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.

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.

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)

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.

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…

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.

Addressing uncertainty in atomistic machine learning

DEFF Research Database (Denmark)

Peterson, Andrew A.; Christensen, Rune; Khorshidi, Alireza

2017-01-01

Machine-learning regression has been demonstrated to precisely emulate the potential energy and forces that are output from more expensive electronic-structure calculations. However, to predict new regions of the potential energy surface, an assessment must be made of the credibility of the predi......Machine-learning regression has been demonstrated to precisely emulate the potential energy and forces that are output from more expensive electronic-structure calculations. However, to predict new regions of the potential energy surface, an assessment must be made of the credibility...... of the predictions. In this perspective, we address the types of errors that might arise in atomistic machine learning, the unique aspects of atomistic simulations that make machine-learning challenging, and highlight how uncertainty analysis can be used to assess the validity of machine-learning predictions. We...... suggest this will allow researchers to more fully use machine learning for the routine acceleration of large, high-accuracy, or extended-time simulations. In our demonstrations, we use a bootstrap ensemble of neural network-based calculators, and show that the width of the ensemble can provide an estimate...

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…

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.

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,

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…

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.

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.

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…

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).

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…

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.

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.

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.

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.

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...

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.

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.

A Cultured Learning Environment: Implementing a Problem- and Service-Based Microbiology Capstone Course to Assess Process- and Skill-Based Learning Objectives

Science.gov (United States)

Watson, Rachel M.; Willford, John D.; Pfeifer, Mariel A.

2018-01-01

In this study, a problem-based capstone course was designed to assess the University of Wyoming Microbiology Program's skill-based and process-based student learning objectives. Students partnered with a local farm, a community garden, and a free downtown clinic in order to conceptualize, propose, perform, and present studies addressing problems…

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...

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...

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)

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…

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…

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.

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

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,…

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 ...

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...

Improving learning of anatomy with reusable learning objects

Directory of Open Access Journals (Sweden)

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.

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.

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…

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.

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...

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.

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…

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…

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 ...

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…

Learn Objective-C for Java Developers

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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!

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.

2017 Hans O. Mauksch Address: Using the Science of Learning to Improve Student Learning in Sociology Classes

Science.gov (United States)

Messineo, Melinda

2018-01-01

The 2017 Mauksch Address invites readers to consider how the field of sociology might benefit from greater inclusion of the science of learning into its pedagogy. Results from a survey of 92 teaching and learning experts in sociology reveal the degree to which the discipline's understanding of teaching and learning is informed by the science of…

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

Directory of Open Access Journals (Sweden)

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.

Towards addressing transient learning challenges in undergraduate physics: an example from electrostatics

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Fredlund, T.; Linder, C.; Airey, J.

2015-09-01

In this article we characterize transient learning challenges as learning challenges that arise out of teaching situations rather than conflicts with prior knowledge. We propose that these learning challenges can be identified by paying careful attention to the representations that students produce. Once a transient learning challenge has been identified, teachers can create interventions to address it. By illustration, we argue that an appropriate way to design such interventions is to create variation around the disciplinary-relevant aspects associated with the transient learning challenge.

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

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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.

Predictable Locations Aid Early Object Name Learning

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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…

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

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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.

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...

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.

Speckle-learning-based object recognition through scattering media.

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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.

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.

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

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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…

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

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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.

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

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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.

Learning based particle filtering object tracking for visible-light systems.

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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.

Real-world visual statistics and infants' first-learned object names.

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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).

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.

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

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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.

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

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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.

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

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

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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.

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...

Learning Ontology from Object-Relational Database

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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.

Form over Substance: Learning Objectives in the Business Core

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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…

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

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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.

Using reusable learning objects (rlos) in injection skills teaching: Evaluations from multiple user types.

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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

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.

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

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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,…

Strategies to Address Common Challenges When Teaching in an Active Learning Classroom

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Petersen, Christina I.; Gorman, Kristen S.

2014-01-01

This chapter provides practical strategies for addressing common challenges that arise for teachers in active learning classrooms. Our strategies come from instructors with experience teaching in these environments.

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…

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

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.

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.

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

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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.

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.)

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.

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

Do textbooks address known learning challenges in area measurement? A comparative analysis

Science.gov (United States)

Hong, Dae S.; Choi, Kyong Mi; Runnalls, Cristina; Hwang, Jihyun

2018-02-01

This study compared area lessons from Korean textbooks and US standard-based textbooks to understand differences and similarities among these textbooks, as well as how these textbooks address known learning challenges in area measurement. Several well-known challenges have been identified in previous studies, such as covering, array structure, and linking array structure to area formula. We were interested in knowing if textbooks addressed these issues in their treatments of area measurement and, in doing so, provided students with opportunities to overcome or become familiar with known challenges. The results show that both countries' textbooks demonstrated similar limitations; only few area and area-related lessons are covered and three important learning challenges in area measurement are not covered well, which need to be informed to practicing teachers.

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.

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...

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.

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.

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.

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....

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…

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.

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

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,…

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

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.

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…

[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.

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...

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

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…

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.

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…

Language Learning Careers as an Object of Narrative Research in TESOL

Science.gov (United States)

Benson, Phil

2011-01-01

One of the strengths of narrative research in TESOL is its potential to provide insight into long-term language learning experiences that cannot be investigated in real time. Reliance on retrospection, however, brings two problems that are addressed in this article through the concept of "language learning careers". The first problem is…

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.…

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.

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

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.

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

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…

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…

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…

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.

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.

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.

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,…

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.

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

Lessons Learned From a Community–Academic Partnership Addressing Adolescent Pregnancy Prevention in Filipino American Families

Science.gov (United States)

Javier, Joyce R.; Chamberlain, Lisa J.; Rivera, Kahealani K.; Gonzalez, Sarah E.; Mendoza, Fernando S.; Huffman, Lynne C.

2014-01-01

Background Filipino Americans have more adolescent pregnancies than other Asian-Pacific Islanders (APIs). Few community–academic collaborations have addressed adolescent pregnancy prevention in this community. Objectives We sought to describe the lessons learned from and impact of a community-based teen pregnancy prevention program for Filipino Americans implemented by a Filipina pediatrics resident. Methods We formed a community–academic partnership between the Filipino Youth Coalition, a community-based organization (CBO) in San Jose, California, and the Stanford School of Medicine’s Pediatric Advocacy Program. We developed a culturally tailored parent–teen conference addressing adolescent pregnancy prevention in Filipino Americans. We qualitatively and quantitatively evaluated this intervention by collecting both pre- and post-conference data using a convenience sample design. Lessons Learned Engaging particular aspects of Filipino culture (i.e., religion and intergenerational differences) helped to make this community–academic partnership successful. For physicians-in-training who are conducting community-based participatory research (CBPR), project challenges may include difficulties in building and maintaining academic–community relationships, struggles to promote sustainability, and conflicting goals of “community insiders” and “academic outsiders.” Authors offer insights and implications for residents interested in practicing CBPR. Conclusion CBPR is a key tool for exploring health issues in understudied populations. CBPR experiences can provide meaningful educational opportunities for physicians-in-training and can build sustained capacity in CBOs. They can also help residents to develop analytic skills, directly affect the health of the communities they serve, and, for minority physicians, give back to the communities they call home. PMID:21169708

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

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.

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

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

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.

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.

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.

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.

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

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...

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

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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.

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...

ROBOT LEARNING OF OBJECT MANIPULATION TASK ACTIONS FROM HUMAN DEMONSTRATIONS

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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.

Cloud Computing and Multi Agent System to improve Learning Object Paradigm

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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.

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…

Evaluation of a Learning Object Based Learning Environment in Different Dimensions

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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, �

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,…

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.

Addressing Ebola-related Stigma: Lessons Learned from HIV/AIDS

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Mariam Davtyan

2014-11-01

Full Text Available Background: HIV/AIDS and Ebola Virus Disease (EVD are contemporary epidemics associated with significant social stigma in which communities affected suffer from social rejection, violence, and diminished quality of life. Objective: To compare and contrast stigma related to HIV/AIDS and EVD, and strategically think how lessons learned from HIV stigma can be applied to the current EVD epidemic. Methods: To identify relevant articles about HIV/AIDS and EVD-related stigma, we conducted an extensive literature review using multiple search engines. PubMed was used to search for relevant peer-reviewed journal articles and Google for online sources. We also consulted the websites of the World Health Organization (WHO, Centers for Disease Control and Prevention (CDC, and the National Institutes of Health to retrieve up-to-date information about EVD and HIV/AIDS. Results: Many stigmatizing attitudes and behaviors directed towards those with EVD are strikingly similar to those with HIV/AIDS but there are significant differences worthy of discussion. Both diseases are life-threatening and there is no medical cure. Additionally misinformation about affected groups and modes of transmission runs rampant. Unlike in persons with EVD, historically criminalized and marginalized populations carry a disproportionately higher risk for HIV infection. Moreover, mortality due to EVD occurs within a shorter time span as compared to HIV/AIDS. Conclusions: Stigma disrupts quality of life, whether it is associated with HIV infection or EVD. When addressing EVD, we must think beyond the immediate clinical therapeutic response, to possible HIV implications of serum treatment. There are emerging social concerns of stigma associated with EVD infection and double stigma associated with EVD and HIV infection. Drawing upon lessons learned from HIV, we must work to empower and mobilize prominent members of the community, those who recovered from the disease, and organizations

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.

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.

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).

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.

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.

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...

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.

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.

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.

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.

Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges.

Science.gov (United States)

Goldstein, Benjamin A; Navar, Ann Marie; Carter, Rickey E

2017-06-14

Risk prediction plays an important role in clinical cardiology research. Traditionally, most risk models have been based on regression models. While useful and robust, these statistical methods are limited to using a small number of predictors which operate in the same way on everyone, and uniformly throughout their range. The purpose of this review is to illustrate the use of machine-learning methods for development of risk prediction models. Typically presented as black box approaches, most machine-learning methods are aimed at solving particular challenges that arise in data analysis that are not well addressed by typical regression approaches. To illustrate these challenges, as well as how different methods can address them, we consider trying to predicting mortality after diagnosis of acute myocardial infarction. We use data derived from our institution's electronic health record and abstract data on 13 regularly measured laboratory markers. We walk through different challenges that arise in modelling these data and then introduce different machine-learning approaches. Finally, we discuss general issues in the application of machine-learning methods including tuning parameters, loss functions, variable importance, and missing data. Overall, this review serves as an introduction for those working on risk modelling to approach the diffuse field of machine learning. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Cardiology.

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.

A Multi-Objective Learning to re-Rank Approach to Optimize Online Marketplaces for Multiple Stakeholders

OpenAIRE

Nguyen, Phong; Dines, John; Krasnodebski, Jan

2017-01-01

Multi-objective recommender systems address the difficult task of recommending items that are relevant to multiple, possibly conflicting, criteria. However these systems are most often designed to address the objective of one single stakeholder, typically, in online commerce, the consumers whose input and purchasing decisions ultimately determine the success of the recommendation systems. In this work, we address the multi-objective, multi-stakeholder, recommendation problem involving one or ...

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…

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...

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.

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

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.

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…

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.

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.

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.

ESSA, Equity of Opportunity, and Addressing Barriers to Learning. Research for School Improvement and Transformation. Policy Brief

Science.gov (United States)

Center for Mental Health in Schools at UCLA, 2016

2016-01-01

The "Every Student Succeeds Act" (ESSA) recognizes that significant numbers of students require supports to successfully meet challenging state academic standards. This brief (1) analyzes the act to assess how it addresses the nature and scope of supports to address barriers to learning and re-engage disconnected students and (2)…

Development of Geriatric Mental Health Learning Objectives for Medical Students: A Response to the Institute of Medicine 2012 Report.

Science.gov (United States)

Lehmann, Susan W; Brooks, William B; Popeo, Dennis; Wilkins, Kirsten M; Blazek, Mary C

2017-10-01

America is aging as the population of older adults increases. The shortage of geriatric mental health specialists means that most geriatric mental healthcare will be provided by physicians who do not have specialty training in geriatrics. The Institute of Medicine Report of 2012 highlighted the urgent need for development of national competencies and curricula in geriatric mental health for all clinicians. Virtually all physicians can expect to treat older patients with mental health symptoms, yet currently there are no widely accepted learning objectives in geriatric mental health specific for medical students. The authors describe the development of a set of such learning objectives that all medical students should achieve by graduation. The iterative process included initial drafting by content experts from five medical schools with input and feedback from a wider group of geriatric psychiatrists, geriatricians, internists, and medical educators. The final document builds upon previously published work and includes specific knowledge, attitudes and skills in six key domains: Normal Aging, Mental Health Assessment of the Geriatric Patient, Psychopharmacology, Delirium, Depression, and Dementia. These objectives address a pressing need, providing a framework for national standards and curriculum development. Copyright © 2017 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

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.

[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.

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.

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.

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…

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.

The Place of E-Learning in Africa's Institutions of Higher Learning

Science.gov (United States)

Nafukho, Fredrick Muyia

2007-01-01

The paper seeks to accomplish four objectives. The first is to examine the need for e-learning in Africa's institutions of higher learning. The second is to discuss the policy, institutional, pedagogical, copyright, and quality assurance issues that need to be addressed. The third is to critically examine the advantages and disadvantages of…

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

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.

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.

