.

    Science.gov (United States)

    Konstantinidis, Stathis Th; Wharrad, Heather; Windle, Richard; Bamidis, Panagiotis D

    2017-01-01

    The knowledge existing in the World Wide Web is exponentially expanding, while continuous advancements in health sciences contribute to the creation of new knowledge. There are a lot of efforts trying to identify how the social connectivity can endorse patients' empowerment, while other studies look at the identification and the quality of online materials. However, emphasis has not been put on the big picture of connecting the existing resources with the patients "new habits" of learning through their own Personal Learning Networks. In this paper we propose a framework for empowering patients' digital health literacy adjusted to patients' currents needs by utilizing the contemporary way of learning through Personal Learning Networks, existing high quality learning resources and semantics technologies for interconnecting knowledge pieces. The framework based on the concept of knowledge maps for health as defined in this paper. Health Digital Literacy needs definitely further enhancement and the use of the proposed concept might lead to useful tools which enable use of understandable health trusted resources tailored to each person needs.

  8. Learning Rich Features from RGB-D Images for Object Detection and Segmentation

    OpenAIRE

    Gupta, Saurabh; Girshick, Ross; Arbeláez, Pablo; Malik, Jitendra

    2014-01-01

    In this paper we study the problem of object detection for RGB-D images using semantically rich image and depth features. We propose a new geocentric embedding for depth images that encodes height above ground and angle with gravity for each pixel in addition to the horizontal disparity. We demonstrate that this geocentric embedding works better than using raw depth images for learning feature representations with convolutional neural networks. Our final object detection system achieves an av...

  9. Catalogue of Interactive Learning Objectives to improve an Integrated Medical and Dental Curriculum.

    Science.gov (United States)

    Mahmoodi, Benjamin; Sagheb, K; Sagheb, Ka; Schulz, P; Willershausen, B; Al-Nawas, B; Walter, C

    2016-12-01

    Online learning media are increasingly being incorporated into medical and dental education. However, the coordination between obligatory and facultative teaching domains still remains unsatisfying. The Catalogue of Interactive Learning Objectives of the University Clinic of Mainz (ILKUM), aims to offer knowledge transfer for students while being mindful of their individual qualifications. Its hierarchical structure is designed according to the Association for Dental Education in Europe (ADEE) levels of competence. The ILKUM was designed to establish a stronger interconnection between already existing and prospective learning strategies. All contents are linked to the current lectures as well as to e-learning modules, e.g., clinical case studies and OR videos. Students can conduct self-examinations regarding specific learning objectives. Since 2007, ILKUM has been developed and analyzed regarding its acceptance among dental students. These improved e-learning techniques foster time and location-independent access to study materials and allow an estimation of the knowledge achieved by students. Surveys of our students clearly show a large demand for upgrading ILKUM content (89%; n = 172) with integrated self-testing (89%; n = 174). In parallel to the advancement of our e-learning offering, a portion of internet-based learning is constantly rising among students. The broad acceptance and demand for the development of ILKUM show its potential. Moreover, ILKUM grants fast, topic-oriented querying of learning content without time and locale limitations as well as direct determination of the individually needed knowledge conditions. The long-term goal of the ILKUM project is to be a sustainable, important additional modality of teaching and training for dental and medical students.

  10. Development of national competency-based learning objectives "Medical Informatics" for undergraduate medical education.

    Science.gov (United States)

    Röhrig, R; Stausberg, J; Dugas, M

    2013-01-01

    The aim of this project is to develop a catalogue of competency-based learning objectives "Medical Informatics" for undergraduate medical education (abbreviated NKLM-MI in German). The development followed a multi-level annotation and consensus process. For each learning objective a reason why a physician needs this competence was required. In addition, each objective was categorized according to the competence context (A = covered by medical informatics, B = core subject of medical informatics, C = optional subject of medical informatics), the competence level (1 = referenced knowledge, 2 = applied knowledge, 3 = routine knowledge) and a CanMEDS competence role (medical expert, communicator, collaborator, manager, health advocate, professional, scholar). Overall 42 objectives in seven areas (medical documentation and information processing, medical classifications and terminologies, information systems in healthcare, health telematics and telemedicine, data protection and security, access to medical knowledge and medical signal-/image processing) were identified, defined and consented. With the NKLM-MI the competences in the field of medical informatics vital to a first year resident physician are identified, defined and operationalized. These competencies are consistent with the recommendations of the International Medical Informatics Association (IMIA). The NKLM-MI will be submitted to the National Competence-Based Learning Objectives for Undergraduate Medical Education. The next step is implementation of these objectives by the faculties.

  11. Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks

    Science.gov (United States)

    Furfaro, R.; Linares, R.; Gaylor, D.; Jah, M.; Walls, R.

    2016-09-01

    In this paper, we present an end-to-end approach that employs machine learning techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of resident space objects. State-of-the-Art machine learning architectures (e.g. Extreme Learning Machines, Convolutional Deep Networks) are trained on physical models to learn the Resident Space Object (RSO) features in the vectorized energy and momentum states and parameters. The mapping from measurements to vectorized energy and momentum states and parameters enables behavior characterization via clustering in the features space and subsequent RSO classification. Additionally, Space Object Behavioral Ontologies (SOBO) are employed to define and capture the domain knowledge-base (KB) and BNs are constructed from the SOBO in a semi-automatic fashion to execute probabilistic reasoning over conclusions drawn from trained classifiers and/or directly from processed data. Such an approach enables integrating machine learning classifiers and probabilistic reasoning to support higher-level decision making for space domain awareness applications. The innovation here is to use these methods (which have enjoyed great success in other domains) in synergy so that it enables a "from data to discovery" paradigm by facilitating the linkage and fusion of large and disparate sources of information via a Big Data Science and Analytics framework.

  12. Learning Mathematics by Designing, Programming, and Investigating with Interactive, Dynamic Computer-Based Objects

    Science.gov (United States)

    Marshall, Neil; Buteau, Chantal

    2014-01-01

    As part of their undergraduate mathematics curriculum, students at Brock University learn to create and use computer-based tools with dynamic, visual interfaces, called Exploratory Objects, developed for the purpose of conducting pure or applied mathematical investigations. A student's Development Process Model of creating and using an Exploratory…

  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. Depth Value Pre-Processing for Accurate Transfer Learning Based RGB-D Object Recognition

    DEFF Research Database (Denmark)

    Aakerberg, Andreas; Nasrollahi, Kamal; Rasmussen, Christoffer Bøgelund

    2017-01-01

    of an existing deeplearning based RGB-D object recognition model, namely the FusionNet proposed by Eitel et al. First, we showthat encoding the depth values as colorized surface normals is beneficial, when the model is initialized withweights learned from training on ImageNet data. Additionally, we show...

  15. A Conceptual Framework for Error Remediation with Multiple External Representations Applied to Learning Objects

    Science.gov (United States)

    Leite, Maici Duarte; Marczal, Diego; Pimentel, Andrey Ricardo; Direne, Alexandre Ibrahim

    2014-01-01

    This paper presents the application of some concepts of Intelligent Tutoring Systems (ITS) to elaborate a conceptual framework that uses the remediation of errors with Multiple External Representations (MERs) in Learning Objects (LO). To this is demonstrated a development of LO for teaching the Pythagorean Theorem through this framework. This…

  16. Object-based implicit learning in visual search: perceptual segmentation constrains contextual cueing.

    Science.gov (United States)

    Conci, Markus; Müller, Hermann J; von Mühlenen, Adrian

    2013-07-09

    In visual search, detection of a target is faster when it is presented within a spatial layout of repeatedly encountered nontarget items, indicating that contextual invariances can guide selective attention (contextual cueing; Chun & Jiang, 1998). However, perceptual regularities may interfere with contextual learning; for instance, no contextual facilitation occurs when four nontargets form a square-shaped grouping, even though the square location predicts the target location (Conci & von Mühlenen, 2009). Here, we further investigated potential causes for this interference-effect: We show that contextual cueing can reliably occur for targets located within the region of a segmented object, but not for targets presented outside of the object's boundaries. Four experiments demonstrate an object-based facilitation in contextual cueing, with a modulation of context-based learning by relatively subtle grouping cues including closure, symmetry, and spatial regularity. Moreover, the lack of contextual cueing for targets located outside the segmented region was due to an absence of (latent) learning of contextual layouts, rather than due to an attentional bias towards the grouped region. Taken together, these results indicate that perceptual segmentation provides a basic structure within which contextual scene regularities are acquired. This in turn argues that contextual learning is constrained by object-based selection.

  17. Bayesian feature weighting for unsupervised learning, with application to object recognition

    OpenAIRE

    Carbonetto , Peter; De Freitas , Nando; Gustafson , Paul; Thompson , Natalie

    2003-01-01

    International audience; We present a method for variable selection/weighting in an unsupervised learning context using Bayesian shrinkage. The basis for the model parameters and cluster assignments can be computed simultaneous using an efficient EM algorithm. Applying our Bayesian shrinkage model to a complex problem in object recognition (Duygulu, Barnard, de Freitas and Forsyth 2002), our experiments yied good results.

  18. Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

    Science.gov (United States)

    Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

    2004-01-01

    Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

  19. An Analysis of Learning Objectives and Content Coverage in Introductory Psychology Syllabi

    Science.gov (United States)

    Homa, Natalie; Hackathorn, Jana; Brown, Carrie M.; Garczynski, Amy; Solomon, Erin D.; Tennial, Rachel; Sanborn, Ursula A.; Gurung, Regan A. R.

