Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control.

PubMed

Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We envision that such an interaction is influenced by reward modulated heterosynaptic plasticity (RMHP) rule at the thalamus, guiding the overall goal directed behavior. Using a recurrent neural network actor-critic model of the basal ganglia and a feed-forward correlation-based learning model of the cerebellum, we demonstrate that the RMHP rule can effectively balance the outcomes of the two learning systems. This is tested using simulated environments of increasing complexity with a four-wheeled robot in a foraging task in both static and dynamic configurations. Although modeled with a simplified level of biological abstraction, we clearly demonstrate that such a RMHP induced combinatorial learning mechanism, leads to stabler and faster learning of goal-directed behaviors, in comparison to the individual systems. Thus, in this paper we provide a computational model for adaptive combination of the basal ganglia and cerebellum learning systems by way of neuromodulated plasticity for goal-directed decision making in biological and bio-mimetic organisms.

An Empirical Study of Instructor Adoption of Web-Based Learning Systems

ERIC Educational Resources Information Center

Wang, Wei-Tsong; Wang, Chun-Chieh

2009-01-01

For years, web-based learning systems have been widely employed in both educational and non-educational institutions. Although web-based learning systems are emerging as a useful tool for facilitating teaching and learning activities, the number of users is not increasing as fast as expected. This study develops an integrated model of instructor…

Design and Implementation of a Cooperative Learning System for Digital Content Design Curriculum: Investigation on Learning Effectiveness and Social Presence

ERIC Educational Resources Information Center

Huang, Ming-Shang; Hsiao, Wei-Hung; Chang, Tsung-Sheng; Hu, Mei-Huei

2012-01-01

The purpose of this paper is to investigate the learning effectiveness of cooperative learning system based on social presence theory. We develop a web-based cooperative learning system which contains personal module, admin module, course module, communication module, and learning records module to support the implementation of cooperative…

Educational Application of Dialogue System To Support e-Learning.

ERIC Educational Resources Information Center

Kim, Youn-Gi; Lee, Chul-Hwan; Han, Sun-Gwan

This study is on the design and implementation of an educational dialogue system to support e-learning. The learning domain to apply the dialogue system used the subject of geometry. The knowledge in the dialogue-based system for learning geometry was created and represented by XML-based AIML. The implemented system in this study can understand…

A Situated Cultural Festival Learning System Based on Motion Sensing

ERIC Educational Resources Information Center

Chang, Yi-Hsing; Lin, Yu-Kai; Fang, Rong-Jyue; Lu, You-Te

2017-01-01

A situated Chinese cultural festival learning system based on motion sensing is developed in this study. The primary design principle is to create a highly interactive learning environment, allowing learners to interact with Kinect through natural gestures in the designed learning situation to achieve efficient learning. The system has the…

The Conceptual Mechanism for Viable Organizational Learning Based on Complex System Theory and the Viable System Model

ERIC Educational Resources Information Center

Sung, Dia; You, Yeongmahn; Song, Ji Hoon

2008-01-01

The purpose of this research is to explore the possibility of viable learning organizations based on identifying viable organizational learning mechanisms. Two theoretical foundations, complex system theory and viable system theory, have been integrated to provide the rationale for building the sustainable organizational learning mechanism. The…

Experiences with establishing and implementing learning management system and computer-based test system in medical college.

PubMed

Park, Joo Hyun; Son, Ji Young; Kim, Sun

2012-09-01

The purpose of this study was to establish an e-learning system to support learning in medical education and identify solutions for improving the system. A learning management system (LMS) and computer-based test (CBT) system were established to support e-learning for medical students. A survey of 219 first- and second-grade medical students was administered. The questionnaire included 9 forced choice questions about the usability of system and 2 open-ended questions about necessary improvements to the system. The LMS consisted of a class management, class evaluation, and class attendance system. CBT consisted of a test management, item bank, and authoring tool system. The results of the survey showed a high level of satisfaction in all system usability items except for stability. Further, the advantages of the e-learning system were ensuring information accessibility, providing constant feedback, and designing an intuitive interface. Necessary improvements to the system were stability, user control, readability, and diverse device usage. Based on the findings, suggestions for developing an e-learning system to improve usability by medical students and support learning effectively are recommended.

Building a Critical Components for Successful Multimedia-Based Collaborative eLearning Design Framework

ERIC Educational Resources Information Center

Asanok, M.; Kitrakan, P.; Brahmawong, C.

2008-01-01

With newly developing multimedia and web-based technologies have provided opportunities of developing a multimedia-based collaborative eLearning systems. The development of eLearning systems has started a revolution for instructional content delivering, learning activities and social communication. Based on various positions on this issue have…

The Effectiveness of E-Learning Systems: A Review of the Empirical Literature on Learner Control

ERIC Educational Resources Information Center

Sorgenfrei, Christian; Smolnik, Stefan

2016-01-01

E-learning systems are considerably changing education and organizational training. With the advancement of online-based learning systems, learner control over the instructional process has emerged as a decisive factor in technology-based forms of learning. However, conceptual work on the role of learner control in e-learning has not advanced…

Development of an Adaptive Learning System with Multiple Perspectives based on Students' Learning Styles and Cognitive Styles

ERIC Educational Resources Information Center

Yang, Tzu-Chi; Hwang, Gwo-Jen; Yang, Stephen Jen-Hwa

2013-01-01

In this study, an adaptive learning system is developed by taking multiple dimensions of personalized features into account. A personalized presentation module is proposed for developing adaptive learning systems based on the field dependent/independent cognitive style model and the eight dimensions of Felder-Silverman's learning style. An…

Adaptive Device Context Based Mobile Learning Systems

ERIC Educational Resources Information Center

Pu, Haitao; Lin, Jinjiao; Song, Yanwei; Liu, Fasheng

2011-01-01

Mobile learning is e-learning delivered through mobile computing devices, which represents the next stage of computer-aided, multi-media based learning. Therefore, mobile learning is transforming the way of traditional education. However, as most current e-learning systems and their contents are not suitable for mobile devices, an approach for…

The Development of Online Tutorial Program Design Using Problem-Based Learning in Open Distance Learning System

ERIC Educational Resources Information Center

Said, Asnah; Syarif, Edy

2016-01-01

This research aimed to evaluate of online tutorial program design by applying problem-based learning Research Methods currently implemented in the system of Open Distance Learning (ODL). The students must take a Research Methods course to prepare themselves for academic writing projects. Problem-based learning basically emphasizes the process of…

Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

NASA Astrophysics Data System (ADS)

Mihai, Gabroveanu

2015-09-01

Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

Effects of Learning Support in Simulation-Based Physics Learning

ERIC Educational Resources Information Center

Chang, Kuo-En; Chen, Yu-Lung; Lin, He-Yan; Sung, Yao-Ting

2008-01-01

This paper describes the effects of learning support on simulation-based learning in three learning models: experiment prompting, a hypothesis menu, and step guidance. A simulation learning system was implemented based on these three models, and the differences between simulation-based learning and traditional laboratory learning were explored in…

The Effect of Incorporating Good Learners' Ratings in e-Learning Content-Based Recommender System

ERIC Educational Resources Information Center

Ghauth, Khairil Imran; Abdullah, Nor Aniza

2011-01-01

One of the anticipated challenges of today's e-learning is to solve the problem of recommending from a large number of learning materials. In this study, we introduce a novel architecture for an e-learning recommender system. More specifically, this paper comprises the following phases i) to propose an e-learning recommender system based on…

The Impact of a Peer-Learning Agent Based on Pair Programming in a Programming Course

ERIC Educational Resources Information Center

Han, Keun-Woo; Lee, EunKyoung; Lee, YoungJun

2010-01-01

This paper analyzes the educational effects of a peer-learning agent based on pair programming in programming courses. A peer-learning agent system was developed to facilitate the learning of a programming language through the use of pair programming strategies. This system is based on the role of a peer-learning agent from pedagogical and…

An E-learning System based on Affective Computing

NASA Astrophysics Data System (ADS)

Duo, Sun; Song, Lu Xue

In recent years, e-learning as a learning system is very popular. But the current e-learning systems cannot instruct students effectively since they do not consider the emotional state in the context of instruction. The emergence of the theory about "Affective computing" can solve this question. It can make the computer's intelligence no longer be a pure cognitive one. In this paper, we construct an emotional intelligent e-learning system based on "Affective computing". A dimensional model is put forward to recognize and analyze the student's emotion state and a virtual teacher's avatar is offered to regulate student's learning psychology with consideration of teaching style based on his personality trait. A "man-to-man" learning environment is built to simulate the traditional classroom's pedagogy in the system.

A Lecture Supporting System Based on Real-Time Learning Analytics

ERIC Educational Resources Information Center

Shimada, Atsushi; Konomi, Shin'ichi

2017-01-01

A new lecture supporting system based on real-time learning analytics is proposed. Our target is on-site classrooms where teachers give their lectures, and a lot of students listen to teachers' explanation, conduct exercises etc. We utilize not only an e-Learning system, but also an e-Book system to collect real-time learning activities during the…

Web-based e-learning and virtual lab of human-artificial immune system.

PubMed

Gong, Tao; Ding, Yongsheng; Xiong, Qin

2014-05-01

Human immune system is as important in keeping the body healthy as the brain in supporting the intelligence. However, the traditional models of the human immune system are built on the mathematics equations, which are not easy for students to understand. To help the students to understand the immune systems, a web-based e-learning approach with virtual lab is designed for the intelligent system control course by using new intelligent educational technology. Comparing the traditional graduate educational model within the classroom, the web-based e-learning with the virtual lab shows the higher inspiration in guiding the graduate students to think independently and innovatively, as the students said. It has been found that this web-based immune e-learning system with the online virtual lab is useful for teaching the graduate students to understand the immune systems in an easier way and design their simulations more creatively and cooperatively. The teaching practice shows that the optimum web-based e-learning system can be used to increase the learning effectiveness of the students.

Adding Learning to Knowledge-Based Systems: Taking the "Artificial" Out of AI

Treesearch

Daniel L. Schmoldt

1997-01-01

Both, knowledge-based systems (KBS) development and maintenance require time-consuming analysis of domain knowledge. Where example cases exist, KBS can be built, and later updated, by incorporating learning capabilities into their architecture. This applies to both supervised and unsupervised learning scenarios. In this paper, the important issues for learning systems-...

The Development of a Robot-Based Learning Companion: A User-Centered Design Approach

ERIC Educational Resources Information Center

Hsieh, Yi-Zeng; Su, Mu-Chun; Chen, Sherry Y.; Chen, Gow-Dong

2015-01-01

A computer-vision-based method is widely employed to support the development of a variety of applications. In this vein, this study uses a computer-vision-based method to develop a playful learning system, which is a robot-based learning companion named RobotTell. Unlike existing playful learning systems, a user-centered design (UCD) approach is…

Designing for Inquiry-Based Learning with the Learning Activity Management System

ERIC Educational Resources Information Center

Levy, P.; Aiyegbayo, O.; Little, S.

2009-01-01

This paper explores the relationship between practitioners' pedagogical purposes, values and practices in designing for inquiry-based learning in higher education, and the affordances of the Learning Activity Management System (LAMS) as a tool for creating learning designs in this context. Using a qualitative research methodology, variation was…

Content Classification and Context-Based Retrieval System for E-Learning

ERIC Educational Resources Information Center

Mittal, Ankush; Krishnan, Pagalthivarthi V.; Altman, Edward

2006-01-01

A recent focus in web based learning systems has been the development of reusable learning materials that can be delivered as personalized courses depending of a number of factors such as the user's background, his/her learning preferences, current knowledge based on previous assessments, or previous browsing patterns. The student is often…

An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities

ERIC Educational Resources Information Center

Chiang, Tosti H. C.; Yang, Stephen J. H.; Hwang, Gwo-Jen

2014-01-01

In this study, an augmented reality-based mobile learning system is proposed for conducting inquiry-based learning activities. An experiment has been conducted to examine the effectiveness of the proposed approach in terms of learning achievements and motivations. The subjects were 57 fourth graders from two classes taught by the same teacher in…

Development of a Relational Database for Learning Management Systems

ERIC Educational Resources Information Center

Deperlioglu, Omer; Sarpkaya, Yilmaz; Ergun, Ertugrul

2011-01-01

In today's world, Web-Based Distance Education Systems have a great importance. Web-based Distance Education Systems are usually known as Learning Management Systems (LMS). In this article, a database design, which was developed to create an educational institution as a Learning Management System, is described. In this sense, developed Learning…

The Role of Corticostriatal Systems in Speech Category Learning

PubMed Central

Yi, Han-Gyol; Maddox, W. Todd; Mumford, Jeanette A.; Chandrasekaran, Bharath

2016-01-01

One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning. Keywords: category learning, fMRI, corticostriatal systems, speech, putamen PMID:25331600

Complexity theory and the "puzzling" competencies: Systems-based Practice And Practice-based Learning explored.

PubMed

Gonnering, Russell S

2010-01-01

Of all the clinical competencies, the least understood are Systems-Based Practice and Practice-Based Learning and Improvement. With a shift to competency-based education and evaluation across the spectrum of surgical education and practice, a clear understanding of the power and utility of each competency is paramount. Health care operates as a complex adaptive system, with dynamics foreign to many health care professionals and educators. The adaptation and evolution of such a system is related directly to both the individual and the organizational learning of the agents within the system and knowledge management strategies. Far from being "difficult," Systems-Based Practice and Practice-Based Learning form the heart of quality improvement initiatives and future productivity advances in health care. Copyright 2010 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Feedback Design Patterns for Math Online Learning Systems

ERIC Educational Resources Information Center

Inventado, Paul Salvador; Scupelli, Peter; Heffernan, Cristina; Heffernan, Neil

2017-01-01

Increasingly, computer-based learning systems are used by educators to facilitate learning. Evaluations of several math learning systems show that they result in significant student learning improvements. Feedback provision is one of the key features in math learning systems that contribute to its success. We have recently been uncovering feedback…

A reinforcement learning-based architecture for fuzzy logic control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

This paper introduces a new method for learning to refine a rule-based fuzzy logic controller. A reinforcement learning technique is used in conjunction with a multilayer neural network model of a fuzzy controller. The approximate reasoning based intelligent control (ARIC) architecture proposed here learns by updating its prediction of the physical system's behavior and fine tunes a control knowledge base. Its theory is related to Sutton's temporal difference (TD) method. Because ARIC has the advantage of using the control knowledge of an experienced operator and fine tuning it through the process of learning, it learns faster than systems that train networks from scratch. The approach is applied to a cart-pole balancing system.

Choline acetyltransferase in the hippocampus is associated with learning strategy preference in adult male rats.