Learning Grasp Affordance Densities

DEFF Research Database (Denmark)

Detry, Renaud; Kraft, Dirk; Kroemer, Oliver

2011-01-01

and relies on kernel density estimation to provide a continuous model. Grasp densities are learned and refined from exploration, by letting a robot “play” with an object in a sequence of graspand-drop actions: The robot uses visual cues to generate a set of grasp hypotheses; it then executes......We address the issue of learning and representing object grasp affordance models. We model grasp affordances with continuous probability density functions (grasp densities) which link object-relative grasp poses to their success probability. The underlying function representation is nonparametric...... these and records their outcomes. When a satisfactory number of grasp data is available, an importance-sampling algorithm turns these into a grasp density. We evaluate our method in a largely autonomous learning experiment run on three objects of distinct shapes. The experiment shows how learning increases success...

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...

Grounded Object and Grasp Representations in a Cognitive Architecture

DEFF Research Database (Denmark)

Kraft, Dirk

developed. This work presents a system that is able to learn autonomously about objects and applicable grasps in an unknown environment through exploratory manipulation and to then use this grounded knowledge in a planning setup to address complex tasks. A set of different subsystems is needed to achieve....... The topics are ordered so that we proceed from the more general integration works towards the works describing the individual components. The first chapter gives an overview over the system that is able to learn a grounded visual object representation and a grounded grasp representation. In the following...... part, we describe how this grounding procedures can be embedded in a three cognitive level architecture. Our initial work to use a tactile sensor to enrichen the object representations as well as allow for more complex actions is presented here as well. Since our system is concerned with learning about...

Cultural dimensions of learning: Addressing the challenges of multicultural instruction

Directory of Open Access Journals (Sweden)

Patrick Parrish

2010-05-01

Full Text Available The growing multicultural nature of education and training environments makes it critical that instructors and instructional designers, especially those working in online learning environments, develop skills to deliver culturally sensitive and culturally adaptive instruction. This article explores research into cultural differences to identify those dimensions of culture that are most likely to impact instructional situations. It presents these in the cultural dimensions of learning framework (CDLF, which describes a set of eight cultural parameters regarding social relationships, epistemological beliefs, and temporal perceptions, and illustrates their spectrums of variability as they might be exhibited in instructional situations. The article also explores the literature on instructional design and culture for guidelines on addressing the cross-cultural challenges faced by instructional providers. It suggests that these challenges can be overcome through increased awareness, culturally sensitive communication, modified instructional design processes, and efforts to accommodate the most critical cultural differences. Finally, it describes the use of the CDLF questionnaire as a tool to illuminate the range of preferences existing among learners and to discover the potential range of strategies and tactics that might be useful for a given set of learners.

An innovative program to address learning barriers in small schools: Washington State School Nurse Corps.

Science.gov (United States)

Fast, Gail Ann; Gray, Lorali; Miles-Koehler, Mona

2013-01-01

While all schools in Washington State have had to deal with shrinking financial resources, small, rural school districts, with fewer than 2,000 students, face unique circumstances that further challenge their ability to meet rising student health needs. This article will explore how small districts utilize the services of the Washington State School Nurse Corps (SNC), an innovative program that supports student health and safety while reducing barriers to learning. Through direct registered nursing services and regional nurse administrative consultation and technical assistance, the SNC strengthens rural school districts' capacity to provide a safe and healthy learning environment. In addition, we will examine current research that links health and learning to discover how the SNC model is successful in addressing health risks as barriers to learning. Lastly, as resources continue to dwindle, partnerships between schools, the SNC, and state and local health and education organizations will be critical in maintaining health services and learning support to small, rural schools.

Understanding the Behavioral Intention to Play Austronesian Learning Games: From the Perspectives of Learning Outcome, Service Quality, and Hedonic Value

Science.gov (United States)

Hsiao, Kuo-Lun; Huang, Tien-Chi; Chen, Mu-Yen; Chiang, Nien-Ting

2018-01-01

Although ubiquitous learning is a novel and creative teaching approach, two key issues inhibit its success overall: a lack of appropriate learning strategies regarding learning objectives, and ineffective learning tools for receiving knowledge regarding the chosen subjects. To address these issues, we develops and designs a game-based educational…

E-Learning as a Knowledge Management Approach for Intellectual Capital Utilization

Science.gov (United States)

Shehabat, Issa; Mahdi, Saad A.; Khoualdi, Kamel

2008-01-01

This paper addresses human resources utilization at the university environment. We address the design issues of e-learning courses that can capture the teacher knowledge. The underlying objective is that e-learning is a key knowledge and major resources for many universities. Therefore, the design of e-learning should be an important part of the…

Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

Science.gov (United States)

Bae, Seung-Hwan; Yoon, Kuk-Jin

2018-03-01

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

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...

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...

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…

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…

The use of objective structured self-assessment and peer-feedback (OSSP) for learning communication skills: evaluation using a controlled trial.

Science.gov (United States)

Perera, Jennifer; Mohamadou, Galy; Kaur, Satpal

2010-05-01

Feedback is essential to guide students towards expected performance goals. The usefulness of teacher feedback on improving communication skills (CS) has been well documented. It has been proposed that self-assessment and peer-feedback has an equally important role to play in enhancing learning. This is the focus of this study. Objectively structured self-assessment and peer feedback (OSSP) was incorporated into small group CS teaching sessions of a group of semester one medical students who were learning CS for the first time, to minimise the influence of previous educational interventions. A control group matched for academic performance, gender and age was used to enable parallel evaluation of the innovation. A reflective log containing closed and open ended questions was used for OSSP. Facilitators and simulated patients provided feedback to students in both groups during CS learning as per routine practice. Student perceptions on OSSP and acceptability as a learning method were explored using a questionnaire. CS were assessed in both groups using objective structured clinical examination (OSCE) as per routine practice and assessors were blinded as to which group the student belonged. Mean total score and scores for specific areas of interview skills were significantly higher in the experimental group. Analysis of the questionnaire data showed that students gained fresh insights into specific areas such as empathy, addressing patients' concerns and interview style during OSSP which clearly corroborated the specific differences in scores. The free text comments were highly encouraging as to acceptability of OSSP, in spite of 67% being never exposed to formal self- and peer-assessment during pre-university studies. OSSP promotes effective CS learning and learner acceptability is high.

Addressing Barriers to Learning and Teaching to Enhance Equity of Opportunity. Report from the National Summit on ESSA and Learning Supports

Science.gov (United States)

Center for Mental Health in Schools at UCLA, 2017

2017-01-01

Passage of the "Every Student Succeeds Act" (ESSA) provides opportunities to improve how schools address barriers to learning and teaching and re-engage disconnected students and families. Of particular relevance to these concerns, ESSA replaces what has been described as a maze of programs with a "Student Support and Academic…

CEDS Addresses: Virtual and Blended Learning

Science.gov (United States)

US Department of Education, 2015

2015-01-01

The Common Education Data Standards (CEDS) common data vocabulary supports the collection and use of information about virtual and blended learning. The data element "Virtual Indicator", introduced in version 3 of CEDS, supports a range of virtual learning-related use cases. The Virtual Indicator element may be related to a Course…

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…

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...

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.

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.

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…

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.

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…

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)

Integrating Interprofessional Education and Cultural Competency Training to Address Health Disparities.

Science.gov (United States)

McElfish, Pearl Anna; Moore, Ramey; Buron, Bill; Hudson, Jonell; Long, Christopher R; Purvis, Rachel S; Schulz, Thomas K; Rowland, Brett; Warmack, T Scott

2018-01-01

Many U.S. medical schools have accreditation requirements for interprofessional education and training in cultural competency, yet few programs have developed programs to meet both of these requirements simultaneously. Furthermore, most training programs to address these requirements are broad in nature and do not focus on addressing health disparities. The lack of integration may reduce the students' ability to apply the knowledge learned. Innovative programs that combine these two learning objectives and focus on disenfranchised communities are needed to train the next generation of health professionals. A unique interprofessional education program was developed at the University of Arkansas for Medical Sciences Northwest. The program includes experiential learning, cultural exposure, and competence-building activities for interprofessional teams of medicine, nursing, and pharmacy students. The activities include (a) educational seminars, (b) clinical experiential learning in a student-led clinic, and (c) community-based service-learning through health assessments and survey research events. The program focuses on interprofessional collaboration to address the health disparities experienced by the Marshallese community in northwest Arkansas. The Marshallese are Pacific Islanders who suffer from significant health disparities related to chronic and infectious diseases. Comparison tests revealed statistically significant changes in participants' retrospectively reported pre/posttest scores for Subscales 1 and 2 of the Readiness for Interpersonal Learning Scale and for the Caffrey Cultural Competence in Healthcare Scale. However, no significant change was found for Subscale 3 of the Readiness for Interpersonal Learning Scale. Qualitative findings demonstrated a change in students' knowledge, attitudes, and behavior toward working with other professions and the underserved population. The program had to be flexible enough to meet the educational requirements and

How does the brain rapidly learn and reorganize view-invariant and position-invariant object representations in the inferotemporal cortex?

Science.gov (United States)

Cao, Yongqiang; Grossberg, Stephen; Markowitz, Jeffrey

2011-12-01

All primates depend for their survival on being able to rapidly learn about and recognize objects. Objects may be visually detected at multiple positions, sizes, and viewpoints. How does the brain rapidly learn and recognize objects while scanning a scene with eye movements, without causing a combinatorial explosion in the number of cells that are needed? How does the brain avoid the problem of erroneously classifying parts of different objects together at the same or different positions in a visual scene? In monkeys and humans, a key area for such invariant object category learning and recognition is the inferotemporal cortex (IT). A neural model is proposed to explain how spatial and object attention coordinate the ability of IT to learn invariant category representations of objects that are seen at multiple positions, sizes, and viewpoints. The model clarifies how interactions within a hierarchy of processing stages in the visual brain accomplish this. These stages include the retina, lateral geniculate nucleus, and cortical areas V1, V2, V4, and IT in the brain's What cortical stream, as they interact with spatial attention processes within the parietal cortex of the Where cortical stream. The model builds upon the ARTSCAN model, which proposed how view-invariant object representations are generated. The positional ARTSCAN (pARTSCAN) model proposes how the following additional processes in the What cortical processing stream also enable position-invariant object representations to be learned: IT cells with persistent activity, and a combination of normalizing object category competition and a view-to-object learning law which together ensure that unambiguous views have a larger effect on object recognition than ambiguous views. The model explains how such invariant learning can be fooled when monkeys, or other primates, are presented with an object that is swapped with another object during eye movements to foveate the original object. The swapping procedure is

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.

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.

Communication in Health Professions: A European consensus on inter- and multi-professional learning objectives in German.

Science.gov (United States)

Bachmann, Cadja; Kiessling, Claudia; Härtl, Anja; Haak, Rainer

2016-01-01

Communication is object of increasing attention in the health professions. Teaching communication competencies should already begin in undergraduate education or pre-registration training. The aim of this project was to translate the Health Professions Core Communication Curriculum (HPCCC), an English catalogue of learning objectives, into German to make its content widely accessible in the German-speaking countries. This catalogue lists 61 educational objectives and was agreed on by 121 international communication experts. A European reference framework for inter- and multi-professional curriculum development for communication in the health professions in German-speaking countries should be provided. The German version of the HPCCC was drafted by six academics and went through multiple revisions until consensus was reached. The learning objectives were paired with appropriate teaching and assessment tools drawn from the database of the teaching Committee of the European Association for Communication Health Care (tEACH). The HPCCC learning objectives are now available in German and can be applied for curriculum planning and development in the different German-speaking health professions, the educational objectives can also be used for inter-professional purposes. Examples for teaching methods and assessment tools are given for using and implementing the objectives. The German version of the HPCCC with learning objectives for communication in health professions can contribute significantly to inter- and multi-professional curriculum development in the health care professions in the German-speaking countries. Examples for teaching methods and assessment tools from the materials compiled by tEACH supplement the curricular content and provide suggestions for practical implementation of the learning objectives in teaching and assessment. The relevance of the German HPCCC to the processes of curriculum development for the various health professions and inter

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,…

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…

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

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

The Spiral-in Method for Designing and Connecting Learning Objects

DEFF Research Database (Denmark)

Vlachos, Evgenios

2012-01-01

. The Spiral-in Method (SiM) encloses pedagogical and didactic potentials, addresses issues on both the educator and the group learners and implements personalized mechanisms. This methodology structures the design process into four distinct phases, fragmentation, coordination, combination and grouping...... given, LOs are created and connected in a linear structure, like a spiral. The LOs are grouped together into lessons attempting to satisfy short-term learning outcomes. The spiral has to be fully wrapped for the possession of the subject matter....

Objective-guided image annotation.

Science.gov (United States)

Mao, Qi; Tsang, Ivor Wai-Hung; Gao, Shenghua

2013-04-01

Automatic image annotation, which is usually formulated as a multi-label classification problem, is one of the major tools used to enhance the semantic understanding of web images. Many multimedia applications (e.g., tag-based image retrieval) can greatly benefit from image annotation. However, the insufficient performance of image annotation methods prevents these applications from being practical. On the other hand, specific measures are usually designed to evaluate how well one annotation method performs for a specific objective or application, but most image annotation methods do not consider optimization of these measures, so that they are inevitably trapped into suboptimal performance of these objective-specific measures. To address this issue, we first summarize a variety of objective-guided performance measures under a unified representation. Our analysis reveals that macro-averaging measures are very sensitive to infrequent keywords, and hamming measure is easily affected by skewed distributions. We then propose a unified multi-label learning framework, which directly optimizes a variety of objective-specific measures of multi-label learning tasks. Specifically, we first present a multilayer hierarchical structure of learning hypotheses for multi-label problems based on which a variety of loss functions with respect to objective-guided measures are defined. And then, we formulate these loss functions as relaxed surrogate functions and optimize them by structural SVMs. According to the analysis of various measures and the high time complexity of optimizing micro-averaging measures, in this paper, we focus on example-based measures that are tailor-made for image annotation tasks but are seldom explored in the literature. Experiments show consistency with the formal analysis on two widely used multi-label datasets, and demonstrate the superior performance of our proposed method over state-of-the-art baseline methods in terms of example-based measures on four

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…

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.