    2013-01-01

    Introductory psychology is one of the most popular undergraduate courses and often serves as the gateway to choosing psychology as an academic major. However, little research has examined the typical structure of introductory psychology courses. The current study examined student learning objectives (SLOs) and course content in introductory…

  20. Joint Attention and Object Learning in 5- and 7-Month-Old Infants

    Science.gov (United States)

    Cleveland, Allison; Schug, Mariah; Striano, Tricia

    2007-01-01

    We examined the effects of joint attention for object learning in 5- and 7-month-old infants. Infants interacted with an adult social partner who taught them about a novel toy in two conditions. In the "Joint Attention" condition, the adult spoke about the toy while alternating gaze between the infant and the toy, while in the…

  1. Diagram, a Learning Environment for Initiation to Object-Oriented Modeling with UML Class Diagrams

    Science.gov (United States)

    Py, Dominique; Auxepaules, Ludovic; Alonso, Mathilde

    2013-01-01

    This paper presents Diagram, a learning environment for object-oriented modelling (OOM) with UML class diagrams. Diagram an open environment, in which the teacher can add new exercises without constraints on the vocabulary or the size of the diagram. The interface includes methodological help, encourages self-correcting and self-monitoring, and…

  2. Design and Use of a Learning Object for Finding Complex Polynomial Roots

    Science.gov (United States)

    Benitez, Julio; Gimenez, Marcos H.; Hueso, Jose L.; Martinez, Eulalia; Riera, Jaime

    2013-01-01

    Complex numbers are essential in many fields of engineering, but students often fail to have a natural insight of them. We present a learning object for the study of complex polynomials that graphically shows that any complex polynomials has a root and, furthermore, is useful to find the approximate roots of a complex polynomial. Moreover, we…

  3. Development and Factor Analysis of an Instrument to Measure Preservice Teachers' Perceptions of Learning Objects

    Science.gov (United States)

    Sahin, Sami

    2010-01-01

    The purpose of this study was to develop a questionnaire to measure student teachers' perception of digital learning objects. The participants included 308 voluntary senior students attending courses in a college of education of a public university in Turkey. The items were extracted to their related factors by the principal axis factoring method.…

  4. Examining the Use of Web-Based Reusable Learning Objects by Animal and Veterinary Nursing Students

    Science.gov (United States)

    Chapman-Waterhouse, Emily; Silva-Fletcher, Ayona; Whittlestone, Kim David

    2016-01-01

    This intervention study examined the interaction of animal and veterinary nursing students with reusable learning objects (RLO) in the context of preparing for summative assessment. Data was collected from 199 undergraduates using quantitative and qualitative methods. Students accessed RLO via personal devices in order to reinforce taught…

  5. Development and Implementation Costs of Student Learning Objectives: Considerations for TIF Grantees

    Science.gov (United States)

    Fermanich, Mark; Carl, Brad; Finster, Matthew

    2015-01-01

    This brief explores the costs of developing and implementing Student Learning Objectives (SLOs) in order to help Teacher Incentive Fund (TIF) grantees interested in adopting SLOs anticipate and understand the costs of implementing them in a district or school. The brief focuses on the costs involved with the initial design and implementation of an…

  6. Experiences with Reusable E-Learning Objects: From Theory to Practice.

    Science.gov (United States)

    Muzio, Jeanette A.; Heins, Tanya; Mundell, Roger

    2002-01-01

    Explains reusable electronic learning objects (ELOs) that are stored in a database and discusses the practical application of creating and reusing ELOs at Royal Roads University (Canada). Highlights include ELOs and the instructional design of online courses; and examples of using templates to develop interactive ELOs. (Author/LRW)

  7. Practicing doctors' perceptions on new learning objectives for Vietnamese medical schools

    NARCIS (Netherlands)

    Hoat, L; Dung, DV; Wright, E.P.

    2008-01-01

    Background. As part of the process to develop more community-oriented medical teaching in Vietnam, eight medical schools prepared a set of standard learning objectives with attention to the needs of a doctor working with the community. Because they were prepared based on government documents and the

  8. Error-Driven Learning in Visual Categorization and Object Recognition: A Common-Elements Model

    Science.gov (United States)

    Soto, Fabian A.; Wasserman, Edward A.

    2010-01-01

    A wealth of empirical evidence has now accumulated concerning animals' categorizing photographs of real-world objects. Although these complex stimuli have the advantage of fostering rapid category learning, they are difficult to manipulate experimentally and to represent in formal models of behavior. We present a solution to the representation…

  9. A Learning Research Informed Design and Evaluation of a Web-Enhanced Object Oriented Programming Seminar

    Science.gov (United States)

    Georgantaki, Stavroula C.; Retalis, Symeon D.

    2007-01-01

    "Object-Oriented Programming" subject is included in the ACM Curriculum Guidelines for Undergraduate and Graduate Degree Programs in Computer Science as well as in Curriculum for K-12 Computer Science. In a few research studies learning problems and difficulties have been recorded, and therefore, specific pedagogical guidelines and…

  10. Designing Learning Object Repositories as Systems for Managing Educational Communities Knowledge

    Science.gov (United States)

    Sampson, Demetrios G.; Zervas, Panagiotis

    2013-01-01

    Over the past years, a number of international initiatives that recognize the importance of sharing and reusing digital educational resources among educational communities through the use of Learning Object Repositories (LORs) have emerged. Typically, these initiatives focus on collecting digital educational resources that are offered by their…

  11. Two-Way Text Messaging: An Interactive Mobile Learning Environment in Higher Education

    Science.gov (United States)

    Premadasa, H. K. Salinda; Meegama, R. G. N.

    2016-01-01

    Short messaging service (SMS) is perhaps the most popular mobile technology prevalent among students in higher education due to its ubiquitous nature and the capability of two-way communication. However, a major limitation in two-way text messaging is sending back a part of received data with the reply message. This limitation results in users of…

  12. Mobile Learning: Integrating Text Messaging into a Community College Pre-Algebra Course

    Science.gov (United States)

    Bull, Prince; McCormick, Carlos

    2012-01-01

    This study investigated the use of text messaging as an educational tool in a pre-algebra course at a community college in the central region of North Carolina. The research was conducted in two pre-algebra classes with thirty-three students and one instructor. Data were gathered using qualitative and quantitative methods. A mixed method design…

  13. The Effect of Speech-to-Text Technology on Learning a Writing Strategy

    Science.gov (United States)

    Haug, Katrina N.; Klein, Perry D.

    2018-01-01

    Previous research has shown that speech-to-text (STT) software can support students in producing a given piece of writing. This is the 1st study to investigate the use of STT to teach a writing strategy. We pretested 45 Grade 5 students on argument writing and trained them to use STT. Students participated in 4 lessons on an argument writing…

  14. Learning beyond the Classroom: Using Text Messages to Measure General Chemistry Students' Study Habits

    Science.gov (United States)

    Ye, Li; Oueini, Razanne; Dickerson, Austin P.; Lewis, Scott E.

    2015-01-01

    This study used a series of text message inquiries sent to General Chemistry students asking: "Have you studied for General Chemistry I in the past 48 hours? If so, how did you study?" This method for collecting data is novel to chemistry education research so the first research goals were to investigate the feasibility of the technique…

  15. Challenges of Transitioning to an e-Learning System with Learning Objects Capabilities

    Science.gov (United States)

    Raspopovic, Miroslava; Cvetanovic, Svetlana; Jankulovic, Aleksandar

    2016-01-01

    In order for higher education institutions, which implements blended and/or online learning to remain competitive and innovative it needs to keep up with the cutting edge technological and educational advances. This task is usually very difficult, keeping in mind the budget constraints that many institutions have. This usually implies that…

  16. Learning Object Repositories in e-Learning: Challenges for Learners in Saudi Arabia

    Science.gov (United States)

    AlMegren, Abdullah; Yassin, Siti Zuraiyni

    2013-01-01

    The advent of the millennium has seen the introduction of a new paradigm for ICT-enhanced education. Advances in ICT have led to the emergence of learning networks comprising people who want to discover and share various innovative technologies on a global scale. Over the past decade, there has been tremendous worldwide interest in the concept of…

  17. Astronomical References in Chaucer: What Can Modern Students Learn from Studying Ancient Texts?

    Directory of Open Access Journals (Sweden)

    Victor Kennedy

    2005-06-01

    Full Text Available One of the problems in the field of English literature studies is that, with compartmentalization and specialization, it becomes introspective to the point where it devolves into the study of metafiction and metacriticism. At its heart, however, literature has to be about something: Thackeray claimed its subject is human nature, but human nature is based in the interface between human and nature. This paper explores some of the problems in the interface between human knowledge, institutions, and nature, and will offer an example of cross-disciplinary, historical study to illustrate a well-known but, to most modern readers, impenetrable medieval text, Chaucer’s Treatise on the Astrolabe. It ends with three recommendations: look to history, cross boundaries between academic fields, and use practical, as well as theoretical, teaching methods.

  18. A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems

    Directory of Open Access Journals (Sweden)

    R. Venkata Rao

    2014-01-01

    Full Text Available The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-learning based optimization (TLBO algorithm adapted for multi-objective problems. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. The MO-ITLBO algorithm uses a grid-based approach to adaptively assess the non-dominated solutions (i.e. Pareto front maintained in an external archive. The performance of the MO-ITLBO algorithm is assessed by implementing it on unconstrained and constrained test problems proposed for the Congress on Evolutionary Computation 2009 (CEC 2009 competition. The performance assessment is done by using the inverted generational distance (IGD measure. The IGD measures obtained by using the MO-ITLBO algorithm are compared with the IGD measures of the other state-of-the-art algorithms available in the literature. Finally, Lexicographic ordering is used to assess the overall performance of competitive algorithms. Results have shown that the proposed MO-ITLBO algorithm has obtained the 1st rank in the optimization of unconstrained test functions and the 3rd rank in the optimization of constrained test functions.

  19. Objects Classification by Learning-Based Visual Saliency Model and Convolutional Neural Network.

    Science.gov (United States)

    Li, Na; Zhao, Xinbo; Yang, Yongjia; Zou, Xiaochun

    2016-01-01

    Humans can easily classify different kinds of objects whereas it is quite difficult for computers. As a hot and difficult problem, objects classification has been receiving extensive interests with broad prospects. Inspired by neuroscience, deep learning concept is proposed. Convolutional neural network (CNN) as one of the methods of deep learning can be used to solve classification problem. But most of deep learning methods, including CNN, all ignore the human visual information processing mechanism when a person is classifying objects. Therefore, in this paper, inspiring the completed processing that humans classify different kinds of objects, we bring forth a new classification method which combines visual attention model and CNN. Firstly, we use the visual attention model to simulate the processing of human visual selection mechanism. Secondly, we use CNN to simulate the processing of how humans select features and extract the local features of those selected areas. Finally, not only does our classification method depend on those local features, but also it adds the human semantic features to classify objects. Our classification method has apparently advantages in biology. Experimental results demonstrated that our method made the efficiency of classification improve significantly.