PubMed

Hawley, Wayne R; Witty, Christine F; Daniel, Jill M; Dohanich, Gary P

2015-08-01

One principle of the multiple memory systems hypothesis posits that the hippocampus-based and striatum-based memory systems compete for control over learning. Consistent with this notion, previous research indicates that the cholinergic system of the hippocampus plays a role in modulating the preference for a hippocampus-based place learning strategy over a striatum-based stimulus--response learning strategy. Interestingly, in the hippocampus, greater activity and higher protein levels of choline acetyltransferase (ChAT), the enzyme that synthesizes acetylcholine, are associated with better performance on hippocampus-based learning and memory tasks. With this in mind, the primary aim of the current study was to determine if higher levels of ChAT and the high-affinity choline uptake transporter (CHT) in the hippocampus were associated with a preference for a hippocampus-based place learning strategy on a task that also could be solved by relying on a striatum-based stimulus--response learning strategy. Results confirmed that levels of ChAT in the dorsal region of the hippocampus were associated with a preference for a place learning strategy on a water maze task that could also be solved by adopting a stimulus-response learning strategy. Consistent with previous studies, the current results support the hypothesis that the cholinergic system of the hippocampus plays a role in balancing competition between memory systems that modulate learning strategy preference. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of an E-Learning Platform for Vocational Education Systems in Germany

ERIC Educational Resources Information Center

Schober, Andreas; Müller, Frederik; Linden, Sabine; Klois, Martha; Künne, Bernd

2014-01-01

This paper describes an existing web-based learning platform named "Third Place of Learning" (TPL)--"Dritter Lernort". This project's aim is to connect the system of vocational education with digital media by a web-based learning platform. TPL supports student's digital learning by means of interactive examples and exercises.…

Developing a Mobile Learning Management System for Outdoors Nature Science Activities Based on 5E Learning Cycle

ERIC Educational Resources Information Center

Lai, Ah-Fur; Lai, Horng-Yih; Chuang, Wei-Hsiang; Wu, Zih-Heng

2015-01-01

Traditional outdoor learning activities such as inquiry-based learning in nature science encounter many dilemmas. Due to prompt development of mobile computing and widespread of mobile devices, mobile learning becomes a big trend on education. The main purpose of this study is to develop a mobile-learning management system for overcoming the…

Discontinuous categories affect information-integration but not rule-based category learning.

PubMed

Maddox, W Todd; Filoteo, J Vincent; Lauritzen, J Scott; Connally, Emily; Hejl, Kelli D

2005-07-01

Three experiments were conducted that provide a direct examination of within-category discontinuity manipulations on the implicit, procedural-based learning and the explicit, hypothesis-testing systems proposed in F. G. Ashby, L. A. Alfonso-Reese, A. U. Turken, and E. M. Waldron's (1998) competition between verbal and implicit systems model. Discontinuous categories adversely affected information-integration but not rule-based category learning. Increasing the magnitude of the discontinuity did not lead to a significant decline in performance. The distance to the bound provides a reasonable description of the generalization profile associated with the hypothesis-testing system, whereas the distance to the bound plus the distance to the trained response region provides a reasonable description of the generalization profile associated with the procedural-based learning system. These results suggest that within-category discontinuity differentially impacts information-integration but not rule-based category learning and provides information regarding the detailed processing characteristics of each category learning system. ((c) 2005 APA, all rights reserved).

Attitudes to the Application of a Web-Based Learning System in a Microbiology Course

ERIC Educational Resources Information Center

Masiello, I.; Ramberg, R.; Lonka, K.

2005-01-01

Computer-based systems have great potential for delivering learning material. Here, a Web-based learning management system is employed by a medical university to support undergraduate courses. The objective was to help the university's staff to understand the readiness and attitudes of students to the use of information technology, their…

The Effectiveness of Using Cloud-Based Cross-Device IRS to Support Classical Chinese Learning

ERIC Educational Resources Information Center

Wang, Yi-Hsuan

2017-01-01

The purpose of the present study was to examine the effects of integrating a cloud-based cross-device interactive response system (CCIRS) on enhancing students' classical Chinese learning. The system is a cloud-based IRS system which provides instructors and learners with an environment in which to achieve immediate interactive learning and…

Constraint-Based Scheduling System

NASA Technical Reports Server (NTRS)

Zweben, Monte; Eskey, Megan; Stock, Todd; Taylor, Will; Kanefsky, Bob; Drascher, Ellen; Deale, Michael; Daun, Brian; Davis, Gene

1995-01-01

Report describes continuing development of software for constraint-based scheduling system implemented eventually on massively parallel computer. Based on machine learning as means of improving scheduling. Designed to learn when to change search strategy by analyzing search progress and learning general conditions under which resource bottleneck occurs.

Personalized E- learning System Based on Intelligent Agent

NASA Astrophysics Data System (ADS)

Duo, Sun; Ying, Zhou Cai

Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

The involvement of model-based but not model-free learning signals during observational reward learning in the absence of choice.

PubMed

Dunne, Simon; D'Souza, Arun; O'Doherty, John P

2016-06-01

A major open question is whether computational strategies thought to be used during experiential learning, specifically model-based and model-free reinforcement learning, also support observational learning. Furthermore, the question of how observational learning occurs when observers must learn about the value of options from observing outcomes in the absence of choice has not been addressed. In the present study we used a multi-armed bandit task that encouraged human participants to employ both experiential and observational learning while they underwent functional magnetic resonance imaging (fMRI). We found evidence for the presence of model-based learning signals during both observational and experiential learning in the intraparietal sulcus. However, unlike during experiential learning, model-free learning signals in the ventral striatum were not detectable during this form of observational learning. These results provide insight into the flexibility of the model-based learning system, implicating this system in learning during observation as well as from direct experience, and further suggest that the model-free reinforcement learning system may be less flexible with regard to its involvement in observational learning. Copyright © 2016 the American Physiological Society.

Development of Adaptive Kanji Learning System for Mobile Phone

ERIC Educational Resources Information Center

Li, Mengmeng; Ogata, Hiroaki; Hou, Bin; Hashimoto, Satoshi; Liu, Yuqin; Uosaki, Noriko; Yano, Yoneo

2010-01-01

This paper describes an adaptive learning system based on mobile phone email to support the study of Japanese Kanji. In this study, the main emphasis is on using the adaptive learning to resolve one common problem of the mobile-based email or SMS language learning systems. To achieve this goal, the authors main efforts focus on three aspects:…

Development of a health care systems curriculum.

PubMed

Pruitt, Zachary; Mhaskar, Rahul; Kane, Bryan G; Barraco, Robert D; DeWaay, Deborah J; Rosenau, Alex M; Bresnan, Kristin A; Greenberg, Marna Rayl

2017-01-01

There is currently no gold standard for delivery of systems-based practice in medical education, and it is challenging to incorporate into medical education. Health systems competence requires physicians to understand patient care within the broader health care system and is vital to improving the quality of care clinicians provide. We describe a health systems curriculum that utilizes problem-based learning across 4 years of systems-based practice medical education at a single institution. This case study describes the application of a problem-based learning approach to system-based practice medical education. A series of behavioral statements, called entrustable professional activities, was created to assess student health system competence. Student evaluation of course curriculum design, delivery, and assessment was provided through web-based surveys. To meet competency standards for system-based practice, a health systems curriculum was developed and delivered across 4 years of medical school training. Each of the health system lectures and problem-based learning activities are described herein. The majority of first and second year medical students stated they gained working knowledge of health systems by engaging in these sessions. The majority of the 2016 graduating students (88.24%) felt that the course content, overall, prepared them for their career. A health systems curriculum in undergraduate medical education using a problem-based learning approach is feasible. The majority of students learning health systems curriculum through this format reported being prepared to improve individual patient care and optimize the health system's value (better care and health for lower cost).

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

NASA Technical Reports Server (NTRS)

Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

1988-01-01

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Web-Based Learning Support System

NASA Astrophysics Data System (ADS)

Fan, Lisa

Web-based learning support system offers many benefits over traditional learning environments and has become very popular. The Web is a powerful environment for distributing information and delivering knowledge to an increasingly wide and diverse audience. Typical Web-based learning environments, such as Web-CT, Blackboard, include course content delivery tools, quiz modules, grade reporting systems, assignment submission components, etc. They are powerful integrated learning management systems (LMS) that support a number of activities performed by teachers and students during the learning process [1]. However, students who study a course on the Internet tend to be more heterogeneously distributed than those found in a traditional classroom situation. In order to achieve optimal efficiency in a learning process, an individual learner needs his or her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This chapter demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. It focuses on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. An example of using Rough Set to analyze student personal information to assist students with effective learning and predict student performance is presented.

An Intelligent Learning Diagnosis System for Web-Based Thematic Learning Platform

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Liu, Ming-Chou; Chu, San-Shine; Cheng, Chih-Lun

2007-01-01

This work proposes an intelligent learning diagnosis system that supports a Web-based thematic learning model, which aims to cultivate learners' ability of knowledge integration by giving the learners the opportunities to select the learning topics that they are interested, and gain knowledge on the specific topics by surfing on the Internet to…

On Learning: Metrics Based Systems for Countering Asymmetric Threats

DTIC Science & Technology

2006-05-25

of self- education . While this alone cannot guarantee organizational learning , no organization can learn without a spirit of individual learning ...held views on globalization and the impact of Information Age technology . The emerging environment conceptually links to the learning model as part...On Learning : Metrics Based Systems for Countering Asymmetric Threats A Monograph by MAJ Rafael Lopez U.S. Army School of Advanced Military

Rapid Training of Information Extraction with Local and Global Data Views

DTIC Science & Technology

2012-05-01

relation type extension system based on active learning a relation type extension system based on semi-supervised learning, and a crossdomain...bootstrapping system for domain adaptive named entity extraction. The active learning procedure adopts features extracted at the sentence level as the local

Learning from and with Museum Objects: Design Perspectives, Environment, and Emerging Learning Systems

ERIC Educational Resources Information Center

Vartiainen, Henriikka; Enkenberg, Jorma

2013-01-01

Sociocultural approaches emphasize the systemic, context-bound nature of learning, which is mediated by other people, physical and conceptual artifacts, and tools. However, current educational systems tend not to approach learning from the systemic perspective, and mostly situate learning within classroom environments. This design-based research…

Future View: Web Navigation based on Learning User's Browsing Strategy

NASA Astrophysics Data System (ADS)

Nagino, Norikatsu; Yamada, Seiji

In this paper, we propose a Future View system that assists user's usual Web browsing. The Future View will prefetch Web pages based on user's browsing strategies and present them to a user in order to assist Web browsing. To learn user's browsing strategy, the Future View uses two types of learning classifier systems: a content-based classifier system for contents change patterns and an action-based classifier system for user's action patterns. The results of learning is applied to crawling by Web robots, and the gathered Web pages are presented to a user through a Web browser interface. We experimentally show effectiveness of navigation using the Future View.

A Genetic Algorithm Approach to Recognise Students' Learning Styles

ERIC Educational Resources Information Center

Yannibelli, Virginia; Godoy, Daniela; Amandi, Analia

2006-01-01

Learning styles encapsulate the preferences of the students, regarding how they learn. By including information about the student learning style, computer-based educational systems are able to adapt a course according to the individual characteristics of the students. In accomplishing this goal, educational systems have been mostly based on the…

The Ontologies of Complexity and Learning about Complex Systems

ERIC Educational Resources Information Center

Jacobson, Michael J.; Kapur, Manu; So, Hyo-Jeong; Lee, June

2011-01-01

This paper discusses a study of students learning core conceptual perspectives from recent scientific research on complexity using a hypermedia learning environment in which different types of scaffolding were provided. Three comparison groups used a hypermedia system with agent-based models and scaffolds for problem-based learning activities that…

3D interactive augmented reality-enhanced digital learning systems for mobile devices

NASA Astrophysics Data System (ADS)

Feng, Kai-Ten; Tseng, Po-Hsuan; Chiu, Pei-Shuan; Yang, Jia-Lin; Chiu, Chun-Jie

2013-03-01

With enhanced processing capability of mobile platforms, augmented reality (AR) has been considered a promising technology for achieving enhanced user experiences (UX). Augmented reality is to impose virtual information, e.g., videos and images, onto a live-view digital display. UX on real-world environment via the display can be e ectively enhanced with the adoption of interactive AR technology. Enhancement on UX can be bene cial for digital learning systems. There are existing research works based on AR targeting for the design of e-learning systems. However, none of these work focuses on providing three-dimensional (3-D) object modeling for en- hanced UX based on interactive AR techniques. In this paper, the 3-D interactive augmented reality-enhanced learning (IARL) systems will be proposed to provide enhanced UX for digital learning. The proposed IARL systems consist of two major components, including the markerless pattern recognition (MPR) for 3-D models and velocity-based object tracking (VOT) algorithms. Realistic implementation of proposed IARL system is conducted on Android-based mobile platforms. UX on digital learning can be greatly improved with the adoption of proposed IARL systems.

A Game Based e-Learning System to Teach Artificial Intelligence in the Computer Sciences Degree

ERIC Educational Resources Information Center

de Castro-Santos, Amable; Fajardo, Waldo; Molina-Solana, Miguel

2017-01-01

Our students taking the Artificial Intelligence and Knowledge Engineering courses often encounter a large number of problems to solve which are not directly related to the subject to be learned. To solve this problem, we have developed a game based e-learning system. The elected game, that has been implemented as an e-learning system, allows to…

Digital case-based learning system in school.