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.

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)…

#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…

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

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.

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…

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

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....

Addressing data heterogeneity: Lessons learned from a multimedia risk assessment

International Nuclear Information System (INIS)

Oezkaynak, H.; Xue, Jianping; Butler, D.A.; Haroun, L.A.; MacDonell, M.M.; Fingleton, D.J.

1991-01-01

Cleanup activities are currently being conducted by the US Department of Energy (DOE) at a former chemical plant site that has been inactive for more than 20 years. The Army produced nitroaromatic explosives at the 220-acre site during the 1940s, and radioactive materials of the uranium and thorium series were processed there by DOE's predecessor agency during the 1950s and 1960s. Chemical and radioactive contaminants are present in soil, surface water, sediment, and groundwater at the site as a result of both past releases and disposal activities and subsequent contaminant migration. Samples have been collected from these media over a number of years under both DOE's environmental monitoring program and the site characterization program of the Superfund process. Results of samples analyses have been compiled in a computerized data base. These data are being evaluated in the context of potential exposure pathways that are currently present at the site or that may be present in the future, in order to estimate possible adverse impacts to human health and the environment in the absence of cleanup. This paper discusses the methodology used to address associated tasks and the lessons learned during the assessment process. Statistical issues and recommended future directions for dealing with technical aspects of this project and with similar multimedia risk assessment projects are addressed in the final discussion. 10 refs., 9 figs., 1 tab

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.

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.

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

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

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

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…

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…

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.

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.

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

The study of topics of Astronomy in Physics teaching that addresses the significant learning

Science.gov (United States)

Santos Neta, M. L.; Voelzke, M. R.

2017-12-01

In this work are discussed the results of the case study on the oceanic tides for which it was used didactic sequences, based on the Cycle of Experience of George Kelly (Kelly 1963), applied in four groups of the first year of the integral medium teaching. The data obtained in two same tests - Pre and Post-Test - before and after the application of the didactic sequences, as well as the verification of the significant learning analysed as for the conditions of the previous knowledge considering authors Boczko (1984), Horvath (2008) and Kepler & Saraiva (2013). Also the values were analysed obtained the Post-Test II applied to the long period. The results reveal that the worked groups presented previous knowledge in conditions adapted for the understanding of the event, as well as, for they be used in the situation-problem resolution that demands the understanding. Verify also that the idea of the didactic sequence can be used as tool in the relationship teaching-learning addressed to the significant learning.

Addressing Information Literacy through Student-Centered Learning

Science.gov (United States)

Bond, Paul

2016-01-01

This case study describes several courses that resulted from a teaching partnership between an instructional technologist/professor and a librarian that evolved over several semesters, and the information literacy implications of the course formats. In order to increase student engagement, active learning and inquiry-based learning techniques were…

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

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

Generative Street Addresses from Satellite Imagery

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İlke Demir

2018-03-01

Full Text Available We describe our automatic generative algorithm to create street addresses from satellite images by learning and labeling roads, regions, and address cells. Currently, 75% of the world’s roads lack adequate street addressing systems. Recent geocoding initiatives tend to convert pure latitude and longitude information into a memorable form for unknown areas. However, settlements are identified by streets, and such addressing schemes are not coherent with the road topology. Instead, we propose a generative address design that maps the globe in accordance with streets. Our algorithm starts with extracting roads from satellite imagery by utilizing deep learning. Then, it uniquely labels the regions, roads, and structures using some graph- and proximity-based algorithms. We also extend our addressing scheme to (i cover inaccessible areas following similar design principles; (ii be inclusive and flexible for changes on the ground; and (iii lead as a pioneer for a unified street-based global geodatabase. We present our results on an example of a developed city and multiple undeveloped cities. We also compare productivity on the basis of current ad hoc and new complete addresses. We conclude by contrasting our generative addresses to current industrial and open solutions.

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

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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.

Assessing Program Learning Objectives to Improve Undergraduate Physics Education

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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.

Discovery and Use of Online Learning Resources: Case Study Findings

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Recker, Mimi M.; Dorward, James; Nelson, Laurie Miller

2004-01-01

Much recent research and funding have focused on building Internet-based repositories that contain collections of high-quality learning resources, often called "learning objects." Yet little is known about how non-specialist users, in particular teachers, find, access, and use digital learning resources. To address this gap, this article…

Using MPAs to address regional-scale ecological objectives in the North Sea: modelling the effects of fishing effort displacement

NARCIS (Netherlands)

Greenstreet, S.P.R.; Fraser, H.M.; Piet, G.J.

2009-01-01

The use of Marine Protected Areas (MPAs) to address regional-scale objectives as part of an ecosystem approach to management in the North Sea is examined. Ensuring that displacement of fishing activity does not negate the ecological benefits gained from MPAs is a major concern. Two scenarios are

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...

Credit assignment between body and object probed by an object transportation task.

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Kong, Gaiqing; Zhou, Zhihao; Wang, Qining; Kording, Konrad; Wei, Kunlin

2017-10-17

It has been proposed that learning from movement errors involves a credit assignment problem: did I misestimate properties of the object or those of my body? For example, an overestimate of arm strength and an underestimate of the weight of a coffee cup can both lead to coffee spills. Though previous studies have found signs of simultaneous learning of the object and of the body during object manipulation, there is little behavioral evidence about their quantitative relation. Here we employed a novel weight-transportation task, in which participants lift the first cup filled with liquid while assessing their learning from errors. Specifically, we examined their transfer of learning when switching to a contralateral hand, the second identical cup, or switching both hands and cups. By comparing these transfer behaviors, we found that 25% of the learning was attributed to the object (simply because of the use of the same cup) and 58% of the learning was attributed to the body (simply because of the use of the same hand). The nervous system thus seems to partition the learning of object manipulation between the object and the body.

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

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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.

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

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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.

Object-Location-Aware Hashing for Multi-Label Image Retrieval via Automatic Mask Learning.

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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.

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

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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…

Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

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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

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

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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.

Service-Learning and Philanthropy: Implications for Course Design

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Hatcher, Julie A.; Studer, Morgan L.

2015-01-01

Developing good citizens is an historic role for higher education (Sullivan & Rosin, 2008) and the emergence of service-learning as a pedagogical strategy has heightened attention to the intentional educational objectives to be addressed in higher education. This article examines the role of service-learning in developing philanthropic values…

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…

Multi-Objective Reinforcement Learning-Based Deep Neural Networks for Cognitive Space Communications

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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.

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.

Developing a Code of Practice for Learning Analytics

Science.gov (United States)

Sclater, Niall

2016-01-01

Ethical and legal objections to learning analytics are barriers to development of the field, thus potentially denying students the benefits of predictive analytics and adaptive learning. Jisc, a charitable organization that champions the use of digital technologies in UK education and research, has attempted to address this with the development of…

An Analysis of Learning Objectives and Content Coverage in Introductory Psychology Syllabi

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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…

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.

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

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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

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

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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.

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…

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

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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…

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

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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.

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

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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.

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

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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

Robust Individual-Cell/Object Tracking via PCANet Deep Network in Biomedicine and Computer Vision

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Bineng Zhong

2016-01-01

Full Text Available Tracking individual-cell/object over time is important in understanding drug treatment effects on cancer cells and video surveillance. A fundamental problem of individual-cell/object tracking is to simultaneously address the cell/object appearance variations caused by intrinsic and extrinsic factors. In this paper, inspired by the architecture of deep learning, we propose a robust feature learning method for constructing discriminative appearance models without large-scale pretraining. Specifically, in the initial frames, an unsupervised method is firstly used to learn the abstract feature of a target by exploiting both classic principal component analysis (PCA algorithms with recent deep learning representation architectures. We use learned PCA eigenvectors as filters and develop a novel algorithm to represent a target by composing of a PCA-based filter bank layer, a nonlinear layer, and a patch-based pooling layer, respectively. Then, based on the feature representation, a neural network with one hidden layer is trained in a supervised mode to construct a discriminative appearance model. Finally, to alleviate the tracker drifting problem, a sample update scheme is carefully designed to keep track of the most representative and diverse samples during tracking. We test the proposed tracking method on two standard individual cell/object tracking benchmarks to show our tracker's state-of-the-art performance.

Teaching & Learning Across Collaborative Digital contexts

DEFF Research Database (Denmark)

Sorensen, Elsebeth Korsgaard

This paper addresses the challenge of teaching and learning in a blended, collaborative Digital Context. It reports on a case study in which the promotion of learners empowerment and meta-learning are key objectives. The findings of the case study suggest the presence of a promising potential...... in a marriage between theory-led designs, digital technology, and dialogic collaborative knowledge building for cultivating and enhancing student empowerment....

The use of interprofessional learning and simulation in undergraduate nursing programs to address interprofessional communication and collaboration: An integrative review of the literature.

Science.gov (United States)

Granheim, Benedikte M; Shaw, Julie M; Mansah, Martha

2018-03-01

To identify how simulation and interprofessional learning are used together in undergraduate nursing programs and undertaken in schools of nursing to address interprofessional communication and collaboration. An integrative literature review. The databases CINAHL, ProQuest, PubMed, Scopus, PsycInfo and Science Direct were searched to identify articles from 2006 to 2016 that reported on the use of IPL and simulation together in undergraduate nursing education. Whittemore and Knafl's five step process was used to guide the integrative review of quantitative and qualitative literature. Only peer reviewed articles written in English that addressed undergraduate nursing studies, were included in the review. Articles that did not aim to improve communication and collaboration were excluded. All articles selected were examined to determine their contribution to interprofessional learning and simulation in undergraduate nursing knowledge. The faculties of nursing used interprofessional learning and simulation in undergraduate nursing programs that in some cases were connected to a specific course. A total of nine articles, eight research papers and one narrative report, that focused on collaboration and communication were selected for this review. Studies predominantly used nursing and medical student participants. None of the included studies identified prior student experience with interprofessional learning and simulation. Four key themes were identified: communication, collaboration/teamwork, learning in practice and understanding of roles, and communication. This review highlights the identified research relating to the combined teaching strategy of interprofessional learning and simulation that addressed communication and collaboration in undergraduate nursing programs. Further research into the implementation of interprofessional learning and simulation may benefit the emergent challenges. Information drawn from this review can be used in informing education and

The ambiguous and bewitching power of knowledge, skills and attitudes leads to confusing statements of learning objectives.

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Guilbert, J-J

2002-01-01

The words "knowledge", "skills" and "attitudes" are given different meanings by health personnel when discussing educational issues. Ambiguity is known as a handicap to efficient communication. In the design of a curriculum the quality of the definition of learning objectives plays a fundamental role. If learning objectives lack clarity, learners and teachers will face operational difficulties. As Robert Mager said, "If you are not certain of where you are going you may very well end up somewhere else and not even know it". Knowledge is not only memory of facts but what you do with it. The complexity of human behaviour should not be underestimated. This is why educational objectives need active non-ambiguous verbs in order to achieve better communication between teachers and learners and to assess that complexity. This is why I suggest using the expression intellectual skill (or competence) as meaning "a rational decision or act". Sensomotor skill (or competence) would replace "skills" as presently used and cover only "acts which require a neuromuscular coordination". Interpersonal communication skill (or competence) would replace "attitude(s)" and be limited to "verbal and non-verbal relation between persons". As the level of validity of assessment of learners' competencies is linked to the clarity of learning objectives, it is hoped that the above suggestions will raise the overall level of validity of the evaluation system. This is why it is important that everybody understands, in the same manner, the meaning of a learning objective. It will help learners to focus their learning efforts on the right target. It will help teachers to ensure the relevance to health needs of their teaching and the validity of assessment instruments. In both cases it will be beneficial to the health of the population.

Addressing Ebola-related stigma: lessons learned from HIV/AIDS.

Science.gov (United States)

Davtyan, Mariam; Brown, Brandon; Folayan, Morenike Oluwatoyin

2014-01-01

HIV/AIDS and Ebola Virus Disease (EVD) are contemporary epidemics associated with significant social stigma in which communities affected suffer from social rejection, violence, and diminished quality of life. To compare and contrast stigma related to HIV/AIDS and EVD, and strategically think how lessons learned from HIV stigma can be applied to the current EVD epidemic. To identify relevant articles about HIV/AIDS and EVD-related stigma, we conducted an extensive literature review using multiple search engines. PubMed was used to search for relevant peer-reviewed journal articles and Google for online sources. We also consulted the websites of the World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), and the National Institutes of Health to retrieve up-to-date information about EVD and HIV/AIDS. Many stigmatizing attitudes and behaviors directed towards those with EVD are strikingly similar to those with HIV/AIDS but there are significant differences worthy of discussion. Both diseases are life-threatening and there is no medical cure. Additionally misinformation about affected groups and modes of transmission runs rampant. Unlike in persons with EVD, historically criminalized and marginalized populations carry a disproportionately higher risk for HIV infection. Moreover, mortality due to EVD occurs within a shorter time span as compared to HIV/AIDS. Stigma disrupts quality of life, whether it is associated with HIV infection or EVD. When addressing EVD, we must think beyond the immediate clinical therapeutic response, to possible HIV implications of serum treatment. There are emerging social concerns of stigma associated with EVD infection and double stigma associated with EVD and HIV infection. Drawing upon lessons learned from HIV, we must work to empower and mobilize prominent members of the community, those who recovered from the disease, and organizations working at the grassroots level to disseminate clear and accurate

Blended e-learning Design: Discussion of Cultural Issues

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Ahmed A Al-Hunaiyyan

2008-06-01

Full Text Available Blended e-learning is becoming an educational issue especially with the new development of e-learning technology and globalization. Educators as the question: can we design these systems to accommodate different cultural groups and various learning strategies. This paper addresses some design issues when selecting a blended e-learning approach; it discusses some cultural elements that affect the design of blended e-learning. The paper also explores issues related to learning design, then emphasizes on the importance of cultural learning objects (CLO and its role in the design of multimedia-based e-learning systems.