  20. Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences

    Science.gov (United States)

    2016-01-01

    Emerging studies indicate that several species such as corvids, apes and children solve ‘The Crow and the Pitcher’ task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause–effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended ‘learning–prediction–abstraction’ loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration. PMID:27466440

  1. Learning object location predictors with boosting and grammar-guided feature extraction

    Energy Technology Data Exchange (ETDEWEB)

    Eads, Damian Ryan [Los Alamos National Laboratory; Rosten, Edward [UNIV OF CAMBRIDGE; Helmbold, David [UC/SANTA CRUZ

    2009-01-01

    The authors present BEAMER: a new spatially exploitative approach to learning object detectors which shows excellent results when applied to the task of detecting objects in greyscale aerial imagery in the presence of ambiguous and noisy data. There are four main contributions used to produce these results. First, they introduce a grammar-guided feature extraction system, enabling the exploration of a richer feature space while constraining the features to a useful subset. This is specified with a rule-based generative grammer crafted by a human expert. Second, they learn a classifier on this data using a newly proposed variant of AdaBoost which takes into account the spatially correlated nature of the data. Third, they perform another round of training to optimize the method of converting the pixel classifications generated by boosting into a high quality set of (x,y) locations. lastly, they carefully define three common problems in object detection and define two evaluation criteria that are tightly matched to these problems. Major strengths of this approach are: (1) a way of randomly searching a broad feature space, (2) its performance when evaluated on well-matched evaluation criteria, and (3) its use of the location prediction domain to learn object detectors as well as to generate detections that perform well on several tasks: object counting, tracking, and target detection. They demonstrate the efficacy of BEAMER with a comprehensive experimental evaluation on a challenging data set.

  2. Effects of Image-Based and Text-Based Active Learning Exercises on Student Examination Performance in a Musculoskeletal Anatomy Course

    Science.gov (United States)

    Gross, M. Melissa; Wright, Mary C.; Anderson, Olivia S.

    2017-01-01

    Research on the benefits of visual learning has relied primarily on lecture-based pedagogy, but the potential benefits of combining active learning strategies with visual and verbal materials on learning anatomy has not yet been explored. In this study, the differential effects of text-based and image-based active learning exercises on examination…

  3. Usage Volume and Trends Indicate Academic Library Online Learning Objects and Tutorials Are Being Used

    Directory of Open Access Journals (Sweden)

    Ruby Muriel Lavallee Warren

    2017-03-01

    Full Text Available A Review of: Hess, A. N., & Hristova, M. (2016. To search or to browse: How users navigate a new interface for online library tutorials. College & Undergraduate Libraries, 23(2, 168-183. http://dx.doi.org/10.1080/10691316.2014.963274 Objective – To discover how users interact with a new online interface for learning objects, user preferences for types of access when given both browsing and searching options, and user needs for tutorial subject matter. Design – Mixed methods, with quantitative analysis of web traffic and qualitative analysis of recorded search terms through grounded textual theory. Setting – An academic library in the Western United States of America. Subjects – Users of the Libraries’ online tutorials and learning objects. Methods – The researchers collected web traffic statistics and organically occurring searches from the Libraries’ tutorial access interface. They defined the collection period as the 2013/2014 academic year, with collection beginning in September 2013 and ending in April 2014. Web traffic for organic searches, facilitated searches (search results accessed through clicking on particular words in a tag cloud, and categorical browsing was collected via Google Analytics. They categorized other interaction types (accessing featured content, leaving the page, etc. under an umbrella term of “other.” Their analysis of web traffic was limited to unique page views, with unique page views defined as views registered to different browser sessions. Unique page views were analyzed to determine which types of interface interaction occurred most frequently, both on-campus and off-campus, and whether there were differences in types of interaction preferred over time or by users with different points of origin. Individual organic search keywords and phrases, and the dates and times of those searches, were separately collected and recorded. One of the researchers coded the recorded organic search terms using

  4. Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

    Science.gov (United States)

    Fiorini, Rodolfo A.; Dacquino, Gianfranco

    2005-03-01

    GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous

  5. Alignment of learning objectives and assessments in therapeutics courses to foster higher-order thinking.

    Science.gov (United States)

    FitzPatrick, Beverly; Hawboldt, John; Doyle, Daniel; Genge, Terri

    2015-02-17

    To determine whether national educational outcomes, course objectives, and classroom assessments for 2 therapeutics courses were aligned for curricular content and cognitive processes, and if they included higher-order thinking. Document analysis and student focus groups were used. Outcomes, objectives, and assessment tasks were matched for specific therapeutics content and cognitive processes. Anderson and Krathwohl's Taxonomy was used to define higher-order thinking. Students discussed whether assessments tested objectives and described their thinking when responding to assessments. There were 7 outcomes, 31 objectives, and 412 assessment tasks. The alignment for content and cognitive processes was not satisfactory. Twelve students participated in the focus groups. Students thought more short-answer questions than multiple choice questions matched the objectives for content and required higher-order thinking. The alignment analysis provided data that could be used to reveal and strengthen the enacted curriculum and improve student learning.

  6. On hierarchical models for visual recognition and learning of objects, scenes, and activities

    CERN Document Server

    Spehr, Jens

    2015-01-01

    In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model...

  7. A scalable machine-learning approach to recognize chemical names within large text databases

    Directory of Open Access Journals (Sweden)

    Wren Jonathan D

    2006-09-01

    Full Text Available Abstract Motivation The use or study of chemical compounds permeates almost every scientific field and in each of them, the amount of textual information is growing rapidly. There is a need to accurately identify chemical names within text for a number of informatics efforts such as database curation, report summarization, tagging of named entities and keywords, or the development/curation of reference databases. Results A first-order Markov Model (MM was evaluated for its ability to distinguish chemical names from words, yielding ~93% recall in recognizing chemical terms and ~99% precision in rejecting non-chemical terms on smaller test sets. However, because total false-positive events increase with the number of words analyzed, the scalability of name recognition was measured by processing 13.1 million MEDLINE records. The method yielded precision ranges from 54.7% to 100%, depending upon the cutoff score used, averaging 82.7% for approximately 1.05 million putative chemical terms extracted. Extracted chemical terms were analyzed to estimate the number of spelling variants per term, which correlated with the total number of times the chemical name appeared in MEDLINE. This variability in term construction was found to affect both information retrieval and term mapping when using PubMed and Ovid.

  8. The Computer Book of the Internal Medicine Resident: competence acquisition and achievement of learning objectives.

    Science.gov (United States)

    Oristrell, J; Oliva, J C; Casanovas, A; Comet, R; Jordana, R; Navarro, M

    2014-01-01

    The Computer Book of the Internal Medicine resident (CBIMR) is a computer program that was validated to analyze the acquisition of competences in teams of Internal Medicine residents. To analyze the characteristics of the rotations during the Internal Medicine residency and to identify the variables associated with the acquisition of clinical and communication skills, the achievement of learning objectives and resident satisfaction. All residents of our service (n=20) participated in the study during a period of 40 months. The CBIMR consisted of 22 self-assessment questionnaires specific for each rotation, with items on services (clinical workload, disease protocolization, resident responsibilities, learning environment, service organization and teamwork) and items on educational outcomes (acquisition of clinical and communication skills, achievement of learning objectives, overall satisfaction). Associations between services features and learning outcomes were analyzed using bivariate and multivariate analysis. An intense clinical workload, high resident responsibilities and disease protocolization were associated with the acquisition of clinical skills. High clinical competence and teamwork were both associated with better communication skills. Finally, an adequate learning environment was associated with increased clinical competence, the achievement of educational goals and resident satisfaction. Potentially modifiable variables related with the operation of clinical services had a significant impact on the acquisition of clinical and communication skills, the achievement of educational goals, and resident satisfaction during the specialized training in Internal Medicine. Copyright © 2013 Elsevier España, S.L. All rights reserved.

  9. E-learning teaches attendings "how to" objectively assess pediatric urology trainees' surgery skills for orchiopexy.

    Science.gov (United States)

    Fernandez, Nicolas; Maizels, Max; Farhat, Walid; Smith, Edwin; Liu, Dennis; Chua, Michael; Bhanji, Yasin

    2018-04-01

    Established methods to train pediatric urology surgery by residency training programs require updating in response to administrative changes such as new, reduced trainee duty hours. Therefore, new objective methods must be developed to teach trainees. We approached this need by creating e-learning to teach attendings objective assessment of trainee skills using the Zwisch scale, an established assessment tool. The aim of this study was to identify whether or not e-learning is an appropriate platform for effective teaching of this assessment tool, by assessing inter-rater correlation of assessments made by the attendings after participation in the e-learning. Pediatric orchiopexy was used as the index case. An e-learning tool was created to teach attending surgeons objective assessment of trainees' surgical skills. First, e-learning content was created which showed the assessment method videotape of resident surgery done in the operating room. Next, attendings were enrolled to e-learn this method. Finally, the ability of enrollees to assess resident surgery skill performance was tested. Namely, test video was made showing a trainee performing inguinal orchiopexy. All enrollees viewed the same online videos. Assessments of surgical skills (Zwisch scale) were entered into an online survey. Data were analyzed by intercorrelation coefficient kappa analysis (strong correlation was ICC ≥ 0.7). A total of 11 attendings were enrolled. All accessed the online learning and then made assessments of surgical skills trainees showed on videotapes. The e-learning comprised three modules: 1. "Core concepts," in which users learned the assessment tool methods; 2. "Learn to assess," in which users learned how to assess by watching video clips, explaining the assessment method; and 3. "Test," in which users tested their skill at making assessments by watching video clips and then actively inputting their ratings of surgical and global skills as viewed in the video clips (Figure

  10. Assessment of Online Information Literacy Learning Objects For First Year Community

    Directory of Open Access Journals (Sweden)

    Mara Bordignon

    2016-09-01

    Full Text Available Objective – The main objective was to determine whether information literacy (IL learning objects (LOs impact student IL competency, specifically in a foundational first year English composition course. The primary research question was: What is the effectiveness of IL LOs compared to face-to-face instruction in terms of students’ skill acquisition? Methods – The methods involved testing student IL competency through a multiple-choice test given pre- and post-IL intervention. Effectiveness was measured by assessing whether IL competency improves after exposure to one of two interventions: online IL LOs or face-to-face librarian-led workshop. Over two semesters, equal sections of the course were tested for each of these interventions. For the IL LOs group, students first completed a pre-test, then they worked independently through three online IL LOs. The three IL LOs were videos comprised of animation, screen casting, and video capture on these topics: Finding Articles at Seneca Libraries (hereafter referred to as Finding Articles, Finding Articles on Current Issues, and Popular and Scholarly Sources. The students were then given the same test again. For the face-to-face group, the pre- and post-tests were also required for the same number of sections. This study was conducted under institutional ethics approval. Results – Descriptive analysis revealed student test scores increased for both interventions, IL LOs and face-to-face. Test scores increased, on average, between 14 to 37%. In comparing post-tests, results revealed a statistically significant difference only with the first topic, Finding Articles. In this case, the IL LOs (video group outperformed the face-to-face group by at least 10%. No significance, in terms of performance from pre- and post-test scores, was found for the other two topics. Conclusion – Both IL LO and face-to-face library led workshop interventions had a positive impact on students’ IL skill acquisition

  11. Learning Clinical Procedures Through Internet Digital Objects: Experience of Undergraduate Students Across Clinical Faculties.