PubMed

Gu, Peipei; Guo, Jiayang

2017-01-01

With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

Digital case-based learning system in school

PubMed Central

Gu, Peipei

2017-01-01

With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework. PMID:29107965

Developing Web-Based Assessment Strategies for Facilitating Junior High School Students to Perform Self-Regulated Learning in an E-Learning Environment

ERIC Educational Resources Information Center

Wang, Tzu-Hua

2011-01-01

This research refers to the self-regulated learning strategies proposed by Pintrich (1999) in developing a multiple-choice Web-based assessment system, the Peer-Driven Assessment Module of the Web-based Assessment and Test Analysis system (PDA-WATA). The major purpose of PDA-WATA is to facilitate learner use of self-regulatory learning behaviors…

C[superscript 4] (C Quad): Development of the Application for Language Learning Based on Social and Cognitive Presences

ERIC Educational Resources Information Center

Yamada, Masanori; Goda, Yoshiko; Matsukawa, Hideya; Hata, Kojiro; Yasunami, Seisuke

2013-01-01

This research aims to develop collaborative language learning systems based on social and cognitive presence for learning settings out of class, and evaluate their effects on learning attitude and performance. The main purpose of this system is focusing on the building of a learning community, therefore the Community of Inquiry (CoI) framework…

Using Games-Based eLearning Technologies in Overcoming Difficulties in Teaching Information Systems

ERIC Educational Resources Information Center

Connolly, Thomas; Stanfield, Mark

2006-01-01

The contributions of this research center on two major areas: delineation of a new model of distance education in which the authors identify three generations of eLearning; and examination of how eLearning and games-based eLearning technologies can be used to enrich the Information Systems (IS) learning experiences of students with different…

The Effectiveness of the Gesture-Based Learning System (GBLS) and Its Impact on Learning Experience

ERIC Educational Resources Information Center

Shakroum, Moamer; Wong, Kok Wai; Fung, Lance Chun Che

2016-01-01

Several studies and experiments have been conducted in recent years to examine the value and the advantage of using the Gesture-Based Learning System (GBLS).The investigation of the influence of the GBLS mode on the learning outcomes is still scarce. Most previous studies did not address more than one category of learning outcomes (cognitive,…

A Methodological Approach to Encourage the Service-Oriented Learning Systems Development

ERIC Educational Resources Information Center

Diez, David; Malizia, Alessio; Aedo, Ignacio; Diaz, Paloma; Fernandez, Camino; Dodero, Juan-Manuel

2009-01-01

The basic idea of service-oriented learning is that a learning environment should be conceived as a set of independent units of learning packaged as learning services. The design, development and deployment of a learning system based on integrating different learning services needs both a technological platform to support the system as well as a…

Recent Trends in Minicomputer-Based Integrated Learning Systems for Reading and Language Arts Instruction.

ERIC Educational Resources Information Center

Balajthy, Ernest

This paper discusses minicomputer-based ILSs (integrated learning systems), i.e., computer-based systems of hardware and software. An example of a minicomputer-based system in a school district (a composite of several actual districts) considers hardware, staffing, scheduling, reactions, problems, and training for a subskill-oriented reading…

Interactive web-based learning modules prior to general medicine advanced pharmacy practice experiences.

PubMed

Isaacs, Alex N; Walton, Alison M; Nisly, Sarah A

2015-04-25

To implement and evaluate interactive web-based learning modules prior to advanced pharmacy practice experiences (APPEs) on inpatient general medicine. Three clinical web-based learning modules were developed for use prior to APPEs in 4 health care systems. The aim of the interactive modules was to strengthen baseline clinical knowledge before the APPE to enable the application of learned material through the delivery of patient care. For the primary endpoint, postassessment scores increased overall and for each individual module compared to preassessment scores. Postassessment scores were similar among the health care systems. The survey demonstrated positive student perceptions of this learning experience. Prior to inpatient general medicine APPEs, web-based learning enabled the standardization and assessment of baseline student knowledge across 4 health care systems.

A New Approach to Personalization: Integrating E-Learning and M-Learning

ERIC Educational Resources Information Center

Nedungadi, Prema; Raman, Raghu

2012-01-01

Most personalized learning systems are designed for either personal computers (e-learning) or mobile devices (m-learning). Our research has resulted in a cloud-based adaptive learning system that incorporates mobile devices into a classroom setting. This system is fully integrated into the formative assessment process and, most importantly,…

Toward a Learner-Centered System for Adult Learning

ERIC Educational Resources Information Center

Hermans, Henry; Kalz, Marco; Koper, Rob

2013-01-01

Purpose: The purpose of this paper is to present an e-learning system that integrates the use of concepts of virtual learning environments, personal learning environments, and social network sites. The system is based on a learning model which comprises and integrates three learning contexts for the adult learner: the formal, instructional…

Time-Decayed User Profile for Second Language Vocabulary Learning System

ERIC Educational Resources Information Center

Li, Li; Wei, Xiao

2014-01-01

Vocabulary learning is the foundation of second language learning. Many E-learning systems have been developed to help learners to learn vocabulary efficiently. Most of these systems employ Ebbinghaus Forgetting Curve to make the review schedule for learners. However, learners are different in learning ability and the review schedule based on…

ELE: An Ontology-Based System Integrating Semantic Search and E-Learning Technologies

ERIC Educational Resources Information Center

Barbagallo, A.; Formica, A.

2017-01-01

ELSE (E-Learning for the Semantic ECM) is an ontology-based system which integrates semantic search methodologies and e-learning technologies. It has been developed within a project of the CME (Continuing Medical Education) program--ECM (Educazione Continua nella Medicina) for Italian participants. ELSE allows the creation of e-learning courses…

Acceptance of Competency-Based Workplace e-Learning Systems: Effects of Individual and Peer Learning Support

ERIC Educational Resources Information Center

Cheng, Bo; Wang, Minhong; Yang, Stephen J. H.; Kinshuk; Peng, Jun

2011-01-01

Current endeavors to integrate competency-based learning approaches with e-learning systems designed for delivery of training to adult learners in the workplace are growing. However, academic efforts in examining learners' perceptions of, and reactions toward, this technology-delivered pedagogical innovation are limited. Drawing together…

An Operational Approach for Building Learning Environments Supporting Cognitive Flexibility

ERIC Educational Resources Information Center

Chieu, Vu Minh

2007-01-01

Constructivism is a learning theory that states that people learn by actively constructing their own knowledge, based on prior knowledge. A significant number of ICT-based constructivist learning systems have been proposed in recent years. According to our analysis, those systems exhibit only a few constructivist principles, and a critical problem…

Automatic Detection of Learning Styles for an E-Learning System

ERIC Educational Resources Information Center

Ozpolat, Ebru; Akar, Gozde B.

2009-01-01

A desirable characteristic for an e-learning system is to provide the learner the most appropriate information based on his requirements and preferences. This can be achieved by capturing and utilizing the learner model. Learner models can be extracted based on personality factors like learning styles, behavioral factors like user's browsing…

The Construction of an Online Competitive Game-Based Learning System for Junior High School Students

ERIC Educational Resources Information Center

Cheng, Yuh-Ming; Kuo, Sheng-Huang; Lou, Shi-Jer; Shih, Ru-Chu

2012-01-01

The purpose of this study aimed to construct an online competitive game-based learning system by using freeware for junior high school students and to assess its effectiveness. From the learning standpoints, game mechanisms including learning points, competition mechanism, training room mechanism, questioning & answering mechanism, tips, and…

Implementation of Project Based Learning in Mechatronic Lab Course at Bandung State Polytechnic

ERIC Educational Resources Information Center

Basjaruddin, Noor Cholis; Rakhman, Edi

2016-01-01

Mechatronics is a multidisciplinary that includes a combination of mechanics, electronics, control systems, and computer science. The main objective of mechatronics learning is to establish a comprehensive mindset in the development of mechatronic systems. Project Based Learning (PBL) is an appropriate method for use in the learning process of…

A self-learning rule base for command following in dynamical systems

NASA Technical Reports Server (NTRS)

Tsai, Wei K.; Lee, Hon-Mun; Parlos, Alexander

1992-01-01

In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

Development of a health care systems curriculum

PubMed Central

Pruitt, Zachary; Mhaskar, Rahul; Kane, Bryan G; Barraco, Robert D; DeWaay, Deborah J; Rosenau, Alex M; Bresnan, Kristin A; Greenberg, Marna Rayl

2017-01-01

Background There is currently no gold standard for delivery of systems-based practice in medical education, and it is challenging to incorporate into medical education. Health systems competence requires physicians to understand patient care within the broader health care system and is vital to improving the quality of care clinicians provide. We describe a health systems curriculum that utilizes problem-based learning across 4 years of systems-based practice medical education at a single institution. Methods This case study describes the application of a problem-based learning approach to system-based practice medical education. A series of behavioral statements, called entrustable professional activities, was created to assess student health system competence. Student evaluation of course curriculum design, delivery, and assessment was provided through web-based surveys. Results To meet competency standards for system-based practice, a health systems curriculum was developed and delivered across 4 years of medical school training. Each of the health system lectures and problem-based learning activities are described herein. The majority of first and second year medical students stated they gained working knowledge of health systems by engaging in these sessions. The majority of the 2016 graduating students (88.24%) felt that the course content, overall, prepared them for their career. Conclusion A health systems curriculum in undergraduate medical education using a problem-based learning approach is feasible. The majority of students learning health systems curriculum through this format reported being prepared to improve individual patient care and optimize the health system’s value (better care and health for lower cost). PMID:29138614

A Web-Based Learning and Assessment System To Support Flexible Education.

ERIC Educational Resources Information Center

Gardner, Lesley; Sheridan, D.; White, D.

2002-01-01

Describes the development of a computer-supported, Web-based learning system, CECIL, at the University of Auckland (New Zealand). Discusses the potential benefits that a university-wide resource management system may have in terms of educational flexibility, such as online learning for distance education, and resource sharing, as well as…

Location Based Services for Outdoor Ecological Learning System: Design and Implementation

ERIC Educational Resources Information Center

Hsiao, Hsien-Sheng; Lin, Chih-Cheng; Feng, Ruei-Ting; Li, Kun Jing

2010-01-01

This paper aimed to demonstrate how location-based services were implemented in ubiquitous outdoor ecological learning system. In an elementary school in northern Taiwan, two fifth grade classes on an ecology project were randomly selected: The experimental group could access the ecological learning system on hand-held devices while the control…

Impact on Student Motivation by Using a QR-Based U-Learning Material Production System to Create Authentic Learning Experiences

ERIC Educational Resources Information Center

Chin, Kai-Yi; Lee, Ko-Fong; Chen, Yen-Lin

2015-01-01

This study developed a QR-based U-Learning Material Production System (QR-ULMPS) that provides teachers with an education tool to motivate college level students enrolled in a liberal arts course. QR-ULMPS was specifically designed to support the development of u-learning materials and create an engaging context-aware u-learning environment for…

Development and Evaluation of Mechatronics Learning System in a Web-Based Environment

ERIC Educational Resources Information Center

Shyr, Wen-Jye

2011-01-01

The development of remote laboratory suitable for the reinforcement of undergraduate level teaching of mechatronics is important. For the reason, a Web-based mechatronics learning system, called the RECOLAB (REmote COntrol LABoratory), for remote learning in engineering education has been developed in this study. The web-based environment is an…

Pre-Service Mathematics Teachers' Experiences with Proficiency-Based Learning

ERIC Educational Resources Information Center

Smith, Carmen Petrick; Tinkler, Alan; DeMink-Carthew, Jessica; Tinker, Barri

2017-01-01

Proficiency-based learning systems are becoming more common across the United States, yet few pre-service mathematics teachers have experienced this type of system in the classroom themselves. Teacher education courses are one opportunity for pre-service teachers to experience proficiency-based learning; however, we know little about the impact…

A Field-Based Learning Experience for Introductory Level GIS Students

ERIC Educational Resources Information Center

Carlson, Tom

2007-01-01

This article describes a pedagogic foundation for introducing a field-based geographic information systems (GIS) experience to the GIS curriculum at the university level and uses a dual evaluation methodology to monitor student learning and satisfaction. Students learned the basics of field-based global position systems (GPS) and GIS data…

Web-Based Reading Annotation System with an Attention-Based Self-Regulated Learning Mechanism for Promoting Reading Performance

ERIC Educational Resources Information Center

Chen, Chih-Ming; Huang, Sheng-Hui

2014-01-01

Due to the rapid development of information technology, web-based learning has become a dominant trend. That is, learners can often learn anytime and anywhere without being restricted by time and space. Autonomic learning primarily occurs in web-based learning environments, and self-regulated learning (SRL) is key to autonomic learning…

Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan.

PubMed

Chen, Hong-Ren; Tseng, Hsiao-Fen

2012-08-01

Web-based e-learning is not restricted by time or place and can provide teachers with a learning environment that is flexible and convenient, enabling them to efficiently learn, quickly develop their professional expertise, and advance professionally. Many research reports on web-based e-learning have neglected the role of the teacher's perspective in the acceptance of using web-based e-learning systems for in-service education. We distributed questionnaires to 402 junior high school teachers in central Taiwan. This study used the Technology Acceptance Model (TAM) as our theoretical foundation and employed the Structure Equation Model (SEM) to examine factors that influenced intentions to use in-service training conducted through web-based e-learning. The results showed that motivation to use and Internet self-efficacy were significantly positively associated with behavioral intentions regarding the use of web-based e-learning for in-service training through the factors of perceived usefulness and perceived ease of use. The factor of computer anxiety had a significantly negative effect on behavioral intentions toward web-based e-learning in-service training through the factor of perceived ease of use. Perceived usefulness and motivation to use were the primary reasons for the acceptance by junior high school teachers of web-based e-learning systems for in-service training. Copyright © 2011 Elsevier Ltd. All rights reserved.

A meta-learning system based on genetic algorithms

NASA Astrophysics Data System (ADS)

Pellerin, Eric; Pigeon, Luc; Delisle, Sylvain

2004-04-01

The design of an efficient machine learning process through self-adaptation is a great challenge. The goal of meta-learning is to build a self-adaptive learning system that is constantly adapting to its specific (and dynamic) environment. To that end, the meta-learning mechanism must improve its bias dynamically by updating the current learning strategy in accordance with its available experiences or meta-knowledge. We suggest using genetic algorithms as the basis of an adaptive system. In this work, we propose a meta-learning system based on a combination of the a priori and a posteriori concepts. A priori refers to input information and knowledge available at the beginning in order to built and evolve one or more sets of parameters by exploiting the context of the system"s information. The self-learning component is based on genetic algorithms and neural Darwinism. A posteriori refers to the implicit knowledge discovered by estimation of the future states of parameters and is also applied to the finding of optimal parameters values. The in-progress research presented here suggests a framework for the discovery of knowledge that can support human experts in their intelligence information assessment tasks. The conclusion presents avenues for further research in genetic algorithms and their capability to learn to learn.

Development of cyberblog-based intelligent tutorial system to improve students learning ability algorithm

NASA Astrophysics Data System (ADS)

Wahyudin; Riza, L. S.; Putro, B. L.

2018-05-01

E-learning as a learning activity conducted online by the students with the usual tools is favoured by students. The use of computer media in learning provides benefits that are not owned by other learning media that is the ability of computers to interact individually with students. But the weakness of many learning media is to assume that all students have a uniform ability, when in reality this is not the case. The concept of Intelligent Tutorial System (ITS) combined with cyberblog application can overcome the weaknesses in neglecting diversity. An Intelligent Tutorial System-based Cyberblog application (ITS) is a web-based interactive application program that implements artificial intelligence which can be used as a learning and evaluation media in the learning process. The use of ITS-based Cyberblog in learning is one of the alternative learning media that is interesting and able to help students in measuring ability in understanding the material. This research will be associated with the improvement of logical thinking ability (logical thinking) of students, especially in algorithm subjects.