Development and Implementation Costs of Student Learning Objectives: Considerations for TIF Grantees

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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…

Addressing Hunger Issues Through Service Learning

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Nancy Kershaw

2007-09-01

Full Text Available The U.S. Government has set a goal of reducing the prevalence of food insecurity to 6% or less by 2010. To achieve this goal, education and action are necessary. Youth in Oregon were introduced to the issue through the role playing simulation, Are You Hungry Tonight? The simulation was utilized with youth, adult volunteers, and youth development staff. Participants indicated increased understanding of people with limited resources, including: Financial pressures, emotional stresses and frustrations they face; Difficulty of improving one’s situation; Difficult choices people make; Positive and negative impacts of community organizations. Simulation participants developed an understanding of hunger issues and empathy for people experiencing food insecurity. Participants were subsequently challenged to complete service learning projects that would help provide additional food resources for their communities. Providing education through the simulation set the stage for youth to participate fully in service learning projects to help alleviate hunger.

Incremental concept learning with few training examples and hierarchical classification

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Bouma, H.; Eendebak, P.T.; Schutte, K.; Azzopardi, G.; Burghouts, G.J.

2015-01-01

Object recognition and localization are important to automatically interpret video and allow better querying on its content. We propose a method for object localization that learns incrementally and addresses four key aspects. Firstly, we show that for certain applications, recognition is feasible

Science Integrating Learning Objectives: A Cooperative Learning Group Process

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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…

Joint Attention and Object Learning in 5- and 7-Month-Old Infants

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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…

Design and Use of a Learning Object for Finding Complex Polynomial Roots

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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…

Soft systems thinking and social learning for adaptive management.

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Cundill, G; Cumming, G S; Biggs, D; Fabricius, C

2012-02-01

The success of adaptive management in conservation has been questioned and the objective-based management paradigm on which it is based has been heavily criticized. Soft systems thinking and social-learning theory expose errors in the assumption that complex systems can be dispassionately managed by objective observers and highlight the fact that conservation is a social process in which objectives are contested and learning is context dependent. We used these insights to rethink adaptive management in a way that focuses on the social processes involved in management and decision making. Our approach to adaptive management is based on the following assumptions: action toward a common goal is an emergent property of complex social relationships; the introduction of new knowledge, alternative values, and new ways of understanding the world can become a stimulating force for learning, creativity, and change; learning is contextual and is fundamentally about practice; and defining the goal to be addressed is continuous and in principle never ends. We believe five key activities are crucial to defining the goal that is to be addressed in an adaptive-management context and to determining the objectives that are desirable and feasible to the participants: situate the problem in its social and ecological context; raise awareness about alternative views of a problem and encourage enquiry and deconstruction of frames of reference; undertake collaborative actions; and reflect on learning. ©2011 Society for Conservation Biology.

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

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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.

The effects of short-term and long-term learning on the responses of lateral intraparietal neurons to visually presented objects.

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Sigurdardottir, Heida M; Sheinberg, David L

2015-07-01

The lateral intraparietal area (LIP) is thought to play an important role in the guidance of where to look and pay attention. LIP can also respond selectively to differently shaped objects. We sought to understand to what extent short-term and long-term experience with visual orienting determines the responses of LIP to objects of different shapes. We taught monkeys to arbitrarily associate centrally presented objects of various shapes with orienting either toward or away from a preferred spatial location of a neuron. The training could last for less than a single day or for several months. We found that neural responses to objects are affected by such experience, but that the length of the learning period determines how this neural plasticity manifests. Short-term learning affects neural responses to objects, but these effects are only seen relatively late after visual onset; at this time, the responses to newly learned objects resemble those of familiar objects that share their meaning or arbitrary association. Long-term learning affects the earliest bottom-up responses to visual objects. These responses tend to be greater for objects that have been associated with looking toward, rather than away from, LIP neurons' preferred spatial locations. Responses to objects can nonetheless be distinct, although they have been similarly acted on in the past and will lead to the same orienting behavior in the future. Our results therefore indicate that a complete experience-driven override of LIP object responses may be difficult or impossible. We relate these results to behavioral work on visual attention.

Looking within and beyond the community: lessons learned by researching, theorising and acting to address urban poverty and health.

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Hodgetts, Darrin; Chamberlain, Kerry; Tankel, Yadena; Groot, Shiloh

2014-01-01

Urban poverty and health inequalities are inextricably intertwined. By working in partnership with service providers and communities to address urban poverty, we can enhance the wellness of people in need. This article reflects on lessons learned from the Family100 project that explores the everyday lives, frustrations and dilemmas faced by 100 families living in poverty in Auckland. Lessons learned support the need to bring the experiences and lived realities of families to the fore in public deliberations about community and societal responses to urban poverty and health inequality.

First keynote address - biological monitoring

International Nuclear Information System (INIS)

Turner, J.E.

1984-01-01

The author describes the interplay of physical research and the practice of radiation protection. There are both analogies in and differences between the problems of health protection from radiation and chemical pollutants. In formulating research objectives for synfuel technologies, it is important to take what lessons there are to be learned from the radiation experience. The regulation of the exposure of persons to radiation probably rests on a firmer scientific basis than does the regulation of exposure to many toxic chemicals. Some things in radiation protection - in both applied work and in research - should help to guide in approaching chemicals. The second section of this paper gives a brief description of the practice of radiation protection. The next section mentions some fundamental deficiencies that exist in radiation protection. Some physical research avenues illustrate how such deficiencies are being addressed as part of an integrated radiation research program. In the fourth section the author focuses on chemical pollutants, drawing some lessons from the radiation experience

Linking actions and objects: Context-specific learning of novel weight priors.

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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.

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...

Learning Mathematics by Designing, Programming, and Investigating with Interactive, Dynamic Computer-Based Objects

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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…

Error-Driven Learning in Visual Categorization and Object Recognition: A Common-Elements Model

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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…

Objects of Desire.

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Zielinski, Dave

2000-01-01

Describes learning objects, also known as granules, chunks, or information nuggets, and likens them to help screens. Discusses concerns about how they can go wrong: (1) faulty pretest questions; (2) missing links in the learning object chain; (3) poor frames of reference; and (4) lack of customization. (JOW)

Pre-Service and In-Service Teachers' Experiences of Learning to Program in an Object-Oriented Language

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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…

Rapid response learning of brand logo priming: Evidence that brand priming is not dominated by rapid response learning.

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Boehm, Stephan G; Smith, Ciaran; Muench, Niklas; Noble, Kirsty; Atherton, Catherine

2017-08-31

Repetition priming increases the accuracy and speed of responses to repeatedly processed stimuli. Repetition priming can result from two complementary sources: rapid response learning and facilitation within perceptual and conceptual networks. In conceptual classification tasks, rapid response learning dominates priming of object recognition, but it does not dominate priming of person recognition. This suggests that the relative engagement of network facilitation and rapid response learning depends on the stimulus domain. Here, we addressed the importance of the stimulus domain for rapid response learning by investigating priming in another domain, brands. In three experiments, participants performed conceptual decisions for brand logos. Strong priming was present, but it was not dominated by rapid response learning. These findings add further support to the importance of the stimulus domain for the relative importance of network facilitation and rapid response learning, and they indicate that brand priming is more similar to person recognition priming than object recognition priming, perhaps because priming of both brands and persons requires individuation.

Ecological origins of object salience: reward, uncertainty, aversiveness and novelty

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Ali Ghazizadeh

2016-08-01

Full Text Available Among many objects around us, some of them are more salient than others (i.e., attract our attention automatically. Some objects may be inherently salient (e.g., brighter, but others may become salient by virtue of their ecological relevance through experience. However, the importance of ecological experience in guiding attention has not been studied systematically. To address this question, we let subjects (macaque monkeys view a large number of complex objects (>300, each experienced repeatedly (>5 days with rewarding, aversive or no outcome association (mere-perceptual exposure. Test of salience was done on separate days using free viewing with no outcome. We found that gaze was biased among the objects from the outset, affecting saccades to objects or fixations within objects. When the outcome was rewarding, gaze preference was stronger (i.e. positive for objects with larger or equal but uncertain rewards. The effects of aversive outcomes were variable. Gaze preference was positive for some outcome associations (e.g. airpuff, but negative for others (e.g. time-out, possibly due to differences in threat levels. Finally, novel objects attracted gaze, but mere perceptual exposure of objects reduced their salience (learned negative salience. Our results show that, in primates, object salience is strongly influenced by previous ecological experience and is supported by a large memory capacity. Owing to such learned salience, the capacity to rapidly choose important objects can grow during the entire life to promote biological fitness.

Learning Clinical Procedures Through Internet Digital Objects: Experience of Undergraduate Students Across Clinical Faculties

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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

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...

Third-Party Social Interaction and Word Learning from Video

Science.gov (United States)

O'Doherty, Katherine; Troseth, Georgene L.; Shimpi, Priya M.; Goldenberg, Elizabeth; Akhtar, Nameera; Saylor, Megan M.

2011-01-01

In previous studies, very young children have learned words while "overhearing" a conversation, yet they have had trouble learning words from a person on video. In Study 1, 64 toddlers (mean age = 29.8 months) viewed an object-labeling demonstration in 1 of 4 conditions. In 2, the speaker (present or on video) directly addressed the child, and in…

A Personal Journey Into Home Learning

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Colleen RAJA

2012-12-01

Full Text Available In this narrative the author, Colleen Raja, shares her personal experience and reflections on the decision she made to homeschool. Through reflection and story she shares her own struggles and triumphs in learning about herself, her surroundings and the true desires and needs of her children. She also addresses and debunks some of the typical stereotypes and objections to home learning. In the end she sees that what had taken her several years to discover about and desire from the lifestyle of home learning took her children mere moments to embrace.

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

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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.

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

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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.

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.

Learning User Preferences for Sets of Objects

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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.

A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems

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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.

Concept Maps as Instructional Tools for Improving Learning of Phase Transitions in Object-Oriented Analysis and Design

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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…

Space Objects Maneuvering Detection and Prediction via Inverse Reinforcement Learning

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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.

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....

Pinoy Nutrition Hub: The Philippine Experience in Addressing Moderate Malnutrition

International Nuclear Information System (INIS)

Ramos, Arlo; Fuentes, Eureka; Duque, Yvonette; Soriano, Nezer; Gomez, Marijo

2014-01-01

Full text: • Objective: Malnutrition is a persistent problem in the Philippines. The 2011 survey of the Food and Nutrition Research Institute reported that 3 out of 10 children are malnourished. Data shows 20.2% of children 0-47 months are underweight while 33.6% are stunted. This rate is higher in depressed areas in the country. PD Hearth is a time and tested effective program model to address malnutrition. But the PDH has minimum standards that need to be followed in the program implementation. However, a developing country like the Philippines has limitations in its resources and implementations. This paper aims to share the Philippine experience in addressing moderate malnutrition through a contextualized and modified PD Hearth approach. The specific objectives of this paper are: - to describe the challenges in implementing PD Hearth in the context of the Philippines; - to describe the innovations and modifications in the PD Hearth; - and, to illustrate the successful intervention of the PNH program against malnourished children in the community. • Methods: The Pinoy Nutrition Hub model is an innovation of PD Hearth approach. The first step was the participatory approach evaluation of existing programs on MNCHN in the communities. The next step was for the stakeholders to identify the gaps and address them. This was followed by gathering lessons learned and good practices that arose from implementing PD Hearth. Innovations were adopted to address restrictions and maximize learning in its implementation. The contextualized approach was called Pinoy Nutrition Hub (PNH). • Outcomes: - The PNH was piloted in three Area Development Programs (ADP) that represent the three island groups of the Philippines. All three ADPs reported improvement in the weight of the malnourished children enrolled in the program. Below is an illustration of the how the actual weight of children in the Visayas ADP increased. Figure 1 (Display Omitted). Average Weight of Malnourished

Facilitating peer based learning through summative assessment - An adaptation of the Objective Structured Clinical Assessment tool for the blended learning environment.