    Science.gov (United States)

    Li, Tse Yan; Gao, Xiaoli; Wong, Kin; Tse, Christine Shuk Kwan; Chan, Ying Yee

    2015-04-14

    Various digital learning objects (DLOs) are available via the World Wide Web, showing the flow of clinical procedures. It is unclear to what extent these freely accessible Internet DLOs facilitate or hamper students' acquisition of clinical competence. This study aimed to understand the experience of undergraduate students across clinical disciplines-medicine, dentistry, and nursing-in using openly accessible Internet DLOs, and to investigate the role of Internet DLOs in facilitating their clinical learning. Mid-year and final-year groups were selected from each undergraduate clinical degree program of the University of Hong Kong-Bachelor of Medicine and Bachelor of Surgery (MBBS), Bachelor of Dental Surgery (BDS), and Bachelor of Nursing (BNurs). All students were invited to complete a questionnaire on their personal and educational backgrounds, and their experiences and views on using Internet DLOs in learning clinical procedures. The questionnaire design was informed by the findings of six focus groups. Among 439 respondents, 97.5% (428/439) learned a variety of clinical procedures through Internet DLOs. Most nursing students (107/122, 87.7%) learned preventive measures through Internet DLOs, with a lower percentage of medical students (99/215, 46.0%) and dental students (43/96, 45%) having learned them this way (both Plearning in the planned curriculum. This trend calls for a transformation of the educator's role from dispensing knowledge to guidance and support.

  12. Linking actions and objects: Context-specific learning of novel weight priors.

    Science.gov (United States)

    Trewartha, Kevin M; Flanagan, J Randall

    2017-06-01

    Distinct explicit and implicit memory processes support weight predictions used when lifting objects and making perceptual judgments about weight, respectively. The first time that an object is encountered weight is predicted on the basis of learned associations, or priors, linking size and material to weight. A fundamental question is whether the brain maintains a single, global representation of priors, or multiple representations that can be updated in a context specific way. A second key question is whether the updating of priors, or the ability to scale lifting forces when repeatedly lifting unusually weighted objects requires focused attention. To investigate these questions we compared the adaptability of weight predictions used when lifting objects and judging their weights in different groups of participants who experienced size-weight inverted objects passively (with the objects placed on the hands) or actively (where participants lift the objects) under full or divided attention. To assess weight judgments we measured the size-weight illusion after every 20 trials of experience with the inverted objects both passively and actively. The attenuation of the illusion that arises when lifting inverted object was found to be context-specific such that the attenuation was larger when the mode of interaction with the inverted objects matched the method of assessment of the illusion. Dividing attention during interaction with the inverted objects had no effect on attenuation of the illusion, but did slow the rate at which lifting forces were scaled to the weight inverted objects. These findings suggest that the brain stores multiple representations of priors that are context specific, and that focused attention is important for scaling lifting forces, but not for updating weight predictions used when judging object weight. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Applications of Speech-to-Text Recognition and Computer-Aided Translation for Facilitating Cross-Cultural Learning through a Learning Activity: Issues and Their Solutions

    Science.gov (United States)

    Shadiev, Rustam; Wu, Ting-Ting; Sun, Ai; Huang, Yueh-Min

    2018-01-01

    In this study, 21 university students, who represented thirteen nationalities, participated in an online cross-cultural learning activity. The participants were engaged in interactions and exchanges carried out on Facebook® and Skype® platforms, and their multilingual communications were supported by speech-to-text recognition (STR) and…

  14. Reading to learn experimental practice: The role of text and firsthand experience in the acquisition of an abstract science principle

    Science.gov (United States)

    Richmond, Erica Kesin

    2008-10-01

    From the onset of schooling, texts are used as important educational tools. In the primary years, they are integral to learning how to decode and develop fluency. In the later elementary years, they are often essential to the acquisition of academic content. Unfortunately, many children experience difficulties with this process, which is due in large part to their unfamiliarity with the genre of academic texts. The articles presented in this dissertation share an underlying theme of how to develop children's ability to comprehend and learn from academic, and specifically, non-narrative texts. The first article reviews research on the development of non-narrative discourse to elucidate the linguistic precursors to non-narrative text comprehension. The second and third articles draw from an empirical study that investigated the best way to integrate text, manipulation, and first-hand experience for children's acquisition and application of an abstract scientific principle. The scientific principle introduced in the study was the Control of Variables Strategy (CVS), a fundamental idea underlying scientific reasoning and a strategy for designing unconfounded experiments. Eight grade 4 classes participated in the study (N = 129), in one of three conditions: (a) read procedural text and manipulate experimental materials, (b) listen to procedural text and manipulate experimental materials, or (c) read procedural text with no opportunity to manipulate experimental materials. Findings from the study indicate that children who had the opportunity to read and manipulate materials were most effective at applying the strategy to designing and justifying unconfounded experiments, and evaluating written and physical experimental designs; however, there was no effect of instructional condition on a written assessment of evaluating familiar and unfamiliar experimental designs one week after the intervention. These results suggest that the acquisition and application of an abstract

  15. Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

    Science.gov (United States)

    Villaverde, Monica; Perez, David; Moreno, Felix

    2015-11-17

    The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

  16. Active learning in the lecture theatre using 3D printed objects.

    Science.gov (United States)

    Smith, David P

    2016-01-01

    The ability to conceptualize 3D shapes is central to understanding biological processes. The concept that the structure of a biological molecule leads to function is a core principle of the biochemical field. Visualisation of biological molecules often involves vocal explanations or the use of two dimensional slides and video presentations. A deeper understanding of these molecules can however be obtained by the handling of objects. 3D printed biological molecules can be used as active learning tools to stimulate engagement in large group lectures. These models can be used to build upon initial core knowledge which can be delivered in either a flipped form or a more didactic manner. Within the teaching session the students are able to learn by handling, rotating and viewing the objects to gain an appreciation, for example, of an enzyme's active site or the difference between the major and minor groove of DNA. Models and other artefacts can be handled in small groups within a lecture theatre and act as a focal point to generate conversation. Through the approach presented here core knowledge is first established and then supplemented with high level problem solving through a "Think-Pair-Share" cooperative learning strategy. The teaching delivery was adjusted based around experiential learning activities by moving the object from mental cognition and into the physical environment. This approach led to students being able to better visualise biological molecules and a positive engagement in the lecture. The use of objects in teaching allows the lecturer to create interactive sessions that both challenge and enable the student.

  17. Social interaction facilitates word learning in preverbal infants: Word-object mapping and word segmentation.

    Science.gov (United States)

    Hakuno, Yoko; Omori, Takahide; Yamamoto, Jun-Ichi; Minagawa, Yasuyo

    2017-08-01

    In natural settings, infants learn spoken language with the aid of a caregiver who explicitly provides social signals. Although previous studies have demonstrated that young infants are sensitive to these signals that facilitate language development, the impact of real-life interactions on early word segmentation and word-object mapping remains elusive. We tested whether infants aged 5-6 months and 9-10 months could segment a word from continuous speech and acquire a word-object relation in an ecologically valid setting. In Experiment 1, infants were exposed to a live tutor, while in Experiment 2, another group of infants were exposed to a televised tutor. Results indicate that both younger and older infants were capable of segmenting a word and learning a word-object association only when the stimuli were derived from a live tutor in a natural manner, suggesting that real-life interaction enhances the learning of spoken words in preverbal infants. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Machine learning in infrared object classification - an all-sky selection of YSO candidates

    Science.gov (United States)

    Marton, Gabor; Zahorecz, Sarolta; Toth, L. Viktor; Magnus McGehee, Peregrine; Kun, Maria

    2015-08-01

    Object classification is a fundamental and challenging problem in the era of big data. I will discuss up-to-date methods and their application to classify infrared point sources.We analysed the ALLWISE catalogue, the most recent public source catalogue of the Wide-field Infrared Survey Explorer (WISE) to compile a reliable list of Young Stellar Object (YSO) candidates. We tested and compared classical and up-to-date statistical methods as well, to discriminate source types like extragalactic objects, evolved stars, main sequence stars, objects related to the interstellar medium and YSO candidates by using their mid-IR WISE properties and associated near-IR 2MASS data.In the particular classification problem the Support Vector Machines (SVM), a class of supervised learning algorithm turned out to be the best tool. As a result we classify Class I and II YSOs with >90% accuracy while the fraction of contaminating extragalactic objects remains well below 1%, based on the number of known objects listed in the SIMBAD and VizieR databases. We compare our results to other classification schemes from the literature and show that the SVM outperforms methods that apply linear cuts on the colour-colour and colour-magnitude space. Our homogenous YSO candidate catalog can serve as an excellent pathfinder for future detailed observations of individual objects and a starting point of statistical studies that aim to add pieces to the big picture of star formation theory.