A Simple and Effective Remedial Learning System with a Fuzzy Expert System

ERIC Educational Resources Information Center

Lin, C.-C.; Guo, K.-H.; Lin, Y.-C.

2016-01-01

This study aims at implementing a simple and effective remedial learning system. Based on fuzzy inference, a remedial learning material selection system is proposed for a digital logic course. Two learning concepts of the course have been used in the proposed system: number systems and combinational logic. We conducted an experiment to validate…

Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

NASA Astrophysics Data System (ADS)

Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

2018-04-01

A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

The Curse of Planning: Dissecting multiple reinforcement learning systems by taxing the central executive

PubMed Central

Otto, A. Ross; Gershman, Samuel J.; Markman, Arthur B.; Daw, Nathaniel D.

2013-01-01

A number of accounts of human and animal behavior posit the operation of parallel and competing valuation systems in the control of choice behavior. Along these lines, a flexible but computationally expensive model-based reinforcement learning system has been contrasted with a less flexible but more efficient model-free reinforcement learning system. The factors governing which system controls behavior—and under what circumstances—are still unclear. Based on the hypothesis that model-based reinforcement learning requires cognitive resources, we demonstrate that having human decision-makers perform a demanding secondary task engenders increased reliance on a model-free reinforcement learning strategy. Further, we show that across trials, people negotiate this tradeoff dynamically as a function of concurrent executive function demands and their choice latencies reflect the computational expenses of the strategy employed. These results demonstrate that competition between multiple learning systems can be controlled on a trial-by-trial basis by modulating the availability of cognitive resources. PMID:23558545

The Effects of Students' Learning Anxiety and Motivation on the Learning Achievement in the Activity Theory Based Gamified Learning Environment

ERIC Educational Resources Information Center

Su, Chung-Ho

2017-01-01

The advancement of mobile game-based learning has encouraged many related studies, which has enabled students to learn more and faster. To enhance the clinical path of cardiac catheterization learning, this paper has developed a mobile 3D-CCGBLS (3D Cardiac Catheterization Game-Based Learning System) with a learning assessment for cardiac…

The Impact of Team-Based Learning on Nervous System Examination Knowledge of Nursing Students.

PubMed

Hemmati Maslakpak, Masomeh; Parizad, Naser; Zareie, Farzad

2015-12-01

Team-based learning is one of the active learning approaches in which independent learning is combined with small group discussion in the class. This study aimed to determine the impact of team-based learning in nervous system examination knowledge of nursing students. This quasi-experimental study was conducted on 3(rd) grade nursing students, including 5th semester (intervention group) and 6(th) semester (control group). The traditional lecture method and the team-based learning method were used for educating the examination of the nervous system for intervention and control groups, respectively. The data were collected by a test covering 40-questions (multiple choice, matching, gap-filling and descriptive questions) before and after intervention in both groups. Individual Readiness Assurance Test (RAT) and Group Readiness Assurance Test (GRAT) used to collect data in the intervention group. In the end, the collected data were analyzed by SPSS ver. 13 using descriptive and inferential statistical tests. In team-based learning group, mean and standard deviation was 13.39 (4.52) before the intervention, which had been increased to 31.07 (3.20) after the intervention and this increase was statistically significant. Also, there was a statistically significant difference between the scores of RAT and GRAT in team-based learning group. Using team-based learning approach resulted in much better improvement and stability in the nervous system examination knowledge of nursing students compared to traditional lecture method; therefore, this method could be efficiently used as an effective educational approach in nursing education.

Hybrid Multiagent System for Automatic Object Learning Classification

NASA Astrophysics Data System (ADS)

Gil, Ana; de La Prieta, Fernando; López, Vivian F.

The rapid evolution within the context of e-learning is closely linked to international efforts on the standardization of learning object metadata, which provides learners in a web-based educational system with ubiquitous access to multiple distributed repositories. This article presents a hybrid agent-based architecture that enables the recovery of learning objects tagged in Learning Object Metadata (LOM) and provides individualized help with selecting learning materials to make the most suitable choice among many alternatives.

The Role of Corticostriatal Systems in Speech Category Learning.

PubMed

Yi, Han-Gyol; Maddox, W Todd; Mumford, Jeanette A; Chandrasekaran, Bharath

2016-04-01

One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Project-Based Laboratory for Learning Embedded System Design with Industry Support

ERIC Educational Resources Information Center

Lee, Chyi-Shyong; Su, Juing-Huei; Lin, Kuo-En; Chang, Jia-Hao; Lin, Gu-Hong

2010-01-01

A project-based laboratory for learning embedded system design with support from industry is presented in this paper. The aim of this laboratory is to motivate students to learn the building blocks of embedded systems and practical control algorithms by constructing a line-following robot using the quadratic interpolation technique to predict the…

Course Ontology-Based User's Knowledge Requirement Acquisition from Behaviors within E-Learning Systems

ERIC Educational Resources Information Center

Zeng, Qingtian; Zhao, Zhongying; Liang, Yongquan

2009-01-01

User's knowledge requirement acquisition and analysis are very important for a personalized or user-adaptive learning system. Two approaches to capture user's knowledge requirement about course content within an e-learning system are proposed and implemented in this paper. The first approach is based on the historical data accumulated by an…

Ontology-Based Concept Map for Planning a Personalised Learning Path

ERIC Educational Resources Information Center

Chen, Chih-Ming

2009-01-01

Developing personalised web-based learning systems has been an important research issue in e-learning because no fixed learning pathway will be appropriate for all learners. However, most current web-based learning platforms with personalised curriculum sequencing tend to emphasise the learner preferences and interests in relation to personalised…

A Mobile Gamification Learning System for Improving the Learning Motivation and Achievements

ERIC Educational Resources Information Center

Su, C-H.; Cheng, C-H.

2015-01-01

This paper aims to investigate how a gamified learning approach influences science learning, achievement and motivation, through a context-aware mobile learning environment, and explains the effects on motivation and student learning. A series of gamified learning activities, based on MGLS (Mobile Gamification Learning System), was developed and…

Augmenting the senses: a review on sensor-based learning support.

PubMed

Schneider, Jan; Börner, Dirk; van Rosmalen, Peter; Specht, Marcus

2015-02-11

In recent years sensor components have been extending classical computer-based support systems in a variety of applications domains (sports, health, etc.). In this article we review the use of sensors for the application domain of learning. For that we analyzed 82 sensor-based prototypes exploring their learning support. To study this learning support we classified the prototypes according to the Bloom's taxonomy of learning domains and explored how they can be used to assist on the implementation of formative assessment, paying special attention to their use as feedback tools. The analysis leads to current research foci and gaps in the development of sensor-based learning support systems and concludes with a research agenda based on the findings.

Augmenting the Senses: A Review on Sensor-Based Learning Support

PubMed Central

Schneider, Jan; Börner, Dirk; van Rosmalen, Peter; Specht, Marcus

2015-01-01

In recent years sensor components have been extending classical computer-based support systems in a variety of applications domains (sports, health, etc.). In this article we review the use of sensors for the application domain of learning. For that we analyzed 82 sensor-based prototypes exploring their learning support. To study this learning support we classified the prototypes according to the Bloom's taxonomy of learning domains and explored how they can be used to assist on the implementation of formative assessment, paying special attention to their use as feedback tools. The analysis leads to current research foci and gaps in the development of sensor-based learning support systems and concludes with a research agenda based on the findings. PMID:25679313

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

New Functions for Stimulating Learners' Motivation in a Web-Based e-Learning System

ERIC Educational Resources Information Center

Matsuo, Keita; Barolli, Leonard; Xhafa, Fatos; Koyama, Akio; Durresi, Arjan

2008-01-01

Due to the opportunities provided by the Internet, people are taking advantage of e-learning courses and during the last few years enormous research efforts have been dedicated to the development of e-learning systems. So far, many e-learning systems are proposed and used practically. However, in these systems the e-learning completion rate is…

Systems Thinking: A New Lens for Old Problems

ERIC Educational Resources Information Center

Bierema, Laura L.

2003-01-01

This article introduces systems thinking and identifies its implications for practice-based learning and improvement. The article defines systems, identifies fundamental aspects of systems thinking, and provides strategies for creating more practice-based learning environments in medical contexts. (Contains 1 table.)

A Solution-Based Intelligent Tutoring System Integrated with an Online Game-Based Formative Assessment: Development and Evaluation

ERIC Educational Resources Information Center

Hooshyar, Danial; Ahmad, Rodina Binti; Yousefi, Moslem; Fathi, Moein; Abdollahi, Abbas; Horng, Shi-Jinn; Lim, Heuiseok

2016-01-01

Nowadays, intelligent tutoring systems are considered an effective research tool for learning systems and problem-solving skill improvement. Nonetheless, such individualized systems may cause students to lose learning motivation when interaction and timely guidance are lacking. In order to address this problem, a solution-based intelligent…

Internet-based Interactive Construction Management Learning System.

ERIC Educational Resources Information Center

Sawhney, Anil; Mund, Andre; Koczenasz, Jeremy

2001-01-01

Describes a way to incorporate practical content into the construction engineering and management curricula: the Internet-based Interactive Construction Management Learning System, which uses interactive and adaptive learning environments to train students in the areas of construction methods, equipment and processes using multimedia, databases,…

White blood cells identification system based on convolutional deep neural learning networks.

PubMed

Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

2017-11-16

White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

Assessing E-Learning System in Higher Education Institutes: Evidence from Structural Equation Modelling

ERIC Educational Resources Information Center

Ali, Muhammad; Raza, Syed Ali; Qazi, Wasim; Puah, Chin-Hong

2018-01-01

Purpose: This study aims to examine university students' acceptance of e-learning systems in Pakistan. A Web-based learning system is a new form of utilizing technological features. Although, developed countries have initiated and established the concept for e-learning, developing countries require empirical support to implement e-learning.…

Contextualizing Learning Scenarios According to Different Learning Management Systems

ERIC Educational Resources Information Center

Drira, R.; Laroussi, M.; Le Pallec, X.; Warin, B.

2012-01-01

In this paper, we first demonstrate that an instructional design process of Technology Enhanced Learning (TEL) systems based on a Model Driven Approach (MDA) addresses the limits of Learning Technology Standards (LTS), such as SCORM and IMS-LD. Although these standards ensure the interoperability of TEL systems across different Learning Management…

Automatic de-identification of French clinical records: comparison of rule-based and machine-learning approaches.

PubMed

Grouin, Cyril; Zweigenbaum, Pierre

2013-01-01

In this paper, we present a comparison of two approaches to automatically de-identify medical records written in French: a rule-based system and a machine-learning based system using a conditional random fields (CRF) formalism. Both systems have been designed to process nine identifiers in a corpus of medical records in cardiology. We performed two evaluations: first, on 62 documents in cardiology, and on 10 documents in foetopathology - produced by optical character recognition (OCR) - to evaluate the robustness of our systems. We achieved a 0.843 (rule-based) and 0.883 (machine-learning) exact match overall F-measure in cardiology. While the rule-based system allowed us to achieve good results on nominative (first and last names) and numerical data (dates, phone numbers, and zip codes), the machine-learning approach performed best on more complex categories (postal addresses, hospital names, medical devices, and towns). On the foetopathology corpus, although our systems have not been designed for this corpus and despite OCR character recognition errors, we obtained promising results: a 0.681 (rule-based) and 0.638 (machine-learning) exact-match overall F-measure. This demonstrates that existing tools can be applied to process new documents of lower quality.

Mobile Formative Assessment Tool Based on Data Mining Techniques for Supporting Web-Based Learning

ERIC Educational Resources Information Center

Chen, Chih-Ming; Chen, Ming-Chuan

2009-01-01

Current trends clearly indicate that online learning has become an important learning mode. However, no effective assessment mechanism for learning performance yet exists for e-learning systems. Learning performance assessment aims to evaluate what learners learned during the learning process. Traditional summative evaluation only considers final…

Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.

The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networksmore » and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.« less

Neural correlates of reward-based spatial learning in persons with cocaine dependence.

PubMed

Tau, Gregory Z; Marsh, Rachel; Wang, Zhishun; Torres-Sanchez, Tania; Graniello, Barbara; Hao, Xuejun; Xu, Dongrong; Packard, Mark G; Duan, Yunsuo; Kangarlu, Alayar; Martinez, Diana; Peterson, Bradley S

2014-02-01

Dysfunctional learning systems are thought to be central to the pathogenesis of and impair recovery from addictions. The functioning of the brain circuits for episodic memory or learning that support goal-directed behavior has not been studied previously in persons with cocaine dependence (CD). Thirteen abstinent CD and 13 healthy participants underwent MRI scanning while performing a task that requires the use of spatial cues to navigate a virtual-reality environment and find monetary rewards, allowing the functional assessment of the brain systems for spatial learning, a form of episodic memory. Whereas both groups performed similarly on the reward-based spatial learning task, we identified disturbances in brain regions involved in learning and reward in CD participants. In particular, CD was associated with impaired functioning of medial temporal lobe (MTL), a brain region that is crucial for spatial learning (and episodic memory) with concomitant recruitment of striatum (which normally participates in stimulus-response, or habit, learning), and prefrontal cortex. CD was also associated with enhanced sensitivity of the ventral striatum to unexpected rewards but not to expected rewards earned during spatial learning. We provide evidence that spatial learning in CD is characterized by disturbances in functioning of an MTL-based system for episodic memory and a striatum-based system for stimulus-response learning and reward. We have found additional abnormalities in distributed cortical regions. Consistent with findings from animal studies, we provide the first evidence in humans describing the disruptive effects of cocaine on the coordinated functioning of multiple neural systems for learning and memory.

Using an improved association rules mining optimization algorithm in web-based mobile-learning system

NASA Astrophysics Data System (ADS)

Huang, Yin; Chen, Jianhua; Xiong, Shaojun

2009-07-01

Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

Nextgen Navy eLearning Tracking

DTIC Science & Technology

2014-12-01

ELEARNING TRACKING by William E. Miller December 2014 Thesis Advisor: Man-Tak Shing Co-Advisor: Arijit Das THIS PAGE INTENTIONALLY LEFT......Navy’s eLearning (NeL) computer-based learning system relies on a Learning Management System (LMS) for content delivery and tracking learning

Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

NASA Astrophysics Data System (ADS)

Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

2018-03-01

Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

NASA Astrophysics Data System (ADS)

Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

2017-12-01

Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

Efficient Evaluation System for Learning Management Systems

ERIC Educational Resources Information Center

Cavus, Nadire

2009-01-01

A learning management system (LMS) provides the platform for web-based learning environment by enabling the management, delivery, tracking of learning, testing, communication, registration process and scheduling. There are many LMS systems on the market that can be obtained for free or through payment. It has now become an important task to choose…

LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

NASA Astrophysics Data System (ADS)

Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

2013-01-01

As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

Exploring nursing e-learning systems success based on information system success model.