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Wikander, Lolita; Bouchoucha, Stéphane L

2018-01-01

Adapting a course from face to face to blended delivery necessitates that assessments are modified accordingly. In Australia the Objective Structured Clinical Assessment tool, as a derivative from the Objective Structured Clinical Examination, has been used in the face-to-face delivery mode as a formative or summative assessment tool in medicine and nursing since 1990. The Objective Structured Clinical Assessment has been used at Charles Darwin University to assess nursing students' simulated clinical skills prior to the commencement of their clinical placements since 2008. Although the majority of the course is delivered online, students attend a one-week intensive clinical simulation block yearly, prior to attending clinical placements. Initially, the Objective Structured Clinical Assessment was introduced as a lecturer assessed summative assessment, over time it was adapted to better suit the blended learning environment. The modification of the tool from an academic to peer assessed assessment tool, was based on the empirical literature, student feedback and a cross-sectional, qualitative study exploring academics' perceptions of the Objective Structured Clinical Assessment (Bouchoucha et al., 2013a, b). This paper presents an overview of the process leading to the successful adaptation of the Objective Structured Clinical Assessment to suit the requirements of a preregistration nursing course delivered through blended learning. This is significant as many universities are moving their curriculum to fully online or blended delivery, yet little attention has been paid to adapting the assessment of simulated clinical skills. The aim is to identify the benefits and drawbacks of using the peer assessed Objective Structured Clinical Assessment and share recommendations for successful implementation. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Effects of Discipline on the Application of Learning Object Metadata in UK Higher Education: The Case of the Jorum Repository

Science.gov (United States)

Balatsoukas, Panos; O'Brien, Ann; Morris, Anne

2011-01-01

Introduction: This paper reports on the findings of a study investigating the potential effects of discipline (sciences and engineering versus humanities and social sciences) on the application of the Institute of Electrical and Electronic Engineers learning object metadata elements for the description of learning objects in the Jorum learning…

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…

Improving Multi-Instance Multi-Label Learning by Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Ying Yin

2016-05-01

Full Text Available Multi-instance multi-label learning is a learning framework, where every object is represented by a bag of instances and associated with multiple labels simultaneously. The existing degeneration strategy-based methods often suffer from some common drawbacks: (1 the user-specific parameter for the number of clusters may incur the effective problem; (2 SVM may bring a high computational cost when utilized as the classifier builder. In this paper, we propose an algorithm, namely multi-instance multi-label (MIML-extreme learning machine (ELM, to address the problems. To our best knowledge, we are the first to utilize ELM in the MIML problem and to conduct the comparison of ELM and SVM on MIML. Extensive experiments have been conducted on real datasets and synthetic datasets. The results show that MIMLELM tends to achieve better generalization performance at a higher learning speed.

Characterization of medical students recall of factual knowledge using learning objects and repeated testing in a novel e-learning system.

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Taveira-Gomes, Tiago; Prado-Costa, Rui; Severo, Milton; Ferreira, Maria Amélia

2015-01-24

Spaced-repetition and test-enhanced learning are two methodologies that boost knowledge retention. ALERT STUDENT is a platform that allows creation and distribution of Learning Objects named flashcards, and provides insight into student judgments-of-learning through a metric called 'recall accuracy'. This study aims to understand how the spaced-repetition and test-enhanced learning features provided by the platform affect recall accuracy, and to characterize the effect that students, flashcards and repetitions exert on this measurement. Three spaced laboratory sessions (s0, s1 and s2), were conducted with n=96 medical students. The intervention employed a study task, and a quiz task that consisted in mentally answering open-ended questions about each flashcard and grading recall accuracy. Students were randomized into study-quiz and quiz groups. On s0 both groups performed the quiz task. On s1 and s2, the study-quiz group performed the study task followed by the quiz task, whereas the quiz group only performed the quiz task. We measured differences in recall accuracy between groups/sessions, its variance components, and the G-coefficients for the flashcard component. At s0 there were no differences in recall accuracy between groups. The experiment group achieved a significant increase in recall accuracy that was superior to the quiz group in s1 and s2. In the study-quiz group, increases in recall accuracy were mainly due to the session, followed by flashcard factors and student factors. In the quiz group, increases in recall accuracy were mainly accounted by flashcard factors, followed by student and session factors. The flashcard G-coefficient indicated an agreement on recall accuracy of 91% in the quiz group, and of 47% in the study-quiz group. Recall accuracy is an easily collectible measurement that increases the educational value of Learning Objects and open-ended questions. This metric seems to vary in a way consistent with knowledge retention, but further

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...

Object-graphs for context-aware visual category discovery.

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Lee, Yong Jae; Grauman, Kristen

2012-02-01

How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without human supervision, but existing methods assume no prior information and thus tend to perform poorly for cluttered scenes with multiple objects. We propose to leverage knowledge about previously learned categories to enable more accurate discovery, and address challenges in estimating their familiarity in unsegmented, unlabeled images. We introduce two variants of a novel object-graph descriptor to encode the 2D and 3D spatial layout of object-level co-occurrence patterns relative to an unfamiliar region and show that by using them to model the interaction between an image’s known and unknown objects, we can better detect new visual categories. Rather than mine for all categories from scratch, our method identifies new objects while drawing on useful cues from familiar ones. We evaluate our approach on several benchmark data sets and demonstrate clear improvements in discovery over conventional purely appearance-based baselines.

A theoretical design for learning model addressing the networked society

DEFF Research Database (Denmark)

Levinsen, Karin; Nielsen, Janni; Sørensen, Birgitte Holm

2010-01-01

The transition from the industrial to the networked society produces contradictions that challenges the educational system and force it to adapt to new conditions. In a Danish virtual Master in Information and Communication Technologies and Learning (MIL) these contradictions appear as a field of...... which enables students to develop Networked Society competencies and maintain progression in the learning process also during the online periods. Additionally we suggest that our model contributes to the innovation of a networked society's design for learning....... is continuously decreasing. We teach for deep learning but are confronted by students' cost-benefit strategies when they navigate through the study programme under time pressure. To meet these challenges a Design for Learning Model has been developed. The aim is to provide a scaffold that ensures students......' acquisition of the subject matter within a time limit and at a learning quality that support their deep learning process during a subsequent period of on-line study work. In the process of moving from theory to application the model passes through three stages: 1) Conceptual modelling; 2) Orchestration, and 3...

A novice's process of object-oriented programming

DEFF Research Database (Denmark)

Caspersen, Michael Edelgaard; Kölling, Michael

2006-01-01

Exposing students to the process of programming is merely implied but not explicitly addressed in texts on programming which appear to deal with 'program' as a noun rather than as a verb.We present a set of principles and techniques as well as an informal but systematic process of decomposing...... a programming problem. Two examples are used to demonstrate the application of process and techniques.The process is a carefully down-scaled version of a full and rich software engineering process particularly suited for novices learning object-oriented programming. In using it, we hope to achieve two things...

Statistical learning of recurring sound patterns encodes auditory objects in songbird forebrain.

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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.

Addressing Learning Disabilities with UDL and Technology: Strategic Reader

Science.gov (United States)

Hall, Tracey E.; Cohen, Nicole; Vue, Ge; Ganley, Patricia

2015-01-01

CAST created "Strategic Reader," a technology-based system blending Universal Design for Learning (UDL) and Curriculum-Based Measurement (CBM) in a digital learning environment to improve reading comprehension instruction. This experimental study evaluates the effectiveness of Strategic Reader using two treatment conditions for measuring…

Discovery and Use of Online Learning Resources: Case Study Findings

OpenAIRE

Laurie Miller Nelson; James Dorward; Mimi M. Recker

2004-01-01

Much recent research and funding have focused on building Internet-based repositories that contain collections of high-quality learning resources, often called learning objects. Yet little is known about how non-specialist users, in particular teachers, find, access, and use digital learning resources. To address this gap, this article describes a case study of mathematics and science teachers practices and desires surrounding the discovery, selection, and use of digital library resources for...

Microplastics: addressing ecological risk through lessons learned.

Science.gov (United States)

Syberg, Kristian; Khan, Farhan R; Selck, Henriette; Palmqvist, Annemette; Banta, Gary T; Daley, Jennifer; Sano, Larissa; Duhaime, Melissa B

2015-05-01

Plastic litter is an environmental problem of great concern. Despite the magnitude of the plastic pollution in our water bodies, only limited scientific understanding is available about the risk to the environment, particularly for microplastics. The apparent magnitude of the problem calls for quickly developing sound scientific guidance on the ecological risks of microplastics. The authors suggest that future research into microplastics risks should be guided by lessons learned from the more advanced and better understood areas of (eco) toxicology of engineered nanoparticles and mixture toxicity. Relevant examples of advances in these two fields are provided to help accelerate the scientific learning curve within the relatively unexplored area of microplastics risk assessment. Finally, the authors advocate an expansion of the "vector effect" hypothesis with regard to microplastics risk to help focus research of microplastics environmental risk at different levels of biological and environmental organization. © 2015 SETAC.

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…

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…

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.

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.

Discriminative object tracking via sparse representation and online dictionary learning.

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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.

Addressing Student Burnout: What Medical Schools Can Learn From Business Schools.

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Pathipati, Akhilesh S; Cassel, Christine K

2018-03-13

Although they enter school with enthusiasm for a career in medicine, medical students in the United States subsequently report high levels of burnout and disillusionment. As medical school leaders consider how to address this problem, they can look to business schools as one source of inspiration. In this Commentary, the authors argue-based on their collective experience in both medical and business education-that medical schools can draw three lessons from business schools that can help reinvigorate students. First, medical schools should offer more opportunities and dedicated time for creative work. Engaging with diverse challenges promotes intellectual curiosity and can help students maintain perspective. Second, schools should provide more explicit training in resiliency and the management of stressful situations. Many business programs include formal training in how to cope with conflict and how to make high-stakes decisions whereas medical students are typically expected to learn those skills on the job. Finally, medical schools should provide better guidance on practical career considerations like income, lifestyle, and financial skills. Whether in medicine or business, students benefit from open discussions about their personal and professional goals. Medical schools must ensure students have an outlet for those conversations.

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.

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…

New York College of Osteopathic Medicine Learning Outcomes Assessment 2009-2010

Science.gov (United States)

McCarthy, John R.; Mead, Pelham; Achziger, Mary Ann; Bruno, Felicia; Bryant, Claire; Goldstein, Leonard; Jeger, Abraham; Zaika, Rodika; Portanova, Ron

2009-01-01

This is a document that lays out the Mission of the NY College of Osteopathic Medicine's Mission Statement, It's 13 Goals and subsequent Objectives of Learning Outcomes. Benchmarks were established for each Educational Goal and defined further in Objectives. This document represents an historic attempt by NYCOM to address it's need for complete…

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.

Pedagogy framework design in social networked-based learning: Focus on children with learning difficulties

Directory of Open Access Journals (Sweden)

Samira Sadat Sajadi

2014-09-01

Full Text Available This paper presents an investigation on the theory of constructivism applicable for learners with learning difficulties, specifically learners with Attention Deficit Hyperactivity Disorder (ADHD. The primary objective of this paper is to determine whether a constructivist technology enhanced learning pedagogy could be used to help ADHD learners cope with their educational needs within a social-media learning environment. Preliminary work is stated here, in which we are seeking evidence to determine the viability of a constructivist approach for learners with ADHD. The novelty of this research lies in the proposals to support ADHD learners to overcome their weaknesses with appropriate pedagogically sound interventions. As a result, a framework has been designed to illuminate areas in which constructivist pedagogies require to address the limitations of ADHD learners. An analytical framework addressing the suitability of a constructivist learning for ADHD is developed from a combination of literature and expert advice from those involved in the education of learners with ADHD. This analytical framework is married to a new model of pedagogy, which the authors have derived from literature analysis. Future work will expand this model to develop a constructivist social network-based learning and eventually test it in specialist schools with ADHD learners.

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

Exploiting Attribute Correlations: A Novel Trace Lasso-Based Weakly Supervised Dictionary Learning Method.

Science.gov (United States)

Wu, Lin; Wang, Yang; Pan, Shirui

2017-12-01

It is now well established that sparse representation models are working effectively for many visual recognition tasks, and have pushed forward the success of dictionary learning therein. Recent studies over dictionary learning focus on learning discriminative atoms instead of purely reconstructive ones. However, the existence of intraclass diversities (i.e., data objects within the same category but exhibit large visual dissimilarities), and interclass similarities (i.e., data objects from distinct classes but share much visual similarities), makes it challenging to learn effective recognition models. To this end, a large number of labeled data objects are required to learn models which can effectively characterize these subtle differences. However, labeled data objects are always limited to access, committing it difficult to learn a monolithic dictionary that can be discriminative enough. To address the above limitations, in this paper, we propose a weakly-supervised dictionary learning method to automatically learn a discriminative dictionary by fully exploiting visual attribute correlations rather than label priors. In particular, the intrinsic attribute correlations are deployed as a critical cue to guide the process of object categorization, and then a set of subdictionaries are jointly learned with respect to each category. The resulting dictionary is highly discriminative and leads to intraclass diversity aware sparse representations. Extensive experiments on image classification and object recognition are conducted to show the effectiveness of our approach.

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…

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.

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

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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.