  19. Grids in topographic maps reduce distortions in the recall of learned object locations.

    Science.gov (United States)

    Edler, Dennis; Bestgen, Anne-Kathrin; Kuchinke, Lars; Dickmann, Frank

    2014-01-01

    To date, it has been shown that cognitive map representations based on cartographic visualisations are systematically distorted. The grid is a traditional element of map graphics that has rarely been considered in research on perception-based spatial distortions. Grids do not only support the map reader in finding coordinates or locations of objects, they also provide a systematic structure for clustering visual map information ("spatial chunks"). The aim of this study was to examine whether different cartographic kinds of grids reduce spatial distortions and improve recall memory for object locations. Recall performance was measured as both the percentage of correctly recalled objects (hit rate) and the mean distance errors of correctly recalled objects (spatial accuracy). Different kinds of grids (continuous lines, dashed lines, crosses) were applied to topographic maps. These maps were also varied in their type of characteristic areas (LANDSCAPE) and different information layer compositions (DENSITY) to examine the effects of map complexity. The study involving 144 participants shows that all experimental cartographic factors (GRID, LANDSCAPE, DENSITY) improve recall performance and spatial accuracy of learned object locations. Overlaying a topographic map with a grid significantly reduces the mean distance errors of correctly recalled map objects. The paper includes a discussion of a square grid's usefulness concerning object location memory, independent of whether the grid is clearly visible (continuous or dashed lines) or only indicated by crosses.

  20. Small Schools Student Learning Objectives, 9-12: Mathematics, Reading, Reading in the Content Areas, Language Arts.

    Science.gov (United States)

    Nelson, JoAnne, Ed.; Hartl, David, Ed.

    Designed by Washington curriculum specialists and secondary teachers to assist teachers in small schools with the improvement of curriculum and instruction and to aid smaller districts lacking curriculum personnel to comply with Washington's Student Learning Objectives Law, this handbook contains learning objectives in the areas of language arts,…

  1. Video Cases in Teacher Education: A review study on intended and achieved learning objectives by video cases

    NARCIS (Netherlands)

    Geerts, Walter; Van der Werff, Anne; Hummel, Hans; Van Geert, Paul

    2014-01-01

    This literature review focuses on the use of video cases in the education of preservice teachers as a means of achieving higher order learning objectives that are necessary for gaining situated knowledge. An overview of both intended and achieved learning objectives in relevant studies involving

  2. Object-Based Change Detection in Urban Areas from High Spatial Resolution Images Based on Multiple Features and Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2018-02-01

    Full Text Available To improve the accuracy of change detection in urban areas using bi-temporal high-resolution remote sensing images, a novel object-based change detection scheme combining multiple features and ensemble learning is proposed in this paper. Image segmentation is conducted to determine the objects in bi-temporal images separately. Subsequently, three kinds of object features, i.e., spectral, shape and texture, are extracted. Using the image differencing process, a difference image is generated and used as the input for nonlinear supervised classifiers, including k-nearest neighbor, support vector machine, extreme learning machine and random forest. Finally, the results of multiple classifiers are integrated using an ensemble rule called weighted voting to generate the final change detection result. Experimental results of two pairs of real high-resolution remote sensing datasets demonstrate that the proposed approach outperforms the traditional methods in terms of overall accuracy and generates change detection maps with a higher number of homogeneous regions in urban areas. Moreover, the influences of segmentation scale and the feature selection strategy on the change detection performance are also analyzed and discussed.

  3. Learning objects? Nurse educators' views on using patients for student learning : ethics and consent.

    Science.gov (United States)

    Torrance, C; Mansell, I; Wilson, C

    2012-11-01

    This study explored the views of nursing lecturers concerning the use of patients in nursing education, particularly in light of the development of additional learning opportunities such as clinical simulation. Focus group interviews involving 19 educators from one school of nursing in the United Kingdom were held. An interview schedule was developed by the study team from the findings of a focused literature review of the area. The focus groups were audio-taped and transcribed into NVivo (version 8) for analysis and identification of emergent themes. Four major categories emerged from the data analysis: clinical placement; patient consent; educator conflict; and developing competency. The themes of clinical placement and patient consent are presented in this paper. Clinical placement revealed two sub-themes: historical custom and practice and safety. Four sub-themes emerged from the theme of patient consent: informed consent; implied consent; capacity to consent; and patients' value of student involvement in their care. Educators believed that patients benefit from being cared for by well-qualified nurses and to achieve this it is necessary for patients to participate in clinical training. The predominant view seemed to be one of historical necessity; essentially, it has always been done that way so it has to continue that way. There was an awareness of the need for staff and students to consider the patient's rights and wishes, but the prevailing sentiment seemed to be that informed consent and choice were secondary to patient safety and the need to train student nurses. There is some conflict between the need for educating health professions and the Kantian view of never using the patients as a means to an end. Using patients for nursing education may be ethical as long as the patient is fully informed and involved in the decision-making process.

  4. Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

    Science.gov (United States)

    Huang, Chang-Qin; Yang, Shang-Ming; Pan, Yan; Lai, Han-Jiang

    2018-09-01

    Learning-based hashing is a leading approach of approximate nearest neighbor search for large-scale image retrieval. In this paper, we develop a deep supervised hashing method for multi-label image retrieval, in which we propose to learn a binary "mask" map that can identify the approximate locations of objects in an image, so that we use this binary "mask" map to obtain length-limited hash codes which mainly focus on an image's objects but ignore the background. The proposed deep architecture consists of four parts: 1) a convolutional sub-network to generate effective image features; 2) a binary "mask" sub-network to identify image objects' approximate locations; 3) a weighted average pooling operation based on the binary "mask" to obtain feature representations and hash codes that pay most attention to foreground objects but ignore the background; and 4) the combination of a triplet ranking loss designed to preserve relative similarities among images and a cross entropy loss defined on image labels. We conduct comprehensive evaluations on four multi-label image data sets. The results indicate that the proposed hashing method achieves superior performance gains over the state-of-the-art supervised or unsupervised hashing baselines.

  5. Directed Activities Related to Text: Text Analysis and Text Reconstruction.

    Science.gov (United States)

    Davies, Florence; Greene, Terry

    This paper describes Directed Activities Related to Text (DART), procedures that were developed and are used in the Reading for Learning Project at the University of Nottingham (England) to enhance learning from texts and that fall into two broad categories: (1) text analysis procedures, which require students to engage in some form of analysis of…

  6. The Deflector Selector: A machine learning framework for prioritizing hazardous object deflection technology development

    Science.gov (United States)

    Nesvold, E. R.; Greenberg, A.; Erasmus, N.; van Heerden, E.; Galache, J. L.; Dahlstrom, E.; Marchis, F.

    2018-05-01

    Several technologies have been proposed for deflecting a hazardous Solar System object on a trajectory that would otherwise impact the Earth. The effectiveness of each technology depends on several characteristics of the given object, including its orbit and size. The distribution of these parameters in the likely population of Earth-impacting objects can thus determine which of the technologies are most likely to be useful in preventing a collision with the Earth. None of the proposed deflection technologies has been developed and fully tested in space. Developing every proposed technology is currently prohibitively expensive, so determining now which technologies are most likely to be effective would allow us to prioritize a subset of proposed deflection technologies for funding and development. We present a new model, the Deflector Selector, that takes as its input the characteristics of a hazardous object or population of such objects and predicts which technology would be able to perform a successful deflection. The model consists of a machine-learning algorithm trained on data produced by N-body integrations simulating the deflections. We describe the model and present the results of tests of the effectiveness of nuclear explosives, kinetic impactors, and gravity tractors on three simulated populations of hazardous objects.

  7. The Deflector Selector: A Machine Learning Framework for Prioritizing Hazardous Object Deflection Technology Development

    Science.gov (United States)

    Nesvold, Erika; Greenberg, Adam; Erasmus, Nicolas; Van Heerden, Elmarie; Galache, J. L.; Dahlstrom, Eric; Marchis, Franck

    2018-01-01

    Several technologies have been proposed for deflecting a hazardous Solar System object on a trajectory that would otherwise impact the Earth. The effectiveness of each technology depends on several characteristics of the given object, including its orbit and size. The distribution of these parameters in the likely population of Earth-impacting objects can thus determine which of the technologies are most likely to be useful in preventing a collision with the Earth. None of the proposed deflection technologies has been developed and fully tested in space. Developing every proposed technology is currently prohibitively expensive, so determining now which technologies are most likely to be effective would allow us to prioritize a subset of proposed deflection technologies for funding and development. We will present a new model, the Deflector Selector, that takes as its input the characteristics of a hazardous object or population of such objects and predicts which technology would be able to perform a successful deflection. The model consists of a machine-learning algorithm trained on data produced by N-body integrations simulating the deflections. We will describe the model and present the results of tests of the effectiveness of nuclear explosives, kinetic impactors, and gravity tractors on three simulated populations of hazardous objects.