PubMed

Chang, Hui-Chuan; Liu, Chung-Feng; Hwang, Hsin-Ginn

2011-12-01

E-learning is thought of as an innovative approach to enhance nurses' care service knowledge. Extensive research has provided rich information toward system development, courses design, and nurses' satisfaction with an e-learning system. However, a comprehensive view in understanding nursing e-learning system success is an important but less focused-on topic. The purpose of this research was to explore net benefits of nursing e-learning systems based on the updated DeLone and McLean's Information System Success Model. The study used a self-administered questionnaire to collected 208 valid nurses' responses from 21 of Taiwan's medium- and large-scale hospitals that have implemented nursing e-learning systems. The result confirms that the model is sufficient to explore the nurses' use of e-learning systems in terms of intention to use, user satisfaction, and net benefits. However, while the three exogenous quality factors (system quality, information quality, and service quality) were all found to be critical factors affecting user satisfaction, only information quality showed a direct effect on the intention to use. This study provides useful insights for evaluating nursing e-learning system qualities as well as an understanding of nurses' intentions and satisfaction related to performance benefits.

The Study and Design of Adaptive Learning System Based on Fuzzy Set Theory

NASA Astrophysics Data System (ADS)

Jia, Bing; Zhong, Shaochun; Zheng, Tianyang; Liu, Zhiyong

Adaptive learning is an effective way to improve the learning outcomes, that is, the selection of learning content and presentation should be adapted to each learner's learning context, learning levels and learning ability. Adaptive Learning System (ALS) can provide effective support for adaptive learning. This paper proposes a new ALS based on fuzzy set theory. It can effectively estimate the learner's knowledge level by test according to learner's target. Then take the factors of learner's cognitive ability and preference into consideration to achieve self-organization and push plan of knowledge. This paper focuses on the design and implementation of domain model and user model in ALS. Experiments confirmed that the system providing adaptive content can effectively help learners to memory the content and improve their comprehension.

The Multimedia-Based Learning System Improved Cognitive Skills and Motivation of Disabled Children with a Very High Rate

ERIC Educational Resources Information Center

Saad, Sawsan; Dandashi, Amal; Aljaam, Jihad M.; Saleh, Moataz

2015-01-01

A multimedia-based learning system to teach children with intellectual disabilities (ID) the basic living and science concepts is proposed. The tutorials' development is pedagogically based on Mayer's Cognitive Theory of Multimedia Learning combined with Skinner's Operant Conditioning Model. Two types of tutorials are proposed. In the first type;…

Effects of Anxiety Levels on Learning Performance and Gaming Performance in Digital Game-Based Learning

ERIC Educational Resources Information Center

Yang, J. C.; Lin, M. Y. D.; Chen, S. Y.

2018-01-01

Anxiety plays an influential role in foreign language learning. However, a lack of attention was paid to examining the effects of anxiety levels on learning performance and gaming performance in digital game-based learning. To this end, this study developed a game-based English learning system and investigated how different levels of anxiety…

Impact of audio narrated animation on students' understanding and learning environment based on gender

NASA Astrophysics Data System (ADS)

Nasrudin, Ajeng Ratih; Setiawan, Wawan; Sanjaya, Yayan

2017-05-01

This study is titled the impact of audio narrated animation on students' understanding in learning humanrespiratory system based on gender. This study was conducted in eight grade of junior high school. This study aims to investigate the difference of students' understanding and learning environment at boys and girls classes in learning human respiratory system using audio narrated animation. Research method that is used is quasy experiment with matching pre-test post-test comparison group design. The procedures of study are: (1) preliminary study and learning habituation using audio narrated animation; (2) implementation of learning using audio narrated animation and taking data; (3) analysis and discussion. The result of analysis shows that there is significant difference on students' understanding and learning environment at boys and girls classes in learning human respiratory system using audio narrated animation, both in general and specifically in achieving learning indicators. The discussion related to the impact of audio narrated animation, gender characteristics, and constructivist learning environment. It can be concluded that there is significant difference of students' understanding at boys and girls classes in learning human respiratory system using audio narrated animation. Additionally, based on interpretation of students' respond, there is the difference increment of agreement level in learning environment.

Dynamic Interactive Learning Systems

ERIC Educational Resources Information Center

Sabry, Khaled; Barker, Jeff

2009-01-01

This paper reviews and discusses the notions of interactivity and dynamicity of learning systems in relation to information technologies and design principles that can contribute to interactive and dynamic learning. It explores the concept of dynamic interactive learning systems based on the emerging generation of information as part of a…

Two spatiotemporally distinct value systems shape reward-based learning in the human brain.

PubMed

Fouragnan, Elsa; Retzler, Chris; Mullinger, Karen; Philiastides, Marios G

2015-09-08

Avoiding repeated mistakes and learning to reinforce rewarding decisions is critical for human survival and adaptive actions. Yet, the neural underpinnings of the value systems that encode different decision-outcomes remain elusive. Here coupling single-trial electroencephalography with simultaneously acquired functional magnetic resonance imaging, we uncover the spatiotemporal dynamics of two separate but interacting value systems encoding decision-outcomes. Consistent with a role in regulating alertness and switching behaviours, an early system is activated only by negative outcomes and engages arousal-related and motor-preparatory brain structures. Consistent with a role in reward-based learning, a later system differentially suppresses or activates regions of the human reward network in response to negative and positive outcomes, respectively. Following negative outcomes, the early system interacts and downregulates the late system, through a thalamic interaction with the ventral striatum. Critically, the strength of this coupling predicts participants' switching behaviour and avoidance learning, directly implicating the thalamostriatal pathway in reward-based learning.

Concept Based Approach for Adaptive Personalized Course Learning System

ERIC Educational Resources Information Center

Salahli, Mehmet Ali; Özdemir, Muzaffer; Yasar, Cumali

2013-01-01

One of the most important factors for improving the personalization aspects of learning systems is to enable adaptive properties to them. The aim of the adaptive personalized learning system is to offer the most appropriate learning path and learning materials to learners by taking into account their profiles. In this paper, a new approach to…

Emotional learning and the development of differential moralities: implications from research on psychopathy.

PubMed

Blair, R James R; White, Stuart F; Meffert, Harma; Hwang, Soonjo

2013-09-01

In this paper, we will argue that (1) four classes of norm can be distinguished from a neuro-cognitive perspective; (2) learning the prohibitive power of these norms relies on relatively independent emotional systems; (3) individuals with psychopathy show selective impairment for one of these emotional learning systems and two classes of norm: care based and justice based; and (4) while emotional learning systems are necessary for appropriate moral development/reasoning, they are not sufficient for moral development/reasoning.

Using Knowledge-Based Systems to Support Learning of Organizational Knowledge: A Case Study

NASA Technical Reports Server (NTRS)

Cooper, Lynne P.; Nash, Rebecca L.; Phan, Tu-Anh T.; Bailey, Teresa R.

2003-01-01

This paper describes the deployment of a knowledge system to support learning of organizational knowledge at the Jet Propulsion Laboratory (JPL), a US national research laboratory whose mission is planetary exploration and to 'do what no one has done before.' Data collected over 19 weeks of operation were used to assess system performance with respect to design considerations, participation, effectiveness of communication mechanisms, and individual-based learning. These results are discussed in the context of organizational learning research and implications for practice.

Comparing Learning Outcomes of Video-Based E-Learning with Face-to-Face Lectures of Agricultural Engineering Courses in Korean Agricultural High Schools

ERIC Educational Resources Information Center

Park, Sung Youl; Kim, Soo-Wook; Cha, Seung-Bong; Nam, Min-Woo

2014-01-01

This study investigated the effectiveness of e-learning by comparing the learning outcomes in conventional face-to-face lectures and e-learning methods. Two video-based e-learning contents were developed based on the rapid prototyping model and loaded onto the learning management system (LMS), which was available at http://www.greenehrd.com.…

The Evolution of Electronic Pedagogy in an Outcome Based Learning Environment: Learning, Teaching, and the Culture of Technology at California's Newest University--CSU Monterey Bay.

ERIC Educational Resources Information Center

Baldwin, George

California State University Monterey Bay (CSUMB) is the newest university in the CSU system. CSUMB's vision statement distinguishes the institution from others in the system by promoting learning paradigms of Outcome Based Education (OBE) and communication technologies of distributed learning (DL). Faculty are committed to the experimental use of…

Development of an Adaptive Learning System with Two Sources of Personalization Information

ERIC Educational Resources Information Center

Tseng, J. C. R.; Chu, H. C.; Hwang, G. J.; Tsai, C. C.

2008-01-01

Previous research of adaptive learning mainly focused on improving student learning achievements based only on single-source of personalization information, such as learning style, cognitive style or learning achievement. In this paper, an innovative adaptive learning approach is proposed by basing upon two main sources of personalization…

Dynamic Learning Style Prediction Method Based on a Pattern Recognition Technique

ERIC Educational Resources Information Center

Yang, Juan; Huang, Zhi Xing; Gao, Yue Xiang; Liu, Hong Tao

2014-01-01

During the past decade, personalized e-learning systems and adaptive educational hypermedia systems have attracted much attention from researchers in the fields of computer science Aand education. The integration of learning styles into an intelligent system is a possible solution to the problems of "learning deviation" and…

Using Mobile Devices to Enhance the Interactive Learning for Spatial Geometry

ERIC Educational Resources Information Center

Chang, Kuo-En; Wu, Lin-Jung; Lai, Shing-Chuang; Sung, Yao-Ting

2016-01-01

The purpose of this research is to develop a hands-on spatial geometry learning system to facilitate the learning of geometry. The development of this system was based on Duval's four critical elements of geometric learning: perceptual apprehension, sequential apprehension, operative apprehension, and discursive apprehension. The system offers…

Multiplatform E-Learning Systems and Technologies: Mobile Devices for Ubiquitous ICT-Based Education

ERIC Educational Resources Information Center

Goh, Tiong Thye, Ed.

2010-01-01

Multiplatform e-learning systems are emerging technologies that provide integrated learning content to various accessing devices. This book addresses technical challenges, design frameworks, and development experiences of the future that integrate multiple mobile devices into a single multiplatform e-learning system. With expert international…

Using Game-Based Cooperative Learning to Improve Learning Motivation: A Study of Online Game Use in an Operating Systems Course

ERIC Educational Resources Information Center

Jong, Bin-Shyan; Lai, Chien-Hung; Hsia, Yen-Teh; Lin, Tsong-Wuu; Lu, Cheng-Yu

2013-01-01

Many researchers have studied the use of game-based learning. Game-based learning takes many forms, including virtual reality, role playing, and performing tasks. For students to learn specific course content, it is important that the selected game be suited to the course. Thus far, no studies have investigated the use of game-based cooperative…

A simple computational algorithm of model-based choice preference.

PubMed

Toyama, Asako; Katahira, Kentaro; Ohira, Hideki

2017-08-01

A broadly used computational framework posits that two learning systems operate in parallel during the learning of choice preferences-namely, the model-free and model-based reinforcement-learning systems. In this study, we examined another possibility, through which model-free learning is the basic system and model-based information is its modulator. Accordingly, we proposed several modified versions of a temporal-difference learning model to explain the choice-learning process. Using the two-stage decision task developed by Daw, Gershman, Seymour, Dayan, and Dolan (2011), we compared their original computational model, which assumes a parallel learning process, and our proposed models, which assume a sequential learning process. Choice data from 23 participants showed a better fit with the proposed models. More specifically, the proposed eligibility adjustment model, which assumes that the environmental model can weight the degree of the eligibility trace, can explain choices better under both model-free and model-based controls and has a simpler computational algorithm than the original model. In addition, the forgetting learning model and its variation, which assume changes in the values of unchosen actions, substantially improved the fits to the data. Overall, we show that a hybrid computational model best fits the data. The parameters used in this model succeed in capturing individual tendencies with respect to both model use in learning and exploration behavior. This computational model provides novel insights into learning with interacting model-free and model-based components.

A Study of the Design and Implementation of the ASR-Based iCASL System with Corrective Feedback to Facilitate English Learning

ERIC Educational Resources Information Center

Wang, Yi-Hsuan; Young, Shelley Shwu-Ching

2014-01-01

The purpose of the study is to explore and describe how to implement a pedagogical ASR-based intelligent computer-assisted speaking learning (iCASL) system to support adult learners with a private, flexible and individual learning environment to practice English pronunciation. The iCASL system integrates multiple levels of corrective feedback and…

On the Use of Adaptive Instructional Images Based on the Sequential-Global Dimension of the Felder-Silverman Learning Style Theory

ERIC Educational Resources Information Center

Filippidis, Stavros K.; Tsoukalas, Ioannis A.