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:

The Potential of Capstone Learning Experiences in addressing perceived shortcomings in LLB Training in South Africa

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Geo Quinot

2014-11-01

Full Text Available Current debates about legal education in South Africa have revealed the perception that the LLB curriculum does not adequately integrate various outcomes, in particular outcomes relating to the development of skills in communication, problem solving, ethics, and in general a holistic view of the law in practice. One mechanism that has been mooted as a potential remedy to this situation is capstone courses, which will consolidate and integrate the four years of study in the final year and build a bridge to the world of practice. A literature review on capstone courses and learning experiences (collectively referred to as capstones indicates that these curriculum devices as modes of instruction offer particular pedagogical advantages. These include inculcating a strong perception of coherence across the curriculum and hence discipline in students, providing the opportunity for students to reflect on their learning during the course of the entire programme, creating an opportunity to engage with the complexity of law and legal practice, and guiding students through the transition from university to professional identity. An empirical analysis of the modes of instruction used in LLB curricula at 13 South African law faculties/schools indicates that there are six categories of existing modules or learning experiences that already exhibit elements of capstone-course design. These are clinics, internships, moots, research projects, topical capstones and capstone assessment. A further comparative study into foreign law curricula in especially Australia and the United States of America reveals four further noteworthy approaches to capstone-course design, namely problem-based learning, the virtual office, conferences and remedies courses. The empirical study suggests that capstones indeed hold the potential as learning experiences to address some of the challenges facing legal education in South Africa but that further development of this curriculum

The use of a mobile assistant learning system for health education based on project-based learning.

Science.gov (United States)

Wu, Ting-Ting

2014-10-01

With the development of mobile devices and wireless technology, mobile technology has gradually infiltrated nursing practice courses to facilitate instruction. Mobile devices save manpower and reduce errors while enhancing nursing students' professional knowledge and skills. To achieve teaching objectives and address the drawbacks of traditional education, this study presents a mobile assistant learning system to help nursing students prepare health education materials. The proposed system is based on a project-based learning strategy to assist nursing students with internalizing professional knowledge and developing critical thinking skills. Experimental results show that the proposed mobile system and project-based learning strategy can promote learning effectiveness and efficiency. Most nursing students and nursing educators showed positive attitudes toward this mobile learning system and looked forward to using it again in related courses in the future.

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.

Examining the Use of Web-Based Reusable Learning Objects by Animal and Veterinary Nursing Students

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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…

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…

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.

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…

Improving Collaborative Learning in Online Software Engineering Education

Science.gov (United States)

Neill, Colin J.; DeFranco, Joanna F.; Sangwan, Raghvinder S.

2017-01-01

Team projects are commonplace in software engineering education. They address a key educational objective, provide students critical experience relevant to their future careers, allow instructors to set problems of greater scale and complexity than could be tackled individually, and are a vehicle for socially constructed learning. While all…

Using Mind Maps to Make Student Questioning Effective : Learning Outcomes of a Principle-Based Scenario for Teacher Guidance

NARCIS (Netherlands)

Stokhof, Harry; de Vries, Bregje; Bastiaens, Theo; Martens, Rob

2018-01-01

Student questioning is an important learning strategy, but rare in many classrooms, because teachers have concerns if these questions contribute to attaining curricular objectives. Teachers face the challenge of making student questioning effective for learning the curriculum. To address this

Ten years of Object-Oriented analysis on H1

International Nuclear Information System (INIS)

Laycock, Paul

2012-01-01

Over a decade ago, the H1 Collaboration decided to embrace the object-oriented paradigm and completely redesign its data analysis model and data storage format. The event data model, based on the ROOT framework, consists of three layers - tracks and calorimeter clusters, identified particles and finally event summary data - with a singleton class providing unified access. This original solution was then augmented with a fourth layer containing user-defined objects. This contribution will summarise the history of the solutions used, from modifications to the original design, to the evolution of the high-level end-user analysis object framework which is used by H1 today. Several important issues are addressed - the portability of expert knowledge to increase the efficiency of data analysis, the flexibility of the framework to incorporate new analyses, the performance and ease of use, and lessons learned for future projects.

Addressing Diversity: A Call for Action.

Science.gov (United States)

Henderson, Ingeborg

1991-01-01

Suggests a series of steps that individuals in the foreign language profession can take to effectively address the issue of demographic changes in the U.S. college student populations and keeping foreign language learning a feasible discipline in the future. (26 references) (GLR)

Recurrent processing during object recognition

Directory of Open Access Journals (Sweden)

Randall C. O'Reilly

2013-04-01

Full Text Available How does the brain learn to recognize objects visually, and perform this difficult feat robustly in the face of many sources of ambiguity and variability? We present a computational model based on the biology of the relevant visual pathways that learns to reliably recognize 100 different object categories in the face of of naturally-occurring variability in location, rotation, size, and lighting. The model exhibits robustness to highly ambiguous, partially occluded inputs. Both the unified, biologically plausible learning mechanism and the robustness to occlusion derive from the role that recurrent connectivity and recurrent processing mechanisms play in the model. Furthermore, this interaction of recurrent connectivity and learning predicts that high-level visual representations should be shaped by error signals from nearby, associated brain areas over the course of visual learning. Consistent with this prediction, we show how semantic knowledge about object categories changes the nature of their learned visual representations, as well as how this representational shift supports the mapping between perceptual and conceptual knowledge. Altogether, these findings support the potential importance of ongoing recurrent processing throughout the brain's visual system and suggest ways in which object recognition can be understood in terms of interactions within and between processes over time.

Addressing grammar in the interaction task-based learning environment

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Davis Brent M.

2017-01-01

Full Text Available One of the major problems in language teaching is developing grammatical accuracy. This paper proposes that using error correction based on a functional grammar in a task-based learning approach may be a suitable solution. Towards this end an emic (using categories intrinsic to the language functional grammar of the verb phrase is proposed and a description of how this fits into the focus on form component of task-based learning is provided.

Quantitative Analysis of the Usage of a Pedagogical Tool Combining Questions Listed as Learning Objectives and Answers Provided as Online Videos

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Odette Laneuville

2015-05-01

Full Text Available To improve the learning of basic concepts in molecular biology of an undergraduate science class, a pedagogical tool was developed, consisting of learning objectives listed at the end of each lecture and answers to those objectives made available as videos online. The aim of this study was to determine if the pedagogical tool was used by students as instructed, and to explore students’ perception of its usefulness. A combination of quantitative survey data and measures of online viewing was used to evaluate the usage of the pedagogical practice. A total of 77 short videos linked to 11 lectures were made available to 71 students, and 64 completed the survey. Using online tracking tools, a total of 7046 views were recorded. Survey data indicated that most students (73.4% accessed all videos, and the majority (98.4% found the videos to be useful in assisting their learning. Interestingly, approximately half of the students (53.1% always or most of the time used the pedagogical tool as recommended, and consistently answered the learning objectives before watching the videos. While the proposed pedagogical tool was used by the majority of students outside the classroom, only half used it as recommended limiting the impact on students’ involvement in the learning of the material presented in class.

Physics By Inquiry: Addressing Student Learning and Attitude

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Sadaghiani, Homeyra R.

2008-10-01

In the last decade, the results of Physics Education Research and research-based instructional materials have been disseminated from traditional research universities to a wide variety of colleges and universities. Nevertheless, the ways in which different institutions implement these materials depend on their students and the institutional context. Even with the widespread use of these curriculums, the research documenting the effectiveness of these materials with different student populations is scarce. This paper describes the challenges associated with implementing Physics by Inquiry at California State Polytechnic University Pomona and confirms its effectiveness in promoting student conceptual knowledge of physics. However, despite the positive effect on student learning, the evidence suggests that the students did not appreciate the self-discovery aspect of the inquiry approach and characterized the learning process as difficult and unpleasant.

Assessing Complex Learning Objectives through Analytics

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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.

Addressing Cultural Diversity: Effects of a Problem-Based Intercultural Learning Unit

Science.gov (United States)

Busse, Vera; Krause, Ulrike-Marie

2015-01-01

This article explores to what extent a problem-based learning unit in combination with cooperative learning and affectively oriented teaching methods facilitates intercultural learning. As part of the study, students reflected on critical incidents, which display misunderstandings or conflicts that arise as a result of cultural differences. In…

Approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems

International Nuclear Information System (INIS)

Zhang, Xiaoshun; Yu, Tao; Yang, Bo; Zheng, Limin; Huang, Linni

2015-01-01

Highlights: • A novel optimal carbon-energy combined-flow (OCECF) model is firstly established. • A novel approximate ideal multi-objective solution Q(λ) learning is designed. • The proposed algorithm has a high convergence stability and reliability. • The proposed algorithm can be applied for OCECF in a large-scale power grid. - Abstract: This paper proposes a novel approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems. The carbon emissions, fuel cost, active power loss, voltage deviation and carbon emission loss are chosen as the optimization objectives, which are simultaneously optimized by five different Q-value matrices. The dynamic optimal weight of each objective is calculated online from the entire Q-value matrices such that the greedy action policy can be obtained. Case studies are carried out to evaluate the optimization performance for carbon-energy combined-flow in an IEEE 118-bus system and the regional power grid of southern China.

Use of individualized learning plans among fourth-year sub-interns in pediatrics and internal medicine.

Science.gov (United States)

Shepard, Michelle E; Sastre, Elizabeth A; Davidson, Mario A; Fleming, Amy E

2012-01-01

Individualized Learning Plans (ILPs) are an effective tool for promoting self-directed learning among residents. However, no literature details ILP use among medical students. Fifty fourth-year sub-interns in pediatrics and internal medicine created ILPs, including a self-assessment of strengths and weaknesses based on ACGME core competencies and the setting of learning objectives. During weekly follow-up meetings with faculty mentors and peers, students discussed challenges and revised goals. Upon completion of the rotation, students completed a survey of Likert-scale questions addressing satisfaction with and perceived utility of ILP components. Students most often self-identified strengths in the areas of Professionalism and Interpersonal and Communication Skills and weaknesses in Patient Care and Systems-Based Practice. Eighty-two percent set at least one learning objective in an identified area of weakness. Students expressed high confidence in their abilities to create achievable learning objectives and to generate strategies to meet those objectives. Students agreed that discussions during group meetings were meaningful, and they identified the setting learning objectives and weekly meetings as the most important elements of the exercise. Fourth-year sub-interns reported that ILPs helped them to accomplish rotation goals, with the setting of learning objectives and weekly discussions being the most useful elements.

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.

Personalización del proceso de aprendizaje usando learning objects reutilizables

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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.

Chair's Address: Voices of the Company We Keep

Science.gov (United States)

Anokye, Akua Duku

2007-01-01

This article presents a written version of the address Akua Duku Anokye, chairwoman of the Conference on College Composition and Communication (CCCC), gave at the CCCC meeting in New York on March 24, 2007. In her address, Anokye talked about the importance of how an entity or an individual is known by the company they keep. To learn with whom has…

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.…

Problem-Based Learning Associated by Action-Process-Object-Schema (APOS) Theory to Enhance Students' High Order Mathematical Thinking Ability

Science.gov (United States)

Mudrikah, Achmad

2016-01-01

The research has shown a model of learning activities that can be used to stimulate reflective abstraction in students. Reflective abstraction as a method of constructing knowledge in the Action-Process-Object-Schema theory, and is expected to occur when students are in learning activities, will be able to encourage students to make the process of…

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...

Supplementing an emissions tax by a feed-in tariff for renewable electricity to address learning spillovers

International Nuclear Information System (INIS)

Lehmann, Paul

2013-01-01

In the presence of learning spillovers related to renewable energy technologies, an optimal strategy to mitigate climate change should complement an emissions tax by a subsidy for renewables. This article addresses the question how such subsidy should be designed. It is shown that the widely-used approach of a revenue-neutral fixed feed-in tariff can yield an optimal outcome under restrictive conditions only. It has to be adapted continuously as the electricity price changes. Moreover, funding the tariff by a surcharge on the electricity price has important implications for the design of the emission tax. The optimal tax rate has to be below the Pigovian level, differentiated across fossil fuels and adapted over time as the patterns of technological development change. These requirements may pose a formidable challenge for practical decision-making. However, it is important to point out that the eventual choices made with respect to the design and funding of a feed-in tariff have to be based on a careful and more comprehensive policy assessment, including, inter alia, economic effects beyond the electricity sector and existing institutional constraints. - Highlights: • Learning spillovers may warrant a combination of emissions and technology policies. • A revenue-neutral feed-in tariff can correct learning spillovers efficiently. • Optimal implementation of this approach is tedious in practice though. • Tariff and emissions tax have to be differentiated and adapted continuously. • Eventual policy decision depends on institutional constraints and economy-wide effects

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

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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. 

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....

Where's Waldo? How perceptual, cognitive, and emotional brain processes cooperate during learning to categorize and find desired objects in a cluttered scene

Directory of Open Access Journals (Sweden)

Stephen eGrossberg

2014-06-01

Full Text Available The Where’s Waldo problem concerns how individuals can rapidly learn to search a scene to detect, attend, recognize, and look at a valued target object in it. This article develops the ARTSCAN Search neural model to clarify how brain mechanisms across the What and Where cortical streams are coordinated to solve the Where's Waldo problem. The What stream learns positionally-invariant object representations, whereas the Where stream controls positionally-selective spatial and action representations. The model overcomes deficiencies of these computationally complementary properties through What and Where stream interactions. Where stream processes of spatial attention and predictive eye movement control modulate What stream processes whereby multiple view- and positionally-specific object categories are learned and associatively linked to view- and positionally-invariant object categories through bottom-up and attentive top-down interactions. Gain fields control the coordinate transformations that enable spatial attention and predictive eye movements to carry out this role. What stream cognitive-emotional learning processes enable the focusing of motivated attention upon the invariant object categories of desired objects. What stream cognitive names or motivational drives can prime a view- and positionally-invariant object category of a desired target object. A volitional signal can convert these primes into top-down activations that can, in turn, prime What stream view- and positionally-specific categories. When it also receives bottom-up activation from a target, such a positionally-specific category can cause an attentional shift in the Where stream to the positional representation of the target, and an eye movement can then be elicited to foveate it. These processes describe interactions among brain regions that include visual cortex, parietal cortex inferotemporal cortex, prefrontal cortex, amygdala, basal ganglia, and superior colliculus.