  8. Learning Clinical Procedures Through Internet Digital Objects: Experience of Undergraduate Students Across Clinical Faculties

    Science.gov (United States)

    Li, Tse Yan; Wong, Kin; Tse, Christine Shuk Kwan; Chan, Ying Yee

    2015-01-01

    Background Various digital learning objects (DLOs) are available via the World Wide Web, showing the flow of clinical procedures. It is unclear to what extent these freely accessible Internet DLOs facilitate or hamper students’ acquisition of clinical competence. Objective This study aimed to understand the experience of undergraduate students across clinical disciplines—medicine, dentistry, and nursing—in using openly accessible Internet DLOs, and to investigate the role of Internet DLOs in facilitating their clinical learning. Methods Mid-year and final-year groups were selected from each undergraduate clinical degree program of the University of Hong Kong—Bachelor of Medicine and Bachelor of Surgery (MBBS), Bachelor of Dental Surgery (BDS), and Bachelor of Nursing (BNurs). All students were invited to complete a questionnaire on their personal and educational backgrounds, and their experiences and views on using Internet DLOs in learning clinical procedures. The questionnaire design was informed by the findings of six focus groups. Results Among 439 respondents, 97.5% (428/439) learned a variety of clinical procedures through Internet DLOs. Most nursing students (107/122, 87.7%) learned preventive measures through Internet DLOs, with a lower percentage of medical students (99/215, 46.0%) and dental students (43/96, 45%) having learned them this way (both Pstudents accessed DLOs through public search engines, whereas 93.2% (409/439) accessed them by watching YouTube videos. Students often shared DLOs with classmates (277/435, 63.7%), but rarely discussed them with teachers (54/436, 12.4%). The accuracy, usefulness, and importance of Internet DLOs were rated as 6.85 (SD 1.48), 7.27 (SD 1.53), and 7.13 (SD 1.72), respectively, out of a high score of 10. Conclusions Self-exploration of DLOs in the unrestricted Internet environment is extremely common among current e-generation learners and was regarded by students across clinical faculties as an important

  9. Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

    Science.gov (United States)

    Xue, Ming; Yang, Hua; Zheng, Shibao; Zhou, Yi; Yu, Zhenghua

    2014-01-01

    To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV) function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks. PMID:24549252

  10. Reaching Consensus on Essential Biomedical Science Learning Objectives in a Dental Curriculum.

    Science.gov (United States)

    Best, Leandra; Walton, Joanne N; Walker, Judith; von Bergmann, HsingChi

    2016-04-01

    This article describes how the University of British Columbia Faculty of Dentistry reached consensus on essential basic biomedical science objectives for DMD students and applied the information to the renewal of its DMD curriculum. The Delphi Method was used to build consensus among dental faculty members and students regarding the relevance of over 1,500 existing biomedical science objectives. Volunteer panels of at least three faculty members (a basic scientist, a general dentist, and a dental specialist) and a fourth-year dental student were formed for each of 13 biomedical courses in the first two years of the program. Panel members worked independently and anonymously, rating each course objective as "need to know," "nice to know," "irrelevant," or "don't know." Panel members were advised after each round which objectives had not yet achieved a 75% consensus and were asked to reconsider their ratings. After a maximum of three rounds to reach consensus, a second group of faculty experts reviewed and refined the results to establish the biomedical science objectives for the renewed curriculum. There was consensus on 46% of the learning objectives after round one, 80% after round two, and 95% after round three. The second expert group addressed any remaining objectives as part of its review process. Only 47% of previous biomedical science course objectives were judged to be essential or "need to know" for the general dentist. The consensus reached by participants in the Delphi Method panels and a second group of faculty experts led to a streamlined, better integrated DMD curriculum to prepare graduates for future practice.

  11. Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

    Science.gov (United States)

    Ferreria, Paulo Victor R.; Paffenroth, Randy; Wyglinski, Alexander M.; Hackett, Timothy M.; Bilen, Sven G.; Reinhart, Richard C.; Mortensen, Dale J.

    2017-01-01

    Future communication subsystems of space exploration missions can potentially benefit from software-defined radios (SDRs) controlled by machine learning algorithms. In this paper, we propose a novel hybrid radio resource allocation management control algorithm that integrates multi-objective reinforcement learning and deep artificial neural networks. The objective is to efficiently manage communications system resources by monitoring performance functions with common dependent variables that result in conflicting goals. The uncertainty in the performance of thousands of different possible combinations of radio parameters makes the trade-off between exploration and exploitation in reinforcement learning (RL) much more challenging for future critical space-based missions. Thus, the system should spend as little time as possible on exploring actions, and whenever it explores an action, it should perform at acceptable levels most of the time. The proposed approach enables on-line learning by interactions with the environment and restricts poor resource allocation performance through virtual environment exploration. Improvements in the multiobjective performance can be achieved via transmitter parameter adaptation on a packet-basis, with poorly predicted performance promptly resulting in rejected decisions. Simulations presented in this work considered the DVB-S2 standard adaptive transmitter parameters and additional ones expected to be present in future adaptive radio systems. Performance results are provided by analysis of the proposed hybrid algorithm when operating across a satellite communication channel from Earth to GEO orbit during clear sky conditions. The proposed approach constitutes part of the core cognitive engine proof-of-concept to be delivered to the NASA Glenn Research Center SCaN Testbed located onboard the International Space Station.

  12. Struggling readers learning with graphic-rich digital science text: Effects of a Highlight & Animate Feature and Manipulable Graphics

    Science.gov (United States)

    Defrance, Nancy L.

    Technology offers promise of 'leveling the playing field' for struggling readers. That is, instructional support features within digital texts may enable all readers to learn. This quasi-experimental study examined the effects on learning of two support features, which offered unique opportunities to interact with text. The Highlight & Animate Feature highlighted an important idea in prose, while simultaneously animating its representation in an adjacent graphic. It invited readers to integrate ideas depicted in graphics and prose, using each one to interpret the other. The Manipulable Graphics had parts that the reader could operate to discover relationships among phenomena. It invited readers to test or refine the ideas that they brought to, or gleaned from, the text. Use of these support features was compulsory. Twenty fifth grade struggling readers read a graphic-rich digital science text in a clinical interview setting, under one of two conditions: using either the Highlight & Animate Feature or the Manipulable Graphics. Participants in both conditions made statistically significant gains on a multiple choice measure of knowledge of the topic of the text. While there were no significant differences by condition in the amount of knowledge gained; there were significant differences in the quality of knowledge expressed. Transcripts revealed that understandings about light and vision, expressed by those who used the Highlight & Animate Feature, were more often conceptually and linguistically 'complete.' That is, their understandings included both a description of phenomena as well as an explanation of underlying scientific principles, which participants articulated using the vocabulary of the text. This finding may be attributed to the multiple opportunities to integrate graphics (depicting the behavior of phenomena) and prose (providing the scientific explanation of that phenomena), which characterized the Highlight & Animate Condition. Those who used the

  13. The N250 brain potential to personally familiar and newly learned faces and objects

    Directory of Open Access Journals (Sweden)

    Lara Justine Pierce

    2011-10-01

    Full Text Available Studies employing event-related potentials (ERPs have shown that when participants are monitoring for a novel target face, the presentation of their own face elicits an enhanced negative brain potential in posterior channels approximately 250 ms after stimulus onset. Here, we investigate whether the own-face N250 effect generalizes to other highly familiar objects, specifically, images of the participant’s own dog and own car. In our experiments, participants were asked to monitor for a pre-experimentally unfamiliar target face (Joe, a target dog (Experiment 1: Joe’s Dog or a target car (Experiment 2: Joe’s Car. The target face and object stimuli were presented with non-target foils that included novel face and object stimuli, the participant’s own face, their own dog (Experiment 1 and their own car (Experiment 2. The consistent findings across the two experiments were the following: 1 the N250 potential differentiated the target faces and objects from the non-target face and object foils and 2 despite being non-targets, the own face and own objects produced an N250 response that was equal in magnitude to the target faces and objects by the end of the experiment. Thus, as indicated by its response to personally familiar and recently familiarized faces and objects, the N250 component is a sensitive index of individuated representations in visual memory.

  14. The Implementation of Medical Informatics in the National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM).

    Science.gov (United States)

    Behrends, Marianne; Steffens, Sandra; Marschollek, Michael

    2017-01-01

    The National Competence Based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM) describes medical skills and attitudes without being ordered by subjects or organs. Thus, the NKLM enables systematic curriculum mapping and supports curricular transparency. In this paper we describe where learning objectives related to Medical Informatics (MI) in Hannover coincide with other subjects and where they are taught exclusively in MI. An instance of the web-based MERLIN-database was used for the mapping process. In total 52 learning objectives overlapping with 38 other subjects could be allocated to MI. No overlap exists for six learning objectives describing explicitly topics of information technology or data management for scientific research. Most of the overlap was found for learning objectives relating to documentation and aspects of data privacy. The identification of numerous shared learning objectives with other subjects does not mean that other subjects teach the same content as MI. Identifying common learning objectives rather opens up the possibility for teaching cooperations which could lead to an important exchange and hopefully an improvement in medical education. Mapping of a whole medical curriculum offers the opportunity to identify common ground between MI and other medical subjects. Furthermore, in regard to MI, the interaction with other medical subjects can strengthen its role in medical education.

  15. Abstraction ability as an indicator of success for learning object-oriented programming?

    DEFF Research Database (Denmark)

    Bennedsen, Jens Benned; Caspersen, Michael Edelgaard

    2006-01-01

    ability is operationalized as stages of cognitive development (for which validated tests exist). Programming ability is operationalized as grade in the final assessment of a model-based objects-first CS1. The validity of the operationalizations is discussed. Surprisingly, our study shows......Computer science educators generally agree that abstract thinking is a crucial component for learning computer science in general and programming in particular. We report on a study to confirm the hypothesis that general abstraction ability has a positive impact on programming ability. Abstraction...... that there is no correlation between stage of cognitive development (abstraction ability) and final grade in CS1 (programming ability). Possible explanations are identified....

  16. From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

    Science.gov (United States)

    Grossberg, Stephen

    2015-09-24

    This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory

  17. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

    Science.gov (United States)

    Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

    2017-08-24

    The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

  18. Discriminative kernel feature extraction and learning for object recognition and detection

    DEFF Research Database (Denmark)

    Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

    2015-01-01

    Feature extraction and learning is critical for object recognition and detection. By embedding context cue of image attributes into the kernel descriptors, we propose a set of novel kernel descriptors called context kernel descriptors (CKD). The motivation of CKD is to use the spatial consistency...... even in high-dimensional space. In addition, the latent connection between Rényi quadratic entropy and the mapping data in kernel feature space further facilitates us to capture the geometric structure as well as the information about the underlying labels of the CKD using CSQMI. Thus the resulting...... codebook and reduced CKD are discriminative. We report superior performance of our algorithm for object recognition on benchmark datasets like Caltech-101 and CIFAR-10, as well as for detection on a challenging chicken feet dataset....