2009-01-01

An adaptive educational system that uses adaptive presentation is presented. In this system fragments of different images present the same content and the system can choose the one most relevant to the user based on the sequential-global dimension of Felder-Silverman's learning style theory. In order to retrieve the learning style of each student…

An Efficacious Measurement of Learning Initiatives: E-Learning Systems, Learning-Organization Culture, Knowledge Creation, and Innovativeness

ERIC Educational Resources Information Center

Grundhoefer, Raymie

2013-01-01

The purpose of this research is twofold: (a) develop a validated measure for learning initiatives based on knowledge-creation theory and (b) conduct a quantitative study to investigate the relationships between electronic learning systems, learning-organization culture, efficacious knowledge creation (EKC), and innovativeness. Although Cheng-Chang…

Design of a Microlecture Mobile Learning System Based on Smartphone and Web Platforms

ERIC Educational Resources Information Center

Wen, Chuanxue; Zhang, Junfei

2015-01-01

This paper first analyzes the concept and features of microlecture, mobile learning, and ubiquitous learning, then presents the combination of microlecture and mobile learning, to propose a novel way of micro-learning through mobile terminals. Details are presented of a microlecture mobile learning system (MMLS) that can support multiplatforms,…

Measuring Learner's Performance in E-Learning Recommender Systems

ERIC Educational Resources Information Center

Ghauth, Khairil Imran; Abdullah, Nor Aniza

2010-01-01

A recommender system is a piece of software that helps users to identify the most interesting and relevant learning items from a large number of items. Recommender systems may be based on collaborative filtering (by user ratings), content-based filtering (by keywords), and hybrid filtering (by both collaborative and content-based filtering).…

Comparison of Computer-Based Versus Counselor-Based Occupational Information Systems with Disadvantaged Vocational Students

ERIC Educational Resources Information Center

Maola, Joseph; Kane, Gary

1976-01-01

Subjects, who were Occupational Work Experience students, were randomly assigned to individual guidance from either a computerized occupational information system, to a counselor-based information system or to a control group. Results demonstrate a hierarchical learning effect: The computer group learned more than the counseled group, which…

Towards Next Generation Activity-Based Learning Systems

ERIC Educational Resources Information Center

Sampson, Demetrios G.; Karampiperis, Pythagoras

2006-01-01

The need for e-learning systems that support a diverse set of pedagogical requirements has been identified as an important issue in web-based education. Until now, significant research and development effort has been devoted to aiming towards web-based educational systems tailored to specific pedagogical approaches. The most advanced of them are…

Design, Analysis and User Acceptance of Architectural Design Education in Learning System Based on Knowledge Management Theory

ERIC Educational Resources Information Center

Wu, Yun-Wu; Lin, Yu-An; Wen, Ming-Hui; Perng, Yeng-Hong; Hsu, I-Ting

2016-01-01

The major purpose of this study is to develop an architectural design knowledge management learning system with corresponding learning activities to help the students have meaningful learning and improve their design capability in their learning process. Firstly, the system can help the students to obtain and share useful knowledge. Secondly,…

A Distance Instructional System with Learning Performance Evaluation Mechanism: Moodle-Based Educational System Design

ERIC Educational Resources Information Center

Lee, Ying-Chen; Terashima, Nobuyoshi

2012-01-01

In this paper, a Moodle-based educational system has been constructed by providing friendly interface to fit most students in e-learning. For the website implementation, the authors take the course "Multimedia Implementation Using JAVA" as a case study. From the modified Moodle-based educational system, the browsing time of each web page for…

Implementing Practical Based Courses under Open and Distance Learning System: A Study of the Perception of Learners and Counsellors

ERIC Educational Resources Information Center

Basantia, Tapan Kumar

2018-01-01

Implementing practical based courses under Open and Distance Learning (ODL) system is a very difficult and challenging task as the teaching of practical based courses involves intensive practical work. For removing the difficulties and challenges in implementing the practical based courses under ODL system, there is a need to study the existing…

Indirect learning control for nonlinear dynamical systems

NASA Technical Reports Server (NTRS)

Ryu, Yeong Soon; Longman, Richard W.

1993-01-01

In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.

Towards Greater Learner Control: Web Supported Project-Based Learning

ERIC Educational Resources Information Center

Guthrie, Cameron

2010-01-01

Project-based learning has been suggested as an appropriate pedagogy to prepare students in information systems for the realities of the business world. Web-based resources have been used to support such pedagogy with mixed results. The paper argues that the design of web-based learning support to cater to different learning styles may give…

Development of an Inquiry-Based Learning Support System Based on an Intelligent Knowledge Exploration Approach

ERIC Educational Resources Information Center

Wu, Ji-Wei; Tseng, Judy C. R.; Hwang, Gwo-Jen

2015-01-01

Inquiry-Based Learning (IBL) is an effective approach for promoting active learning. When inquiry-based learning is incorporated into instruction, teachers provide guiding questions for students to actively explore the required knowledge in order to solve the problems. Although the World Wide Web (WWW) is a rich knowledge resource for students to…

Utah Work-Based Learning Manual.

ERIC Educational Resources Information Center

Utah State Office of Education, Salt Lake City.

This document presents materials to assist Utah school personnel who are initiating, implementing, or improving work-based learning opportunities for students. The document presents detailed guidelines for creating and maintaining work-based learning systems in schools and resource materials for improving existing work-based opportunities. Formal…

Delivery of Learning Knowledge Objects Using Fuzzy Clustering

ERIC Educational Resources Information Center

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…

Mining Formative Evaluation Rules Using Web-Based Learning Portfolios for Web-Based Learning Systems

ERIC Educational Resources Information Center

Chen, Chih-Ming; Hong, Chin-Ming; Chen, Shyuan-Yi; Liu, Chao-Yu

2006-01-01

Learning performance assessment aims to evaluate what knowledge learners have acquired from teaching activities. Objective technical measures of learning performance are difficult to develop, but are extremely important for both teachers and learners. Learning performance assessment using learning portfolios or web server log data is becoming an…

Validating the Satisfaction and Continuance Intention of E-Learning Systems: Combining TAM and IS Success Models

ERIC Educational Resources Information Center

Lin, Tung-Cheng; Chen, Ching-Jen

2012-01-01

Many e-learning studies have evaluated learning attitudes and behaviors, based on TAM. However, a successful e-learning system (ELS) should take both system and information quality into account by applying ISM developed by Delone and McLean. In addition, the acceptance for information system depends on the perceived usefulness and ease of use…

Am I Extravert or Introvert? Considering the Personality Effect toward e-Learning System

ERIC Educational Resources Information Center

Al-Dujaily, Amal; Kim, Jieun; Ryu, Hokyoung

2013-01-01

A concern of computer-based learning system design is how to accommodate learners' individual differences during learning activities. Previous research suggests that adaptive e-learning systems can effectively address such individual differences and, consequently, they enable more directed tutoring via computer-assisted instruction. In this paper,…

Mind map learning for advanced engineering study: case study in system dynamics

NASA Astrophysics Data System (ADS)

Woradechjumroen, Denchai

2018-01-01

System Dynamics (SD) is one of the subjects that were use in learning Automatic Control Systems in dynamic and control field. Mathematical modelling and solving skills of students for engineering systems are expecting outcomes of the course which can be further used to efficiently study control systems and mechanical vibration; however, the fundamental of the SD includes strong backgrounds in Dynamics and Differential Equations, which are appropriate to the students in governmental universities that have strong skills in Mathematics and Scientifics. For private universities, students are weak in the above subjects since they obtained high vocational certificate from Technical College or Polytechnic School, which emphasize the learning contents in practice. To enhance their learning for improving their backgrounds, this paper applies mind maps based problem based learning to relate the essential relations of mathematical and physical equations. With the advantages of mind maps, each student is assigned to design individual mind maps for self-leaning development after they attend the class and learn overall picture of each chapter from the class instructor. Four problems based mind maps learning are assigned to each student. Each assignment is evaluated via mid-term and final examinations, which are issued in terms of learning concepts and applications. In the method testing, thirty students are tested and evaluated via student learning backgrounds in the past. The result shows that well-design mind maps can improve learning performance based on outcome evaluation. Especially, mind maps can reduce time-consuming and reviewing for Mathematics and Physics in SD significantly.

Antecedences to Continued Intentions of Adopting E-Learning System in Blended Learning Instruction: A Contingency Framework Based on Models of Information System Success and Task-Technology Fit

ERIC Educational Resources Information Center

Lin, Wen-Shan; Wang, Chun-Hsien

2012-01-01

The objective of this study is to propose a research framework that investigates the relation between perceived fit and system factors that can motivate learners in continuing utilizing an e-learning system in blended learning instruction. As learners have the face-to-face learning opportunity in interacting with lecturers, the study aims at…

Content-based VLE designs improve learning efficiency in constructivist statistics education.

PubMed

Wessa, Patrick; De Rycker, Antoon; Holliday, Ian Edward

2011-01-01

We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE) in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses), which required us to develop a specific-purpose Statistical Learning Environment (SLE) based on Reproducible Computing and newly developed Peer Review (PR) technology. The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under investigation. The findings demonstrate that a content-based design outperforms the traditional VLE-based design.

Two Stages Cooperative Learning by Ability Indicators

ERIC Educational Resources Information Center

Wu, YuLung

2013-01-01

The teaching system in Taiwan is currently based on large classes where teachers cannot control student situations totally. In E-Learning System, a teacher who reviews a student's learning situation must examine the students' learning records according to different items, and further organize and define the students' current learning situations,…

An Architecture for Online Laboratory E-Learning System

ERIC Educational Resources Information Center

Duan, Bing; Hosseini, Habib Mir M.; Ling, Keck Voon; Gay, Robert Kheng Leng

2006-01-01

Internet-based learning systems, or e-learning, are widely available in institutes, universities, and industrial companies, hosting regular or continuous education programs. The dream of teaching and learning from anywhere and at anytime becomes a reality due to the construction of e-learning infrastructure. Traditional teaching materials and…

An Analytics-Based Approach to Managing Cognitive Load by Using Log Data of Learning Management Systems and Footprints of Social Media

ERIC Educational Resources Information Center

Yen, Cheng-Huang; Chen, I-Chuan; Lai, Su-Chun; Chuang, Yea-Ru

2015-01-01

Traces of learning behaviors generally provide insights into learners and the learning processes that they employ. In this article, a learning-analytics-based approach is proposed for managing cognitive load by adjusting the instructional strategies used in online courses. The technology-based learning environment examined in this study involved a…

Machine Learning Control For Highly Reconfigurable High-Order Systems

DTIC Science & Technology

2015-01-02

develop and flight test a Reinforcement Learning based approach for autonomous tracking of ground targets using a fixed wing Unmanned...Reinforcement Learning - based algorithms are developed for learning agents’ time dependent dynamics while also learning to control them. Three algorithms...to a wide range of engineering- based problems . Implementation of these solutions, however, is often complicated by the hysteretic, non-linear,

Learning Object Retrieval and Aggregation Based on Learning Styles

ERIC Educational Resources Information Center

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…

The curse of planning: dissecting multiple reinforcement-learning systems by taxing the central executive.

PubMed

Otto, A Ross; Gershman, Samuel J; Markman, Arthur B; Daw, Nathaniel D

2013-05-01

A number of accounts of human and animal behavior posit the operation of parallel and competing valuation systems in the control of choice behavior. In these accounts, a flexible but computationally expensive model-based reinforcement-learning system has been contrasted with a less flexible but more efficient model-free reinforcement-learning system. The factors governing which system controls behavior-and under what circumstances-are still unclear. Following the hypothesis that model-based reinforcement learning requires cognitive resources, we demonstrated that having human decision makers perform a demanding secondary task engenders increased reliance on a model-free reinforcement-learning strategy. Further, we showed that, across trials, people negotiate the trade-off between the two systems dynamically as a function of concurrent executive-function demands, and people's choice latencies reflect the computational expenses of the strategy they employ. These results demonstrate that competition between multiple learning systems can be controlled on a trial-by-trial basis by modulating the availability of cognitive resources.

Recommendation System for Adaptive Learning.

PubMed

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-01-01

An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

ERIC Educational Resources Information Center

Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

2012-01-01

This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

An Adaptive E-Learning System Based on Students' Learning Styles: An Empirical Study

ERIC Educational Resources Information Center

Drissi, Samia; Amirat, Abdelkrim

2016-01-01

Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia.…

Preserved complex emotion-based learning in amnesia.

PubMed

Turnbull, Oliver H; Evans, Cathryn E Y

2006-01-01

An important role for emotion in decision-making has recently been highlighted by disruptions in problem solving abilities after lesion to the frontal lobes. Such complex decision-making skills appear to be based on a class of memory ability (emotion-based learning) that may be anatomically independent of hippocampally mediated episodic memory systems. There have long been reports of intact emotion-based learning in amnesia, arguably dating back to the classic report of Claparede. However, all such accounts relate to relatively simple patterns of emotional valence learning, rather than the more complex contingency patterns of emotional experience, which characterise everyday life. A patient, SL, who had a profound anterograde amnesia following posterior cerebral artery infarction, performed a measure of complex emotion-based learning (the Iowa Gambling Task) on three separate occasions. Despite his severe episodic memory impairment, he showed normal levels of performance on the Gambling Task, at levels comparable or better than controls-including learning that persisted across substantial periods of time (weeks). Thus, emotion-based learning systems appear able to encode, and sustain, more sophisticated patterns of valence learning than have previously been reported.

A Cognitive Approach to e-Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greitzer, Frank L.; Rice, Douglas M.; Eaton, Sharon L.

2003-12-01

Like traditional classroom instruction, distributed learning derives from passive training paradigms. Just as student-centered classroom teaching methods have been applied over several decades of classroom instruction, interactive approaches have been encouraged for distributed learning. While implementation of multimedia-based training features may appear to produce active learning, sophisticated use of multimedia features alone does not necessarily enhance learning. This paper describes the results of applying cognitive science principles to enhance learning in a student-centered, distributed learning environment, and lessons learned in developing and delivering this training. Our interactive, scenario-based approach exploits multimedia technology within a systematic, cognitive framework for learning. Themore » basis of the application of cognitive principles is the innovative use of multimedia technology to implement interaction elements. These simple multimedia interactions, which are used to support new concepts, are later combined with other interaction elements to create more complex, integrated practical exercises. This technology-based approach may be applied in a variety of training and education contexts, but is especially well suited for training of equipment operators and maintainers. For example, it has been used in a sustainment training application for the United States Army's Combat Support System Automated Information System Interface (CAISI). The CAISI provides a wireless communications capability that allows various logistics systems to communicate across the battlefield. Based on classroom training material developed by the CAISI Project Office, the Pacific Northwest National Laboratory designed and developed an interactive, student-centered distributed-learning application for CAISI operators and maintainers. This web-based CAISI training system is also distributed on CD media for use on individual computers, and material developed for the computer-based course can be used in the classroom. In addition to its primary role in sustainment training, this distributed learning course can complement or replace portions of the classroom instruction, thus supporting a blended learning solution.« less

Automated Inattention and Fatigue Detection System in Distance Education for Elementary School Students

ERIC Educational Resources Information Center

Hwang, Kuo-An; Yang, Chia-Hao

2009-01-01

Most courses based on distance learning focus on the cognitive domain of learning. Because students are sometimes inattentive or tired, they may neglect the attention goal of learning. This study proposes an auto-detection and reinforcement mechanism for the distance-education system based on the reinforcement teaching strategy. If a student is…

Progressive Assessment of Student Engagement with Web-Based Guided Learning

ERIC Educational Resources Information Center

Katuk, Norliza

2013-01-01

Purpose: The purpose of this research is to investigate student engagement in guided web-based learning systems. It looks into students' engagement and their behavioral patterns in two types of guided learning systems (i.e. a fully- and a partially-guided). The research also aims to demonstrate how the engagement evolves from the…

A Community-Based Research Approach to Develop an Educational Web Portal

ERIC Educational Resources Information Center

Preiser-Houy, Lara; Navarrete, Carlos J.