Academic Staff Perspectives Towards Adoption of E-learning at Melaka Manipal Medical College: Has E-learning Redefined our Teaching Model?

Science.gov (United States)

Bhardwaj, A; Nagandla, K; Swe, K Mm; Abas, A Bl

2015-01-01

E-learning is the use of Information and Communication Technology (ICT) to provide online education and learning. E- Learning has now been integrated into the traditional teaching as the concept of 'blended learning' that combines digital learning with the existing traditional teaching methods to address the various challenges in the field of medical education. Structured e-learning activities were started in Melaka Manipal Medical College in 2009 via e-learning platform (MOODLE-Modular Object-Oriented Dynamic Learning Environment). The objective of the present study is to investigate the faculty opinions toward the existing e-learning activities, and to analyse the extent of adopting and integration of e-learning into their traditional teaching methods. A cross sectional study was conducted among faculties of Medicine and Dentistry using pre-tested questionnaires. The data was analyzed by using the statistical package for social science, SPSS, version 16.0. The result of our survey indicates that majority of our faculty (65.4%) held positive opinion towards e-learning. Among the few, who demonstrated reservations, it is attributed to their average level of skills and aptitude in the use of computers that was statistically significant (pe-learning that enables smooth transition of the faculty from their traditional teaching methods into blended approach. Our results are anticipated to strengthen the existing e-learning activities of our college and other universities and convincingly adopt e-learning as a viable teaching and learning strategy.

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…

Factors affecting the use of social media in the learning process

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Edison W. Lubua

2017-10-01

Full Text Available Background: The study was established based on the inherent challenges of traditional learning systems, which require to be addressed. Arguably, social media can address many challenges of traditional learning if used properly. On this basis, it was important for the study to determine factors associated with the adoption of social media in learning. Objectives: This study determines the relationship between the ease of use and the usefulness of social media to its adoption. Moreover, it shows whether the perceived security of social media relates to its adoption in the learning environment of higher learning students. The objectives were met through testing hypotheses. Methods: Overall, the study was objective and followed the positivism philosophical stance. It adopted the survey research design. Data were collected through the use of a closed-end questionnaire and was tested using descriptive statistics and the One-Way ANOVA model. The generalisation of the results of tested hypotheses is allowed to the population with characteristics similar to that of the study. Results: Social media offer a good platform for the learning process. Moreover, necessary efforts are required to enhance the perception of users on the usefulness of social media, and improve their awareness of security issues because they relate with the adoption of social media. Also, the complexity of social media relates with to adoption. An ease of use platform enhances the adoption. Conclusion: Social media offer a suitable platform for the extension of traditional classes. Their use would be more effective provided that users are aware of maintaining their safety, able to apply social media tools and able to share the content useful to their learning process. Moreover, the study recommends further studies in specific social media.

The role of play objects and object play in human cognitive evolution and innovation.

Science.gov (United States)

Riede, Felix; Johannsen, Niels N; Högberg, Anders; Nowell, April; Lombard, Marlize

2018-01-01

In this contribution, we address a major puzzle in the evolution of human material culture: If maturing individuals just learn their parental generation's material culture, then what is the origin of key innovations as documented in the archeological record? We approach this question by coupling a life-history model of the costs and benefits of experimentation with a niche-construction perspective. Niche-construction theory suggests that the behavior of organisms and their modification of the world around them have important evolutionary ramifications by altering developmental settings and selection pressures. Part of Homo sapiens' niche is the active provisioning of children with play objects - sometimes functional miniatures of adult tools - and the encouragement of object play, such as playful knapping with stones. Our model suggests that salient material culture innovation may occur or be primed in a late childhood or adolescence sweet spot when cognitive and physical abilities are sufficiently mature but before the full onset of the concerns and costs associated with reproduction. We evaluate the model against a series of archeological cases and make suggestions for future research. © 2018 The Authors Evolutionary Anthropology Published by Wiley Periodicals, Inc.

The role of play objects and object play in human cognitive evolution and innovation

Science.gov (United States)

Johannsen, Niels N.; Högberg, Anders; Nowell, April; Lombard, Marlize

2018-01-01

Abstract In this contribution, we address a major puzzle in the evolution of human material culture: If maturing individuals just learn their parental generation's material culture, then what is the origin of key innovations as documented in the archeological record? We approach this question by coupling a life‐history model of the costs and benefits of experimentation with a niche‐construction perspective. Niche‐construction theory suggests that the behavior of organisms and their modification of the world around them have important evolutionary ramifications by altering developmental settings and selection pressures. Part of Homo sapiens' niche is the active provisioning of children with play objects — sometimes functional miniatures of adult tools — and the encouragement of object play, such as playful knapping with stones. Our model suggests that salient material culture innovation may occur or be primed in a late childhood or adolescence sweet spot when cognitive and physical abilities are sufficiently mature but before the full onset of the concerns and costs associated with reproduction. We evaluate the model against a series of archeological cases and make suggestions for future research. PMID:29446561

Cross-situational statistical word learning in young children.

Science.gov (United States)

Suanda, Sumarga H; Mugwanya, Nassali; Namy, Laura L

2014-10-01

Recent empirical work has highlighted the potential role of cross-situational statistical word learning in children's early vocabulary development. In the current study, we tested 5- to 7-year-old children's cross-situational learning by presenting children with a series of ambiguous naming events containing multiple words and multiple referents. Children rapidly learned word-to-object mappings by attending to the co-occurrence regularities across these ambiguous naming events. The current study begins to address the mechanisms underlying children's learning by demonstrating that the diversity of learning contexts affects performance. The implications of the current findings for the role of cross-situational word learning at different points in development are discussed along with the methodological implications of employing school-aged children to test hypotheses regarding the mechanisms supporting early word learning. Copyright © 2014 Elsevier Inc. All rights reserved.

Semantic Indexing of Medical Learning Objects: Medical Students' Usage of a Semantic Network.

Science.gov (United States)

Tix, Nadine; Gießler, Paul; Ohnesorge-Radtke, Ursula; Spreckelsen, Cord

2015-11-11

The Semantically Annotated Media (SAM) project aims to provide a flexible platform for searching, browsing, and indexing medical learning objects (MLOs) based on a semantic network derived from established classification systems. Primarily, SAM supports the Aachen emedia skills lab, but SAM is ready for indexing distributed content and the Simple Knowledge Organizing System standard provides a means for easily upgrading or even exchanging SAM's semantic network. There is a lack of research addressing the usability of MLO indexes or search portals like SAM and the user behavior with such platforms. The purpose of this study was to assess the usability of SAM by investigating characteristic user behavior of medical students accessing MLOs via SAM. In this study, we chose a mixed-methods approach. Lean usability testing was combined with usability inspection by having the participants complete four typical usage scenarios before filling out a questionnaire. The questionnaire was based on the IsoMetrics usability inventory. Direct user interaction with SAM (mouse clicks and pages accessed) was logged. The study analyzed the typical usage patterns and habits of students using a semantic network for accessing MLOs. Four scenarios capturing characteristics of typical tasks to be solved by using SAM yielded high ratings of usability items and showed good results concerning the consistency of indexing by different users. Long-tail phenomena emerge as they are typical for a collaborative Web 2.0 platform. Suitable but nonetheless rarely used keywords were assigned to MLOs by some users. It is possible to develop a Web-based tool with high usability and acceptance for indexing and retrieval of MLOs. SAM can be applied to indexing multicentered repositories of MLOs collaboratively.

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.

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.

Effects of Academic Service Learning in Drug Misuse and Addiction on Students’ Learning Preferences and Attitudes Toward Harm Reduction

Science.gov (United States)

Kabli, Noufissa; Liu, Ben; Seifert, Tricia

2013-01-01

Objective. To examine academic service-learning pedagogy on student learning and perceptions of drug misuse and addiction. Design. Third- and fourth-year pharmacology students were exposed to an academic service-learning pedagogy that integrated a community service experience with lectures, in-class discussions and debates, group projects, a final paper, and an examination. Reflective writing assignments throughout the course required students to assimilate and apply what they had learned in the classroom to what they learned in their community placement. Assessment. Changes in students’ responses on pre- and post-course survey instruments reflected shifts toward higher-order thinking. Also, subjective student-learning modalities shifted toward learning by writing. Students’ perspectives and attitudes allowed improved context of issues associated with drug misuse and harm reduction models. Conclusion. Academic service-learning pedagogy contributes to developing adaptable, well-rounded, engaged learners who become more compassionate and pragmatic in addressing scientific and social questions relating to drug addiction. PMID:23610481

Lessons Learned From Dynamic Simulations of Advanced Fuel Cycles

International Nuclear Information System (INIS)

Piet, Steven J.; Dixon, Brent W.; Jacobson, Jacob J.; Matthern, Gretchen E.; Shropshire, David E.

2009-01-01

Years of performing dynamic simulations of advanced nuclear fuel cycle options provide insights into how they could work and how one might transition from the current once-through fuel cycle. This paper summarizes those insights from the context of the 2005 objectives and goals of the Advanced Fuel Cycle Initiative (AFCI). Our intent is not to compare options, assess options versus those objectives and goals, nor recommend changes to those objectives and goals. Rather, we organize what we have learned from dynamic simulations in the context of the AFCI objectives for waste management, proliferation resistance, uranium utilization, and economics. Thus, we do not merely describe 'lessons learned' from dynamic simulations but attempt to answer the 'so what' question by using this context. The analyses have been performed using the Verifiable Fuel Cycle Simulation of Nuclear Fuel Cycle Dynamics (VISION). We observe that the 2005 objectives and goals do not address many of the inherently dynamic discriminators among advanced fuel cycle options and transitions thereof

Evaluation of Learning Environments for Object-Oriented Programming: Measuring Cognitive Load with a Novel Measurement Technique

Science.gov (United States)

Uysal, Murat Pasa

2016-01-01

Various methods and tools have been proposed to overcome the learning obstacles for Object-Oriented Programming (OOP). However, it remains difficult especially for novice learners. The problem may be not only adopting an instructional method, but also an Integrated Development Environment (IDE). Learners employ IDEs as a means to solve programming…

An Introduction to Object-Oriented Programming with a Didactic Microworld: "objectKarel"

Science.gov (United States)

Xinogalos, Stelios; Satratzemi, Maya; Dagdilelis, Vassilios

2006-01-01

The objects-first strategy to teaching programming has prevailed over the imperative-first and functional-first strategies during the last decade. However, the objects-first strategy has created added difficulties to both the teaching and learning of programming. In an attempt to confront these difficulties and support the objects-first strategy…

Partnering to provide simulated learning to address Interprofessional Education Collaborative core competencies.

Science.gov (United States)

Murphy, Judy I; Nimmagadda, Jayashree

2015-05-01

Learning to effectively communicate and work with other professionals requires skill, yet interprofessional education is often not included in the undergraduate healthcare provider curriculum. Simulation is an effective pedagogy to bring students from multiple professions together for learning. This article describes a pilot study where nursing and social work students learned together in a simulated learning activity, which was evaluated to by the Readiness for Interprofessional Learning Scale (RIPLS). The RIPLS was used before and after the simulated activity to determine if this form of education impacted students' perceptions of readiness to learn together. Students from both professions improved in their RIPLS scores. Students were also asked to identify their interprofessional strengths and challenges before and after the simulation. Changes were identified in qualitative data where reports of strengths and challenges indicated learning and growth had occurred. In conclusion, this pilot study suggests that interprofessional simulation can be an effective method to integrate Interprofessional Education Collaborative core competencies into the curriculum.

Cultural dimensions of learning: Addressing the challenges of multicultural instruction

OpenAIRE

Patrick Parrish; Jennifer A. Linder-VanBerschot

2010-01-01

The growing multicultural nature of education and training environments makes it critical that instructors and instructional designers, especially those working in online learning environments, develop skills to deliver culturally sensitive and culturally adaptive instruction. This article explores research into cultural differences to identify those dimensions of culture that are most likely to impact instructional situations. It presents these in the cultural dimensions of learning framewor...

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.

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.

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

Addressing techniques of liquid crystal displays

CERN Document Server

Ruckmongathan, Temkar N

2014-01-01

Unique reference source that can be used from the beginning to end of a design project to aid choosing an appropriate LCD addressing technique for a given application This book will be aimed at design engineers who are likely to embed LCD drivers and controllers in many systems including systems on chip. Such designers face the challenge of making the right choice of an addressing technique that will serve them with best performance at minimal cost and complexity. Readers will be able to learn about various methods available for driving matrix LCDs and the comparisons at the end of each chap

A unified computational model of the development of object unity, object permanence, and occluded object trajectory perception.

Science.gov (United States)

Franz, A; Triesch, J

2010-12-01

The perception of the unity of objects, their permanence when out of sight, and the ability to perceive continuous object trajectories even during occlusion belong to the first and most important capacities that infants have to acquire. Despite much research a unified model of the development of these abilities is still missing. Here we make an attempt to provide such a unified model. We present a recurrent artificial neural network that learns to predict the motion of stimuli occluding each other and that develops representations of occluded object parts. It represents completely occluded, moving objects for several time steps and successfully predicts their reappearance after occlusion. This framework allows us to account for a broad range of experimental data. Specifically, the model explains how the perception of object unity develops, the role of the width of the occluders, and it also accounts for differences between data for moving and stationary stimuli. We demonstrate that these abilities can be acquired by learning to predict the sensory input. The model makes specific predictions and provides a unifying framework that has the potential to be extended to other visual event categories. Copyright © 2010 Elsevier Inc. All rights reserved.