  19. A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

    Science.gov (United States)

    Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

    2017-01-01

    The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. PMID:28837096

  20. An Automatic Indicator of the Reusability of Learning Objects Based on Metadata That Satisfies Completeness Criteria

    Science.gov (United States)

    Sanz-Rodríguez, Javier; Margaritopoulos, Merkourios; Margaritopoulos, Thomas; Dodero, Juan Manuel; Sánchez-Alonso, Salvador; Manitsaris, Athanasios

    The search for learning objects in open repositories is currently a tedious task, owing to the vast amount of resources available and the fact that most of them do not have associated ratings to help users make a choice. In order to tackle this problem, we propose a reusability indicator, which can be calculated automatically using the metadata that describes the objects, allowing us to select those materials most likely to be reused. In order for this reusability indicator to be applied, metadata records must reach a certain amount of completeness, guaranteeing that the material is adequately described. This reusability indicator is tested in two studies on the Merlot and eLera repositories, and results obtained offer evidence to support their effectiveness.

  1. Extraction of Pluvial Flood Relevant Volunteered Geographic Information (VGI by Deep Learning from User Generated Texts and Photos

    Directory of Open Access Journals (Sweden)

    Yu Feng

    2018-01-01

    Full Text Available In recent years, pluvial floods caused by extreme rainfall events have occurred frequently. Especially in urban areas, they lead to serious damages and endanger the citizens’ safety. Therefore, real-time information about such events is desirable. With the increasing popularity of social media platforms, such as Twitter or Instagram, information provided by voluntary users becomes a valuable source for emergency response. Many applications have been built for disaster detection and flood mapping using crowdsourcing. Most of the applications so far have merely used keyword filtering or classical language processing methods to identify disaster relevant documents based on user generated texts. As the reliability of social media information is often under criticism, the precision of information retrieval plays a significant role for further analyses. Thus, in this paper, high quality eyewitnesses of rainfall and flooding events are retrieved from social media by applying deep learning approaches on user generated texts and photos. Subsequently, events are detected through spatiotemporal clustering and visualized together with these high quality eyewitnesses in a web map application. Analyses and case studies are conducted during flooding events in Paris, London and Berlin.

  2. Students' Learning Experiences from Didactic Teaching Sessions Including Patient Case Examples as Either Text or Video: A Qualitative Study.

    Science.gov (United States)

    Pedersen, Kamilla; Moeller, Martin Holdgaard; Paltved, Charlotte; Mors, Ole; Ringsted, Charlotte; Morcke, Anne Mette

    2017-10-06

    The aim of this study was to explore medical students' learning experiences from the didactic teaching formats using either text-based patient cases or video-based patient cases with similar content. The authors explored how the two different patient case formats influenced students' perceptions of psychiatric patients and students' reflections on meeting and communicating with psychiatric patients. The authors conducted group interviews with 30 medical students who volunteered to participate in interviews and applied inductive thematic content analysis to the transcribed interviews. Students taught with text-based patient cases emphasized excitement and drama towards the personal clinical narratives presented by the teachers during the course, but never referred to the patient cases. Authority and boundary setting were regarded as important in managing patients. Students taught with video-based patient cases, in contrast, often referred to the patient cases when highlighting new insights, including the importance of patient perspectives when communicating with patients. The format of patient cases included in teaching may have a substantial impact on students' patient-centeredness. Video-based patient cases are probably more effective than text-based patient cases in fostering patient-centered perspectives in medical students. Teachers sharing stories from their own clinical experiences stimulates both engagement and excitement, but may also provoke unintended stigma and influence an authoritative approach in medical students towards managing patients in clinical psychiatry.

  3. Transforming clinical imaging and 3D data for virtual reality learning objects: HTML5 and mobile devices implementation.

    Science.gov (United States)

    Trelease, Robert B; Nieder, Gary L

    2013-01-01

    Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android tablets. This article describes complementary methods for creating comparable, multiplatform VR learning objects in the new HTML5 standard format, circumventing platform-specific limitations imposed by the QuickTime VR multimedia file format. Multiple types or "dimensions" of anatomical information can be embedded in such learning objects, supporting different kinds of online learning applications, including interactive atlases, examination questions, and complex, multi-structure presentations. Such HTML5 VR learning objects are usable on new mobile devices that do not support QuickTime VR, as well as on personal computers. Furthermore, HTML5 VR learning objects can be embedded in "ebook" document files, supporting the development of new types of electronic textbooks on mobile devices that are increasingly popular and self-adopted for mobile learning. © 2012 American Association of Anatomists.

  4. Statistical learning of recurring sound patterns encodes auditory objects in songbird forebrain.

    Science.gov (United States)

    Lu, Kai; Vicario, David S

    2014-10-07

    Auditory neurophysiology has demonstrated how basic acoustic features are mapped in the brain, but it is still not clear how multiple sound components are integrated over time and recognized as an object. We investigated the role of statistical learning in encoding the sequential features of complex sounds by recording neuronal responses bilaterally in the auditory forebrain of awake songbirds that were passively exposed to long sound streams. These streams contained sequential regularities, and were similar to streams used in human infants to demonstrate statistical learning for speech sounds. For stimulus patterns with contiguous transitions and with nonadjacent elements, single and multiunit responses reflected neuronal discrimination of the familiar patterns from novel patterns. In addition, discrimination of nonadjacent patterns was stronger in the right hemisphere than in the left, and may reflect an effect of top-down modulation that is lateralized. Responses to recurring patterns showed stimulus-specific adaptation, a sparsening of neural activity that may contribute to encoding invariants in the sound stream and that appears to increase coding efficiency for the familiar stimuli across the population of neurons recorded. As auditory information about the world must be received serially over time, recognition of complex auditory objects may depend on this type of mnemonic process to create and differentiate representations of recently heard sounds.

  5. Identification of Auditory Object-Specific Attention from Single-Trial Electroencephalogram Signals via Entropy Measures and Machine Learning

    Directory of Open Access Journals (Sweden)

    Yun Lu

    2018-05-01

    Full Text Available Existing research has revealed that auditory attention can be tracked from ongoing electroencephalography (EEG signals. The aim of this novel study was to investigate the identification of peoples’ attention to a specific auditory object from single-trial EEG signals via entropy measures and machine learning. Approximate entropy (ApEn, sample entropy (SampEn, composite multiscale entropy (CmpMSE and fuzzy entropy (FuzzyEn were used to extract the informative features of EEG signals under three kinds of auditory object-specific attention (Rest, Auditory Object1 Attention (AOA1 and Auditory Object2 Attention (AOA2. The linear discriminant analysis and support vector machine (SVM, were used to construct two auditory attention classifiers. The statistical results of entropy measures indicated that there were significant differences in the values of ApEn, SampEn, CmpMSE and FuzzyEn between Rest, AOA1 and AOA2. For the SVM-based auditory attention classifier, the auditory object-specific attention of Rest, AOA1 and AOA2 could be identified from EEG signals using ApEn, SampEn, CmpMSE and FuzzyEn as features and the identification rates were significantly different from chance level. The optimal identification was achieved by the SVM-based auditory attention classifier using CmpMSE with the scale factor τ = 10. This study demonstrated a novel solution to identify the auditory object-specific attention from single-trial EEG signals without the need to access the auditory stimulus.

  6. Using reusable learning objects (rlos) in injection skills teaching: Evaluations from multiple user types.

    Science.gov (United States)

    Williams, Julia; O'Connor, Mórna; Windle, Richard; Wharrad, Heather J

    2015-12-01

    Clinical skills are a critical component of pre-registration nurse education in the United Kingdom, yet there is widespread concern about the clinical skills displayed by newly-qualified nurses. Novel means of supporting clinical skills education are required to address this. A package of Reusable Learning Objects (RLOs) was developed to supplement pre-registration teaching on the clinical skill of administering injection medication. RLOs are electronic resources addressing a single learning objective whose interactivity facilitates learning. This article evaluates a package of five injection RLOs across three studies: (1) questionnaires administered to pre-registration nursing students at University of Nottingham (UoN) (n=46) evaluating the RLO package as a whole; (2) individual RLOs evaluated in online questionnaires by educators and students from UoN; from other national and international institutions; and healthcare professionals (n=265); (3) qualitative evaluation of the RLO package by UoN injection skills tutors (n=6). Data from all studies were assessed for (1) access to, (2) usefulness, (3) impact and (4) integration of the RLOs. Study one found that pre-registration nursing students rate the RLO package highly across all categories, particularly underscoring the value of their self-test elements. Study two found high ratings in online assessments of individual RLOs by multiple users. The global reach is particularly encouraging here. Tutors reported insufficient levels of student-RLO access, which might be explained by the timing of their student exposure. Tutors integrate RLOs into teaching and agree on their use as teaching supplements, not substitutes for face-to-face education. This evaluation encompasses the first years postpackage release. Encouraging data on evaluative categories in this early review suggest that future evaluations are warranted to track progress as the package is adopted and evaluated more widely. Copyright © 2015 Elsevier Ltd

  7. Application of Multi-Objective Human Learning Optimization Method to Solve AC/DC Multi-Objective Optimal Power Flow Problem

    Science.gov (United States)

    Cao, Jia; Yan, Zheng; He, Guangyu

    2016-06-01

    This paper introduces an efficient algorithm, multi-objective human learning optimization method (MOHLO), to solve AC/DC multi-objective optimal power flow problem (MOPF). Firstly, the model of AC/DC MOPF including wind farms is constructed, where includes three objective functions, operating cost, power loss, and pollutant emission. Combining the non-dominated sorting technique and the crowding distance index, the MOHLO method can be derived, which involves individual learning operator, social learning operator, random exploration learning operator and adaptive strategies. Both the proposed MOHLO method and non-dominated sorting genetic algorithm II (NSGAII) are tested on an improved IEEE 30-bus AC/DC hybrid system. Simulation results show that MOHLO method has excellent search efficiency and the powerful ability of searching optimal. Above all, MOHLO method can obtain more complete pareto front than that by NSGAII method. However, how to choose the optimal solution from pareto front depends mainly on the decision makers who stand from the economic point of view or from the energy saving and emission reduction point of view.

  8. Effects of image-based and text-based active learning exercises on student examination performance in a musculoskeletal anatomy course.