2011-01-01

Service-learning projects are becoming more prevalent in Information Systems education. This study explores the use of community-based research, a special kind of a service-learning strategy, in an Information Systems web development course. The paper presents a case study of a service-learning project to develop an educational web portal for a…

Effect of Bayesian Student Modeling on Academic Achievement in Foreign Language Teaching (University Level English Preparatory School Example)

ERIC Educational Resources Information Center

Aslan, Burak Galip; Öztürk, Özlem; Inceoglu, Mustafa Murat

2014-01-01

Considering the increasing importance of adaptive approaches in CALL systems, this study implemented a machine learning based student modeling middleware with Bayesian networks. The profiling approach of the student modeling system is based on Felder and Silverman's Learning Styles Model and Felder and Soloman's Index of Learning Styles…

Perceptions of the Effectiveness of System Dynamics-Based Interactive Learning Environments: An Empirical Study

ERIC Educational Resources Information Center

Qudrat-Ullah, Hassan

2010-01-01

The use of simulations in general and of system dynamics simulation based interactive learning environments (SDILEs) in particular is well recognized as an effective way of improving users' decision making and learning in complex, dynamic tasks. However, the effectiveness of SDILEs in classrooms has rarely been evaluated. This article describes…

An Autonomous Mobile Agent-Based Distributed Learning Architecture: A Proposal and Analytical Analysis

ERIC Educational Resources Information Center

Ahmed, Iftikhar; Sadeq, Muhammad Jafar

2006-01-01

Current distance learning systems are increasingly packing highly data-intensive contents on servers, resulting in the congestion of network and server resources at peak service times. A distributed learning system based on faded information field (FIF) architecture that employs mobile agents (MAs) has been proposed and simulated in this work. The…

Using a Problem-Based Learning Approach to Teach an Intelligent Systems Course

ERIC Educational Resources Information Center

Cheong, France

2008-01-01

While delivering the Intelligent Systems course, an elective course in the Master of Business Information Technology program at RMIT University, it was felt that there was a learning issue as students' learning seemed to be superficial. This perception was based on the questions students asked in class and the mechanical attitude they adopted…

A Computer-Assisted Learning Model Based on the Digital Game Exponential Reward System

ERIC Educational Resources Information Center

Moon, Man-Ki; Jahng, Surng-Gahb; Kim, Tae-Yong

2011-01-01

The aim of this research was to construct a motivational model which would stimulate voluntary and proactive learning using digital game methods offering players more freedom and control. The theoretical framework of this research lays the foundation for a pedagogical learning model based on digital games. We analyzed the game reward system, which…

The MORPG-Based Learning System for Multiple Courses: A Case Study on Computer Science Curriculum

ERIC Educational Resources Information Center

Liu, Kuo-Yu

2015-01-01

This study aimed at developing a Multiplayer Online Role Playing Game-based (MORPG) Learning system which enabled instructors to construct a game scenario and manage sharable and reusable learning content for multiple courses. It used the curriculum of "Introduction to Computer Science" as a study case to assess students' learning…

Effective collaborative learning in biomedical education using a web-based infrastructure.

PubMed

Wu, Yunfeng; Zheng, Fang; Cai, Suxian; Xiang, Ning; Zhong, Zhangting; He, Jia; Xu, Fang

2012-01-01

This paper presents a feature-rich web-based system used for biomedical education at the undergraduate level. With the powerful groupware features provided by the wiki system, the instructors are able to establish a community-centered mentoring environment that capitalizes on local expertise to create a sense of online collaborative learning among students. The web-based infrastructure can help the instructors effectively organize and coordinate student research projects, and the groupware features may support the interactive activities, such as interpersonal communications and data sharing. The groupware features also provide the web-based system with a wide range of additional ways of organizing collaboratively developed materials, which makes it become an effective tool for online active learning. Students are able to learn the ability to work effectively in teams, with an improvement of project management, design collaboration, and technical writing skills. With the fruitful outcomes in recent years, it is positively thought that the web-based collaborative learning environment can perform an excellent shift away from the conventional instructor-centered teaching to community- centered collaborative learning in the undergraduate education.

Enhancing Collaborative Learning in Web 2.0-Based E-Learning Systems: A Design Framework for Building Collaborative E-Learning Contents

ERIC Educational Resources Information Center

El Mhouti, Abderrahim; Nasseh, Azeddine; Erradi, Mohamed; Vasquèz, José Marfa

2017-01-01

Today, the implication of Web 2.0 technologies in e-learning allows envisaging new teaching and learning forms, advocating an important place to the collaboration and social interaction. However, in e-learning systems, learn in a collaborative way is not always so easy because one of the difficulties when arranging e-learning courses can be that…

SVM and PCA Based Learning Feature Classification Approaches for E-Learning System

ERIC Educational Resources Information Center

Khamparia, Aditya; Pandey, Babita

2018-01-01

E-learning and online education has made great improvements in the recent past. It has shifted the teaching paradigm from conventional classroom learning to dynamic web based learning. Due to this, a dynamic learning material has been delivered to learners, instead ofstatic content, according to their skills, needs and preferences. In this…

Conceptualizing Debates in Learning and Educational Research: Toward a Complex Systems Conceptual Framework of Learning

ERIC Educational Resources Information Center

Jacobson, Michael J.; Kapur, Manu; Reimann, Peter

2016-01-01

This article proposes a conceptual framework of learning based on perspectives and methodologies being employed in the study of complex physical and social systems to inform educational research. We argue that the contexts in which learning occurs are complex systems with elements or agents at different levels--including neuronal, cognitive,…

Factors that Influence Acceptance of Web-Based E-Learning Systems for the In-Service Education of Junior High School Teachers in Taiwan

ERIC Educational Resources Information Center

Chen, Hong-Ren; Tseng, Hsiao-Fen

2012-01-01

Web-based e-learning is not restricted by time or place and can provide teachers with a learning environment that is flexible and convenient, enabling them to efficiently learn, quickly develop their professional expertise, and advance professionally. Many research reports on web-based e-learning have neglected the role of the teacher's…

Gemini Observatory base facility operations: systems engineering process and lessons learned

NASA Astrophysics Data System (ADS)

Serio, Andrew; Cordova, Martin; Arriagada, Gustavo; Adamson, Andy; Close, Madeline; Coulson, Dolores; Nitta, Atsuko; Nunez, Arturo

2016-08-01

Gemini North Observatory successfully began nighttime remote operations from the Hilo Base Facility control room in November 2015. The implementation of the Gemini North Base Facility Operations (BFO) products was a great learning experience for many of our employees, including the author of this paper, the BFO Systems Engineer. In this paper we focus on the tailored Systems Engineering processes used for the project, the various software tools used in project support, and finally discuss the lessons learned from the Gemini North implementation. This experience and the lessons learned will be used both to aid our implementation of the Gemini South BFO in 2016, and in future technical projects at Gemini Observatory.

E-Learning Personalization Based on Hybrid Recommendation Strategy and Learning Style Identification

ERIC Educational Resources Information Center

Klasnja-Milicevic, Aleksandra; Vesin, Boban; Ivanovic, Mirjana; Budimac, Zoran

2011-01-01

Personalized learning occurs when e-learning systems make deliberate efforts to design educational experiences that fit the needs, goals, talents, and interests of their learners. Researchers had recently begun to investigate various techniques to help teachers improve e-learning systems. In this paper, we describe a recommendation module of a…

A resident conference for systems-based practice and practice-based learning.

PubMed

Sultana, Carmen J; Baxter, Jason K

2011-02-01

Improving patient safety and quality of care is part of systems-based practice and practice-based learning for residents. We expanded our obstetrics and gynecology department's regularly scheduled morbidity and mortality conferences to teach quality assurance concepts based on patient care on obstetrics and gynecology fourth-year resident rotations. Obstetrics and gynecology fourth-year residents on one of the two rotations each presented and analyzed a systems-based problem they encountered during patient care. They used an online learning module and proposed solutions, many of which were effectively implemented. Over 5 years, case presentations from 33 conferences were available with problems identified in emergency preparedness, coordination of care, scheduling and supervision, communication, medical practice, documentation, and lack of equipment or facilities. Twenty-two of the suggested solutions were partially or totally implemented. Barriers to implementation were identified. In conclusion, a conference presentation by fourth-year residents can identify patient safety problems, aid in their resolution, and suggest changes to patient care while teaching the principles of systems-based practice and practice-based learning.

Applications of Machine Learning and Rule Induction,

DTIC Science & Technology

1995-02-15

An important area of application for machine learning is in automating the acquisition of knowledge bases required for expert systems. In this paper...we review the major paradigms for machine learning , including neural networks, instance-based methods, genetic learning, rule induction, and analytic

Meta-Assessment in a Project-Based Systems Engineering Course

ERIC Educational Resources Information Center

Wengrowicz, Niva; Dori, Yehudit Judy; Dori, Dov

2017-01-01

Project-based learning (PBL) facilitates significant learning, but it poses a major assessment challenge for assessing individual content knowledge. We developed and implemented an assessment approach and tool for a mandatory undergraduate systems engineering PBL-based course. We call this type of assessment "student-oriented"…

Multi-Agent Framework for Virtual Learning Spaces.

ERIC Educational Resources Information Center

Sheremetov, Leonid; Nunez, Gustavo

1999-01-01

Discussion of computer-supported collaborative learning, distributed artificial intelligence, and intelligent tutoring systems focuses on the concept of agents, and describes a virtual learning environment that has a multi-agent system. Describes a model of interactions in collaborative learning and discusses agents for Web-based virtual…

Interactive and collaborative learning in the classroom at the medical school Automated response systems and team-based learning.

PubMed

Nasr, Rihab; Antoun, Jumana; Sabra, Ramzi; Zgheib, Nathalie K

2016-01-01

There has been a pedagogic shift in higher education from the traditional teacher centered to the student centered approach in teaching, necessitating a change in the role of the teacher from a supplier of information to passive receptive students into a more facilitative role. Active learning activities are based on various learning theories such as self-directed learning, cooperative learning and adult learning. There exist many instructional activities that enhance active and collaborative learning. The aim of this manuscript is to describe two methods of interactive and collaborative learning in the classroom, automated response systems (ARS) and team-based learning (TBL), and to list some of their applications and advantages. The success of these innovative teaching and learning methods at a large scale depends on few elements, probably the most important of which is the support of the higher administration and leadership in addition to the availability of “champions” who are committed to lead the change.

Challenge Study: A Project-Based Learning on a Wireless Communication System at Technical High School

ERIC Educational Resources Information Center

Terasawa, Ikuo

2016-01-01

The challenge study is a project based learning curriculum at Technical High School aimed at the construction of a wireless communication system. The first period was engineering issues in the construction of an artificial satellite and the second period was a positional locating system based on the general purpose wire-less device--ZigBee device.…

Learning With E-books and Project-based Strategy in a Community Health Nursing Course.

PubMed

Sung, Tien-Wen; Wu, Ting-Ting

2018-03-01

With advances in information technology, "information-assisted instruction" has been gradually introduced to nursing education curricula. Specifically, the integration of an e-book system can effectively enhance nursing students' attention and interest. Most studies on nursing education that incorporated e-books have focused on the advantages of convenience and assistance provided by e-books. Few studies have addressed community health nursing and off-campus practice activities in relation to suitable teaching strategies for learning activities. This study involved designing and planning a multimedia e-book learning system with a project-based learning activity that conforms to the curriculum and practical requirements of a community health nursing course. The purpose was to reduce the gap between theory and practice and realize an effective learning process. For learning evaluations, a final examination analysis with an independent sample t test; a scoring scheme with intrateam, interteam, and expert ratings; and Bloom's taxonomy-based analysis were conducted. The evaluation results indicated that the comprehension and learning abilities of the experimental group using the e-book system with a mobile device were effectively improved. In addition, the exploratory process involved in project-based learning can develop multiple cognitive skills and problem-solving ability, thereby realizing effective learning.

Comparisons of Internet-Based and Face-to-Face Learning Systems Based on "Equivalency of Experiences" According to Students' Academic Achievements and Satisfactions

ERIC Educational Resources Information Center

Karatas, Sercin; Simsek, Nurettin

2009-01-01

The purpose of this study is to determine whether "equivalent learning experiences" ensure equivalency, in the Internet-based and face-to-face interaction methods on learning results and student satisfaction. In the experimental process of this study, the effect of the Internet-based and face-to-face learning on the equivalency in…

Web-Based Learning Programs: Use by Learners with Various Cognitive Styles

ERIC Educational Resources Information Center

Chen, Ling-Hsiu

2010-01-01

To consider how Web-based learning program is utilized by learners with different cognitive styles, this study presents a Web-based learning system (WBLS) and analyzes learners' browsing data recorded in the log file to identify how learners' cognitive styles and learning behavior are related. In order to develop an adapted WBLS, this study also…

Experiential Learning in Revolutionary and Post-Revolutionary China.

ERIC Educational Resources Information Center

Kraft, Richard J.

Experience-based learning has been evident in the Chinese educational system since the 1930s. Following the Long March in 1934-35, the Chinese Communists introduced a nonformal, experience-based educational system in North Shensi province. This system included drama groups in the countryside to educate peasants, classes in factories, and…

Web-Based Learning and Instruction Support System for Pneumatics

ERIC Educational Resources Information Center

Yen, Chiaming; Li, Wu-Jeng

2003-01-01

This research presents a Web-based learning and instructional system for Pneumatics. The system includes course material, remote data acquisition modules, and a pneumatic laboratory set. The course material is in the HTML format accompanied with text, still and animated images, simulation programs, and computer aided design tools. The data…

MO-DE-BRA-02: From Teaching to Learning: Systems-Based-Practice and Practice-Based-Learning Innovations in Medical Physics Education Programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kapur, A

Purpose: The increasing complexity in the field of radiation medicine and concomitant rise in patient safety concerns call for enhanced systems-level training for future medical physicists and thus commensurate innovations in existing educational program curricula. In this work we report on the introduction of three learning opportunities to augment medical physics educational programs towards building systems-based practice and practice-based learning competencies. Methods: All initiatives were introduced for senior -level graduate students and physics residents in an institution with a newly established medical-physics graduate program and therapeutic-physics residency program. The first, centered on incident learning, was based on a spreadsheet toolmore » that incorporated the reporting structure of the Radiation Oncology-incident Learning System (ROILS), included 120 narratives of published incidents and enabled inter-rater variability calculations. The second, centered on best-practices, was a zero-credit seminar course, where students summarized select presentations from the AAPM virtual library on a weekly basis and moderated class discussions using a point/counterpoint approach. Presentation styles were critiqued. The third; centered on learning-by-teaching, required physics residents to regularly explain fundamental concepts in radiological physics from standard textbooks to board certified physics faculty members. Results: Use of the incident-learning system spreadsheet provided a platform to recast known accidents into the framework of ROILS, thereby increasing awareness of factors contributing to unsafe practice and appreciation for inter-rater variability. The seminar course enhanced awareness of best practices, the effectiveness of presentation styles and encouraged critical thinking. The learn-by-teaching rotation allowed residents to stay abreast of and deepen their knowledge of relevant subjects. Conclusion: The incorporation of systems-driven initiatives broadens comprehension of the wider systems context of medical physics, enhances awareness of resources for innovation, communication and sustained learning while maintaining a metric-driven focus on patient safety within the formative phase of student careers. The initiatives were well-received, feasible, and utilized available or shared-resources translatable across educational programs.« less

E-Learning System Using Segmentation-Based MR Technique for Learning Circuit Construction

ERIC Educational Resources Information Center

Takemura, Atsushi

2016-01-01

This paper proposes a novel e-Learning system using the mixed reality (MR) technique for technical experiments involving the construction of electronic circuits. The proposed system comprises experimenters' mobile computers and a remote analysis system. When constructing circuits, each learner uses a mobile computer to transmit image data from the…

Multiple memory systems as substrates for multiple decision systems

PubMed Central

Doll, Bradley B.; Shohamy, Daphna; Daw, Nathaniel D.