Addressing NCDs through research and capacity building in LMICs: lessons learned from tobacco control.

Science.gov (United States)

Sturke, Rachel; Vorkoper, Susan; Duncan, Kalina; Levintova, Marya; Parascondola, Mark

2016-01-01

Confronting the global non-communicable diseases (NCDs) crisis requires a critical mass of scientists who are well versed in regional health problems and understand the cultural, social, economic, and political contexts that influence the effectiveness of interventions. Investments in global NCD research must be accompanied by contributions to local research capacity. The National Institutes of Health (NIH) and the Fogarty International Center have a long-standing commitment to supporting research capacity building and addressing the growing burden of NCDs in low- and middle-income countries. One program in particular, the NIH International Tobacco and Health Research and Capacity Building Program (TOBAC program), offers an important model for conducting research and building research capacity simultaneously. This article describes the lessons learned from this unique funding model and demonstrates how a relatively modest investment can make important contributions to scientific evidence and capacity building that could inform ongoing and future efforts to tackle the global burden of NCDs.

Addressing NCDs through research and capacity building in LMICs: lessons learned from tobacco control

Directory of Open Access Journals (Sweden)

Rachel Sturke

2016-08-01

Full Text Available Confronting the global non-communicable diseases (NCDs crisis requires a critical mass of scientists who are well versed in regional health problems and understand the cultural, social, economic, and political contexts that influence the effectiveness of interventions. Investments in global NCD research must be accompanied by contributions to local research capacity. The National Institutes of Health (NIH and the Fogarty International Center have a long-standing commitment to supporting research capacity building and addressing the growing burden of NCDs in low- and middle-income countries. One program in particular, the NIH International Tobacco and Health Research and Capacity Building Program (TOBAC program, offers an important model for conducting research and building research capacity simultaneously. This article describes the lessons learned from this unique funding model and demonstrates how a relatively modest investment can make important contributions to scientific evidence and capacity building that could inform ongoing and future efforts to tackle the global burden of NCDs.

Addressing gender dynamics and engaging men in HIV programs: lessons learned from Horizons research.

Science.gov (United States)

Pulerwitz, Julie; Michaelis, Annie; Verma, Ravi; Weiss, Ellen

2010-01-01

In the field of human immunodeficiency virus (HIV) prevention, there has been increasing interest in the role that gender plays in HIV and violence risk, and in successfully engaging men in the response. This article highlights findings from more than 10 studies in Asia, Africa, and Latin America--conducted from 1997 through 2007 as part of the Horizons program--that have contributed to understanding the relationship between gender and men's behaviors, developing useful measurement tools for gender norms, and designing and evaluating the impact of gender-focused program strategies. Studies showed significant associations between support for inequitable norms and risk, such as more partner violence and less condom use. Programmatic lessons learned ranged from insights into appropriate media messages, to strategies to engage men in critically reflecting upon gender inequality, to the qualities of successful program facilitators. The portfolio of work reveals the potential and importance of directly addressing gender dynamics in HIV- and violence-prevention programs for both men and women.

Addressing key concepts in physical geography through interactive learning activities in an online geo-ICT environment

Science.gov (United States)

Verstraeten, Gert; Steegen, An; Martens, Lotte

2016-04-01

The increasing number of geospatial datasets and free online geo-ICT tools offers new opportunities for education in Earth Sciences. Geospatial technology indeed provides an environment through which interactive learning can be introduced in Earth Sciences curricula. However, the effectiveness of such e-learning approaches in terms of learning outcomes has rarely been addressed. Here, we present our experience with the implementation of digital interactive learning activities within an introductory Physical Geography course attended by 90 undergraduate students in Geography, Geology, Biology and Archaeology. Two traditional lectures were replaced by interactive sessions (each 2 h) in a flexible classroom where students had to work both in team and individually in order to explore some key concepts through the integrated use of geospatial data within Google EarthTM. A first interactive lesson dealt with the classification of river systems and aimed to examine the conditions under which rivers tend to meander or to develop a braided pattern. Students were required to collect properties of rivers (river channel pattern, channel slope, climate, discharge, lithology, vegetation, etc). All these data are available on a global scale and have been added as separate map layers in Google EarthTM. Each student collected data for at least two rivers and added this information to a Google Drive Spreadsheet accessible to the entire group. This resulted in a database of more than one hundred rivers spread over various environments worldwide. In a second phase small groups of students discussed the potential relationships between river channel pattern and its controlling factors. Afterwards, the findings of each discussion group were presented to the entire audience. The same set-up was followed in a second interactive session to explore spatial variations in ecosystem properties such as net primary production and soil carbon content. The qualitative evaluation of both interactive

Deep learning for SAR image formation

Science.gov (United States)

Mason, Eric; Yonel, Bariscan; Yazici, Birsen

2017-04-01

The recent success of deep learning has lead to growing interest in applying these methods to signal processing problems. This paper explores the applications of deep learning to synthetic aperture radar (SAR) image formation. We review deep learning from a perspective relevant to SAR image formation. Our objective is to address SAR image formation in the presence of uncertainties in the SAR forward model. We present a recurrent auto-encoder network architecture based on the iterative shrinkage thresholding algorithm (ISTA) that incorporates SAR modeling. We then present an off-line training method using stochastic gradient descent and discuss the challenges and key steps of learning. Lastly, we show experimentally that our method can be used to form focused images in the presence of phase uncertainties. We demonstrate that the resulting algorithm has faster convergence and decreased reconstruction error than that of ISTA.

Learning Science, Learning about Science, Doing Science: Different Goals Demand Different Learning Methods

Science.gov (United States)

Hodson, Derek

2014-01-01

This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that…

Integrated approach to e-learning enhanced both subjective and objective knowledge of aEEG in a neonatal intensive care unit.

Science.gov (United States)

Poon, W B; Tagamolila, V; Toh, Y P; Cheng, Z R

2015-03-01

Various meta-analyses have shown that e-learning is as effective as traditional methods of continuing professional education. However, there are some disadvantages to e-learning, such as possible technical problems, the need for greater self-discipline, cost involved in developing programmes and limited direct interaction. Currently, most strategies for teaching amplitude-integrated electroencephalography (aEEG) in neonatal intensive care units (NICUs) worldwide depend on traditional teaching methods. We implemented a programme that utilised an integrated approach to e-learning. The programme consisted of three sessions of supervised protected time e-learning in an NICU. The objective and subjective effectiveness of the approach was assessed through surveys administered to participants before and after the programme. A total of 37 NICU staff (32 nurses and 5 doctors) participated in the study. 93.1% of the participants appreciated the need to acquire knowledge of aEEG. We also saw a statistically significant improvement in the subjective knowledge score (p = 0.041) of the participants. The passing rates for identifying abnormal aEEG tracings (defined as ≥ 3 correct answers out of 5) also showed a statistically significant improvement (from 13.6% to 81.8%, p e-learning can help improve subjective and objective knowledge of aEEG.

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....

Modeling of Students' Profile and Learning Chronicle with Data Cubes

Science.gov (United States)

Ola, Ade G.; Bai, Xue; Omojokun, Emmanuel E.

2014-01-01

Over the years, companies have relied on On-Line Analytical Processing (OLAP) to answer complex questions relating to issues in business environments such as identifying profitability, trends, correlations, and patterns. This paper addresses the application of OLAP in education and learning. The objective of the research presented in the paper is…

Audiovisual communication of object-names improves the spatial accuracy of recalled object-locations in topographic maps.

Science.gov (United States)

Lammert-Siepmann, Nils; Bestgen, Anne-Kathrin; Edler, Dennis; Kuchinke, Lars; Dickmann, Frank

2017-01-01

Knowing the correct location of a specific object learned from a (topographic) map is fundamental for orientation and navigation tasks. Spatial reference systems, such as coordinates or cardinal directions, are helpful tools for any geometric localization of positions that aims to be as exact as possible. Considering modern visualization techniques of multimedia cartography, map elements transferred through the auditory channel can be added easily. Audiovisual approaches have been discussed in the cartographic community for many years. However, the effectiveness of audiovisual map elements for map use has hardly been explored so far. Within an interdisciplinary (cartography-cognitive psychology) research project, it is examined whether map users remember object-locations better if they do not just read the corresponding place names, but also listen to them as voice recordings. This approach is based on the idea that learning object-identities influences learning object-locations, which is crucial for map-reading tasks. The results of an empirical study show that the additional auditory communication of object names not only improves memory for the names (object-identities), but also for the spatial accuracy of their corresponding object-locations. The audiovisual communication of semantic attribute information of a spatial object seems to improve the binding of object-identity and object-location, which enhances the spatial accuracy of object-location memory.

Adaptive learning in a compartmental model of visual cortex—how feedback enables stable category learning and refinement

Science.gov (United States)

Layher, Georg; Schrodt, Fabian; Butz, Martin V.; Neumann, Heiko

2014-01-01

The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, both of which are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in computational neuroscience. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of additional (sub-) category representations. We demonstrate the temporal evolution of such learning and show how the proposed combination of an associative memory with a modulatory feedback integration successfully establishes category and subcategory representations

Adaptive learning in a compartmental model of visual cortex - how feedback enables stable category learning and refinement

Directory of Open Access Journals (Sweden)

Georg eLayher

2014-12-01

Full Text Available The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, but both belong to the category of felines. In other words, tigers and leopards are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in the computational neurosciences. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of (sub- category representations. We demonstrate the temporal evolution of such learning and show how the approach successully establishes category and subcategory

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.

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.

Object Knowledge Modulates Colour Appearance

Directory of Open Access Journals (Sweden)

Christoph Witzel

2011-01-01

Full Text Available We investigated the memory colour effect for colour diagnostic artificial objects. Since knowledge about these objects and their colours has been learned in everyday life, these stimuli allow the investigation of the influence of acquired object knowledge on colour appearance. These investigations are relevant for questions about how object and colour information in high-level vision interact as well as for research about the influence of learning and experience on perception in general. In order to identify suitable artificial objects, we developed a reaction time paradigm that measures (subjective colour diagnosticity. In the main experiment, participants adjusted sixteen such objects to their typical colour as well as to grey. If the achromatic object appears in its typical colour, then participants should adjust it to the opponent colour in order to subjectively perceive it as grey. We found that knowledge about the typical colour influences the colour appearance of artificial objects. This effect was particularly strong along the daylight axis.

Object knowledge modulates colour appearance

Science.gov (United States)

Witzel, Christoph; Valkova, Hanna; Hansen, Thorsten; Gegenfurtner, Karl R

2011-01-01

We investigated the memory colour effect for colour diagnostic artificial objects. Since knowledge about these objects and their colours has been learned in everyday life, these stimuli allow the investigation of the influence of acquired object knowledge on colour appearance. These investigations are relevant for questions about how object and colour information in high-level vision interact as well as for research about the influence of learning and experience on perception in general. In order to identify suitable artificial objects, we developed a reaction time paradigm that measures (subjective) colour diagnosticity. In the main experiment, participants adjusted sixteen such objects to their typical colour as well as to grey. If the achromatic object appears in its typical colour, then participants should adjust it to the opponent colour in order to subjectively perceive it as grey. We found that knowledge about the typical colour influences the colour appearance of artificial objects. This effect was particularly strong along the daylight axis. PMID:23145224

Surrounded by Water: Talking to Learn in Today's Classrooms

Science.gov (United States)

Ernst-Slavit, Gisela; Wenger, Kerri J.

2016-01-01

The authors explore the importance of talk and interaction for learning, particularly in relation to new K-12 standards and the prominent role of academic language in today's educational contexts. The article concludes with a detailed example of a Grade 6 teacher's use of content and language objectives to address the needs and strengths of all…

Has Research on Collaborative Learning Technologies Addressed Massiveness? A Literature Review

Science.gov (United States)

Manathunga, Kalpani; Hernández-Leo, Davinia

2015-01-01

There is a growing interest in understanding to what extent innovative educational technologies can be used to support massive courses. Collaboration is one of the main desired elements in massive learning actions involving large communities of participants. Accumulated research in collaborative learning technologies has proposed and evaluated…

Different Keystrokes for Different Folks: Addressing Learning Styles in Online Education

Science.gov (United States)

Pinchot, Jamie; Paullet, Karen

2014-01-01

Online learning has become increasingly popular in recent years. This interest in online education has brought about new learning opportunities for both educators and learners. Technology has enabled higher education institutions the ability to provide quality education reaching learners that might otherwise be impossible. When developing online…

An object memory bias induced by communicative reference

OpenAIRE

Marno, Hanna; Davelaar, Eddy J.; Csibra, Gergely

2015-01-01

In humans, a good proportion of knowledge, including knowledge about objects and object kinds, is acquired via social learning by direct communication from others. If communicative signals raise the expectation of social learning about objects, intrinsic (permanent) features that support object recognition are relevant to store into memory, while extrinsic (accidental) object properties can be ignored. We investigated this hypothesis by instructing participants to memorise shape-colour associ...

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…

Mobile Virtual Learning Object for the Assessment of Acute Pain as a Learning Tool to Assess Acute Pain in Nursing: An Analysis of the Mental Workload.

Science.gov (United States)

Alvarez, Ana Graziela; Sasso, Grace; Iyengar, Sriram

2015-11-06