    Science.gov (United States)

    Gross, M Melissa; Wright, Mary C; Anderson, Olivia S

    2017-09-01

    Research on the benefits of visual learning has relied primarily on lecture-based pedagogy, but the potential benefits of combining active learning strategies with visual and verbal materials on learning anatomy has not yet been explored. In this study, the differential effects of text-based and image-based active learning exercises on examination performance were investigated in a functional anatomy course. Each class session was punctuated with an average of 12 text-based and image-based active learning exercises. Participation data from 231 students were compared with their examination performance on 262 questions associated with the in-class exercises. Students also rated the helpfulness and difficulty of the in-class exercises on a survey. Participation in the active learning exercises was positively correlated with examination performance (r = 0.63, P active learning exercises were helpful for seeing images of key ideas (94%) and clarifying key course concepts (80%), and that the image-based exercises were significantly less demanding, less hard and required less effort than text-based exercises (P active learning strategies on student learning, and suggest that integrating them may be especially beneficial for learning anatomy. Anat Sci Educ 10: 444-455. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

  9. BROA: An agent-based model to recommend relevant Learning Objects from Repository Federations adapted to learner profile

    Directory of Open Access Journals (Sweden)

    Paula A. Rodríguez

    2013-03-01

    Full Text Available Learning Objects (LOs are distinguished from traditional educational resources for their easy and quickly availability through Web-based repositories, from which they are accessed through their metadata. In addition, having a user profile allows an educational recommender system to help the learner to find the most relevant LOs based on their needs and preferences. The aim of this paper is to propose an agent-based model so-called BROA to recommend relevant LOs recovered from Repository Federations as well as LOs adapted to learner profile. The model proposed uses both role and service models of GAIA methodology, and the analysis models of the MAS-CommonKADS methodology. A prototype was built based on this model and validated to obtain some assessing results that are finally presented.

  10. Curriculum development for a national cardiotocography education program: a Delphi survey to obtain consensus on learning objectives.

    Science.gov (United States)

    Thellesen, Line; Hedegaard, Morten; Bergholt, Thomas; Colov, Nina P; Hoegh, Stinne; Sorensen, Jette L

    2015-08-01

    To define learning objectives for a national cardiotocography (CTG) education program based on expert consensus. A three-round Delphi survey. One midwife and one obstetrician from each maternity unit in Denmark were appointed based on CTG teaching experience and clinical obstetric experience. Following national and international guidelines, the research group determined six topics as important when using CTG: fetal physiology, equipment, indication, interpretation, clinical management, and communication/responsibility. In the first Delphi round, participants listed one to five learning objectives within the predefined topics. Responses were analyzed by a directed approach to content analysis. Phrasing was modified in accordance with Bloom's taxonomy. In the second and third Delphi rounds, participants rated each objective on a five-point relevance scale. Consensus was predefined as objectives with a mean rating value of ≥ 3. A prioritized list of CTG learning objectives. A total of 42 midwives and obstetricians from 21 maternity units were invited to participate, of whom 26 completed all three Delphi rounds, representing 18 maternity units. The final prioritized list included 40 objectives. The highest ranked objectives emphasized CTG interpretation and clinical management. The lowest ranked objectives emphasized fetal physiology. Mean ratings of relevance ranged from 3.15 to 5.00. National consensus on CTG learning objectives was achieved using the Delphi methodology. This was an initial step in developing a valid CTG education program. A prioritized list of objectives will clarify which topics to emphasize in a CTG education program. © 2015 Nordic Federation of Societies of Obstetrics and Gynecology.

  11. Transforming Clinical Imaging and 3D Data for Virtual Reality Learning Objects: HTML5 and Mobile Devices Implementation

    Science.gov (United States)

    Trelease, Robert B.; Nieder, Gary L.

    2013-01-01

    Web deployable anatomical simulations or "virtual reality learning objects" can easily be produced with QuickTime VR software, but their use for online and mobile learning is being limited by the declining support for web browser plug-ins for personal computers and unavailability on popular mobile devices like Apple iPad and Android…

  12. Concept Maps as Instructional Tools for Improving Learning of Phase Transitions in Object-Oriented Analysis and Design

    Science.gov (United States)

    Shin, Shin-Shing

    2016-01-01

    Students attending object-oriented analysis and design (OOAD) courses typically encounter difficulties transitioning from requirements analysis to logical design and then to physical design. Concept maps have been widely used in studies of user learning. The study reported here, based on the relationship of concept maps to learning theory and…

  13. Pre-Service and In-Service Teachers' Experiences of Learning to Program in an Object-Oriented Language

    Science.gov (United States)

    Govender, I.; Grayson, D. J.

    2008-01-01

    This paper presents the results of an investigation into the various ways in which pre-service and in-service teachers experience learning to program in an object-oriented language. Both groups of teachers were enrolled in university courses. In most cases, the pre-service teachers were learning to program for the first time, while the in-service…

  14. Associative vocabulary learning: development and testing of two paradigms for the (re-) acquisition of action- and object-related words.

    Science.gov (United States)

    Freundlieb, Nils; Ridder, Volker; Dobel, Christian; Enriquez-Geppert, Stefanie; Baumgaertner, Annette; Zwitserlood, Pienie; Gerloff, Christian; Hummel, Friedhelm C; Liuzzi, Gianpiero

    2012-01-01

    Despite a growing number of studies, the neurophysiology of adult vocabulary acquisition is still poorly understood. One reason is that paradigms that can easily be combined with neuroscientfic methods are rare. Here, we tested the efficiency of two paradigms for vocabulary (re-) acquisition, and compared the learning of novel words for actions and objects. Cortical networks involved in adult native-language word processing are widespread, with differences postulated between words for objects and actions. Words and what they stand for are supposed to be grounded in perceptual and sensorimotor brain circuits depending on their meaning. If there are specific brain representations for different word categories, we hypothesized behavioural differences in the learning of action-related and object-related words. Paradigm A, with the learning of novel words for body-related actions spread out over a number of days, revealed fast learning of these new action words, and stable retention up to 4 weeks after training. The single-session Paradigm B employed objects and actions. Performance during acquisition did not differ between action-related and object-related words (time*word category: p = 0.01), but the translation rate was clearly better for object-related (79%) than for action-related words (53%, p = 0.002). Both paradigms yielded robust associative learning of novel action-related words, as previously demonstrated for object-related words. Translation success differed for action- and object-related words, which may indicate different neural mechanisms. The paradigms tested here are well suited to investigate such differences with neuroscientific means. Given the stable retention and minimal requirements for conscious effort, these learning paradigms are promising for vocabulary re-learning in brain-lesioned people. In combination with neuroimaging, neuro-stimulation or pharmacological intervention, they may well advance the understanding of language learning

  15. Fast automated segmentation of multiple objects via spatially weighted shape learning

    Science.gov (United States)

    Chandra, Shekhar S.; Dowling, Jason A.; Greer, Peter B.; Martin, Jarad; Wratten, Chris; Pichler, Peter; Fripp, Jurgen; Crozier, Stuart

    2016-11-01

    Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice’s similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

  16. Rapid Object Detection Systems, Utilising Deep Learning and Unmanned Aerial Systems (uas) for Civil Engineering Applications

    Science.gov (United States)

    Griffiths, D.; Boehm, J.

    2018-05-01

    With deep learning approaches now out-performing traditional image processing techniques for image understanding, this paper accesses the potential of rapid generation of Convolutional Neural Networks (CNNs) for applied engineering purposes. Three CNNs are trained on 275 UAS-derived and freely available online images for object detection of 3m2 segments of railway track. These includes two models based on the Faster RCNN object detection algorithm (Resnet and Incpetion-Resnet) as well as the novel onestage Focal Loss network architecture (Retinanet). Model performance was assessed with respect to three accuracy metrics. The first two consisted of Intersection over Union (IoU) with thresholds 0.5 and 0.1. The last assesses accuracy based on the proportion of track covered by object detection proposals against total track length. In under six hours of training (and two hours of manual labelling) the models detected 91.3 %, 83.1 % and 75.6 % of track in the 500 test images acquired from the UAS survey Retinanet, Resnet and Inception-Resnet respectively. We then discuss the potential for such applications of such systems within the engineering field for a range of scenarios.

  17. A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

    Science.gov (United States)

    Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

    2011-09-01

    Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics

  18. Learners' Use of Communication Strategies in Text-Based and Video-Based Synchronous Computer-Mediated Communication Environments: Opportunities for Language Learning

    Science.gov (United States)

    Hung, Yu-Wan; Higgins, Steve

    2016-01-01

    This study investigates the different learning opportunities enabled by text-based and video-based synchronous computer-mediated communication (SCMC) from an interactionist perspective. Six Chinese-speaking learners of English and six English-speaking learners of Chinese were paired up as tandem (reciprocal) learning dyads. Each dyad participated…

  19. Construction and validation of clinical contents for development of learning objects.

    Science.gov (United States)

    Hortense, Flávia Tatiana Pedrolo; Bergerot, Cristiane Decat; Domenico, Edvane Birelo Lopes de

    2018-01-01

    to describe the process of construction and validation of clinical contents for health learning objects, aimed at patients in the treatment of head and neck cancer. descriptive, methodological study. The development of the script and the storyboard were based on scientific evidence and submitted to the appreciation of specialists for validation of content. The agreement index was checked quantitatively and the suggestions were qualitatively evaluated. The items described in the roadmap were approved by 99% of expert experts. The suggestions for adjustments were inserted in their entirety in the final version. The free-marginal kappa statistical test, for multiple evaluators, presented value equal to 0.68%, granting a substantial agreement. The steps taken in the construction and validation of the content for the production of educational material for patients with head and neck cancer were adequate, relevant and suitable for use in other subjects.

  20. E-learning objects and actor-networks as configuring information literacy teaching

    DEFF Research Database (Denmark)

    Schreiber, Trine Louise

    2017-01-01

    Introduction. With actor-network theory (ANT) as the theoretical lens the aim of the paper is to examine attempts to build network for shaping information literacy teaching. Method. The paper is based on a study of a project in 2014-2016 where information professionals representing ten educational...... libraries produced and implemented e-learning objects in information literacy teaching. The material was collected through interviews, observations, documents and feedback sessions. Analysis. Latour´s concept of translation and Callon´s four translation moments are used to analyze the network building...... that a network configuring information literacy teaching based on new interactive roles has not been stabilized. Conclusion. The paper concludes that the strength of ANT is first of all the mediation of an overview of different kinds of actors involved in network building. Further, the paper proposes to combine...