2014-01-01

It has recently become widely appreciated that value-based decision making is supported by multiple computational strategies. In particular, animal and human behavior in learning tasks appears to include habitual responses described by prominent model-free reinforcement learning (RL) theories, but also more deliberative or goal-directed actions that can be characterized by a different class of theories, model-based RL. The latter theories evaluate actions by using a representation of the contingencies of the task (as with a learned map of a spatial maze), called an “internal model.” Given the evidence of behavioral and neural dissociations between these approaches, they are often characterized as dissociable learning systems, though they likely interact and share common mechanisms. In many respects, this division parallels a longstanding dissociation in cognitive neuroscience between multiple memory systems, describing, at the broadest level, separate systems for declarative and procedural learning. Procedural learning has notable parallels with model-free RL: both involve learning of habits and both are known to depend on parts of the striatum. Declarative memory, by contrast, supports memory for single events or episodes and depends on the hippocampus. The hippocampus is thought to support declarative memory by encoding temporal and spatial relations among stimuli and thus is often referred to as a relational memory system. Such relational encoding is likely to play an important role in learning an internal model, the representation that is central to model-based RL. Thus, insofar as the memory systems represent more general-purpose cognitive mechanisms that might subserve performance on many sorts of tasks including decision making, these parallels raise the question whether the multiple decision systems are served by multiple memory systems, such that one dissociation is grounded in the other. Here we investigated the relationship between model-based RL and relational memory by comparing individual differences across behavioral tasks designed to measure either capacity. Human subjects performed two tasks, a learning and generalization task (acquired equivalence) which involves relational encoding and depends on the hippocampus; and a sequential RL task that could be solved by either a model-based or model-free strategy. We assessed the correlation between subjects’ use of flexible, relational memory, as measured by generalization in the acquired equivalence task, and their differential reliance on either RL strategy in the decision task. We observed a significant positive relationship between generalization and model-based, but not model-free, choice strategies. These results are consistent with the hypothesis that model-based RL, like acquired equivalence, relies on a more general-purpose relational memory system. PMID:24846190

The Current Status and Future Directions in the Development of the Cyber Home Learning System in Korea

ERIC Educational Resources Information Center

Kang, Myunghee; Kim, Seyoung; Yoon, Seonghye; Chung, Warren

2017-01-01

The purpose of this study was to set future directions of the Cyber Home Learning System in Korea based on its current status. The Cyber Home Learning System has been designed and used by K-12 students to study voluntarily at home using online lessons. The development process of the Cyber Home Learning System was composed of the following four…

Construction of IT Based Learning System at University Level

NASA Astrophysics Data System (ADS)

Akiyama, Hidenori; Kozono, Kazutake

Rapid progress of information and communication technologies has been changing the education method. In Japan, online lectures have been recognized as the credits for graduation by the change of a law since 2001. One trial to construct an IT based learning system has been done for the development of IT based higher education and training. Educational effect of online lecture taken anytime and anywhere is evaluated, and then an authoring software for online lectures is developed for educators who are not familiar to IT. A learning management system begins to be operated for whole lectures, and a wireless LAN system is equipped in whole campus of Kumamoto University.

Electronic Learning Systems in Hong Kong Business Organizations: A Study of Early and Late Adopters

ERIC Educational Resources Information Center

Chan, Simon C. H.; Ngai, Eric W. T.

2012-01-01

Based on the diffusion of innovation theory (E. M. Rogers, 1983, 1995), the authors examined the antecedents of the adoption of electronic learning (e-learning) systems by using a time-based assessment model (R. C. Beatty, J. P. Shim, & M. C. Jones, 2001), which classified adopters into categories upon point in time when adopting e-learning…

Designing a Web-Based Science Learning Environment for Model-Based Collaborative Inquiry

NASA Astrophysics Data System (ADS)

Sun, Daner; Looi, Chee-Kit

2013-02-01

The paper traces a research process in the design and development of a science learning environment called WiMVT (web-based inquirer with modeling and visualization technology). The WiMVT system is designed to help secondary school students build a sophisticated understanding of scientific conceptions, and the science inquiry process, as well as develop critical learning skills through model-based collaborative inquiry approach. It is intended to support collaborative inquiry, real-time social interaction, progressive modeling, and to provide multiple sources of scaffolding for students. We first discuss the theoretical underpinnings for synthesizing the WiMVT design framework, introduce the components and features of the system, and describe the proposed work flow of WiMVT instruction. We also elucidate our research approach that supports the development of the system. Finally, the findings of a pilot study are briefly presented to demonstrate of the potential for learning efficacy of the WiMVT implementation in science learning. Implications are drawn on how to improve the existing system, refine teaching strategies and provide feedback to researchers, designers and teachers. This pilot study informs designers like us on how to narrow the gap between the learning environment's intended design and its actual usage in the classroom.

Evaluation Framework Based on Fuzzy Measured Method in Adaptive Learning Systems

ERIC Educational Resources Information Center

Ounaies, Houda Zouari; Jamoussi, Yassine; Ben Ghezala, Henda Hajjami

2008-01-01

Currently, e-learning systems are mainly web-based applications and tackle a wide range of users all over the world. Fitting learners' needs is considered as a key issue to guaranty the success of these systems. Many researches work on providing adaptive systems. Nevertheless, evaluation of the adaptivity is still in an exploratory phase.…

Computer-Assisted English Learning System Based on Free Conversation by Topic

ERIC Educational Resources Information Center

Choi, Sung-Kwon; Kwon, Oh-Woog; Kim, Young-Kil

2017-01-01

This paper aims to describe a computer-assisted English learning system using chatbots and dialogue systems, which allow free conversation outside the topic without limiting the learner's flow of conversation. The evaluation was conducted by 20 experimenters. The performance of the system based on a free conversation by topic was measured by the…

Establishment and Usability Evaluation of an Interactive AR Learning System on Conservation of Fish

ERIC Educational Resources Information Center

Lin, Hao-Chiang Koong; Hsieh, Min-Chai; Wang, Cheng-Hung; Sie, Zong-Yuan; Chang, Shei-Hsi

2011-01-01

In this study, we develop an interactive AR Learning System based on Augmented Reality and interactive touch-screen. The learning content knowledge is about conservation of fish in Taiwan. The system combines the game by the concept of AR book which allows children to learn about the importance of conservation of fish. A mechanism is designed to…

Delayed Feedback Disrupts the Procedural-Learning System but Not the Hypothesis-Testing System in Perceptual Category Learning

ERIC Educational Resources Information Center

Maddox, W. Todd; Ing, A. David

2005-01-01

W. T. Maddox, F. G. Ashby, and C. J. Bohil (2003) found that delayed feedback adversely affects information-integration but not rule-based category learning in support of a multiple-systems approach to category learning. However, differences in the number of stimulus dimensions relevant to solving the task and perceptual similarity failed to rule…

Learning to improve iterative repair scheduling

NASA Technical Reports Server (NTRS)

Zweben, Monte; Davis, Eugene

1992-01-01

This paper presents a general learning method for dynamically selecting between repair heuristics in an iterative repair scheduling system. The system employs a version of explanation-based learning called Plausible Explanation-Based Learning (PEBL) that uses multiple examples to confirm conjectured explanations. The basic approach is to conjecture contradictions between a heuristic and statistics that measure the quality of the heuristic. When these contradictions are confirmed, a different heuristic is selected. To motivate the utility of this approach we present an empirical evaluation of the performance of a scheduling system with respect to two different repair strategies. We show that the scheduler that learns to choose between the heuristics outperforms the same scheduler with any one of two heuristics alone.

Direct heuristic dynamic programming for damping oscillations in a large power system.

PubMed

Lu, Chao; Si, Jennie; Xie, Xiaorong

2008-08-01

This paper applies a neural-network-based approximate dynamic programming method, namely, the direct heuristic dynamic programming (direct HDP), to a large power system stability control problem. The direct HDP is a learning- and approximation-based approach to addressing nonlinear coordinated control under uncertainty. One of the major design parameters, the controller learning objective function, is formulated to directly account for network-wide low-frequency oscillation with the presence of nonlinearity, uncertainty, and coupling effect among system components. Results include a novel learning control structure based on the direct HDP with applications to two power system problems. The first case involves static var compensator supplementary damping control, which is used to provide a comprehensive evaluation of the learning control performance. The second case aims at addressing a difficult complex system challenge by providing a new solution to a large interconnected power network oscillation damping control problem that frequently occurs in the China Southern Power Grid.

KBGIS-II: A knowledge-based geographic information system

NASA Technical Reports Server (NTRS)

Smith, Terence; Peuquet, Donna; Menon, Sudhakar; Agarwal, Pankaj

1986-01-01

The architecture and working of a recently implemented Knowledge-Based Geographic Information System (KBGIS-II), designed to satisfy several general criteria for the GIS, is described. The system has four major functions including query-answering, learning and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial object language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multilayered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is performing all its designated tasks successfully. Future reports will relate performance characteristics of the system.

Factors Affecting Selection of Learning Management Systems in Higher Education Institutions

ERIC Educational Resources Information Center

Spelke, Kenneth A.

2011-01-01

Learning Management Systems, or LMSs, are widely used throughout higher education to deliver a range of instructional services including content delivery, discussion boards and collaborative work space, testing tools, and gradebook functions. LMSs can be used asynchronously or synchronously in support of online learning, classroom-based learning,…

Gaussian Processes for Data-Efficient Learning in Robotics and Control.

PubMed

Deisenroth, Marc Peter; Fox, Dieter; Rasmussen, Carl Edward

2015-02-01

Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning (RL) approaches typically require many interactions with the system to learn controllers, which is a practical limitation in real systems, such as robots, where many interactions can be impractical and time consuming. To address this problem, current learning approaches typically require task-specific knowledge in form of expert demonstrations, realistic simulators, pre-shaped policies, or specific knowledge about the underlying dynamics. In this paper, we follow a different approach and speed up learning by extracting more information from data. In particular, we learn a probabilistic, non-parametric Gaussian process transition model of the system. By explicitly incorporating model uncertainty into long-term planning and controller learning our approach reduces the effects of model errors, a key problem in model-based learning. Compared to state-of-the art RL our model-based policy search method achieves an unprecedented speed of learning. We demonstrate its applicability to autonomous learning in real robot and control tasks.

Automated Decomposition of Model-based Learning Problems

NASA Technical Reports Server (NTRS)

Williams, Brian C.; Millar, Bill

1996-01-01

A new generation of sensor rich, massively distributed autonomous systems is being developed that has the potential for unprecedented performance, such as smart buildings, reconfigurable factories, adaptive traffic systems and remote earth ecosystem monitoring. To achieve high performance these massive systems will need to accurately model themselves and their environment from sensor information. Accomplishing this on a grand scale requires automating the art of large-scale modeling. This paper presents a formalization of [\\em decompositional model-based learning (DML)], a method developed by observing a modeler's expertise at decomposing large scale model estimation tasks. The method exploits a striking analogy between learning and consistency-based diagnosis. Moriarty, an implementation of DML, has been applied to thermal modeling of a smart building, demonstrating a significant improvement in learning rate.

Multiscale Support Vector Learning With Projection Operator Wavelet Kernel for Nonlinear Dynamical System Identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2016-02-03

A giant leap has been made in the past couple of decades with the introduction of kernel-based learning as a mainstay for designing effective nonlinear computational learning algorithms. In view of the geometric interpretation of conditional expectation and the ubiquity of multiscale characteristics in highly complex nonlinear dynamic systems [1]-[3], this paper presents a new orthogonal projection operator wavelet kernel, aiming at developing an efficient computational learning approach for nonlinear dynamical system identification. In the framework of multiresolution analysis, the proposed projection operator wavelet kernel can fulfill the multiscale, multidimensional learning to estimate complex dependencies. The special advantage of the projection operator wavelet kernel developed in this paper lies in the fact that it has a closed-form expression, which greatly facilitates its application in kernel learning. To the best of our knowledge, it is the first closed-form orthogonal projection wavelet kernel reported in the literature. It provides a link between grid-based wavelets and mesh-free kernel-based methods. Simulation studies for identifying the parallel models of two benchmark nonlinear dynamical systems confirm its superiority in model accuracy and sparsity.

Supporting Self-Regulated Learning in Web 2.0 Contexts

ERIC Educational Resources Information Center

Huang, Yong-Ming; Huang, Yueh-Min; Wang, Chia-Sui; Liu, Chien-Hung; Sandnes, Frode Eika

2012-01-01

Web-based self-learning (WBSL) provides learners with a powerful means of acquiring knowledge. However, WBSL may disorient learners, especially when their skills are inadequate for regulating their learning. In this paper, a Web 2.0 self-regulated learning (Web2SRL) system based on the theory of self-regulated learning is proposed. Learners use…

Extend Instruction outside the Classroom: Take Advantage of Your Learning Management System

ERIC Educational Resources Information Center

Jensen, Lauren A.

2010-01-01

Numerous institutions of higher education have implemented a learning management system (LMS) or are considering doing so. This web-based software package provides self-service and quick (often personalized) access to content in a dynamic environment. Learning management systems support administrative, reporting, and documentation activities. LMSs…

Developing a Dynamic Inference Expert System to Support Individual Learning at Work

ERIC Educational Resources Information Center

Hung, Yu Hsin; Lin, Chun Fu; Chang, Ray I.

2015-01-01

In response to the rapid growth of information in recent decades, knowledge-based systems have become an essential tool for organizational learning. The application of electronic performance-support systems in learning activities has attracted considerable attention from researchers. Nevertheless, the vast, ever-increasing amount of information is…

Multi-Criteria Evaluation of the Web-Based E-Learning System: A Methodology Based on Learner Satisfaction and Its Applications

ERIC Educational Resources Information Center

Shee, Daniel Y.; Wang, Yi-Shun

2008-01-01

The web-based e-learning system (WELS) has emerged as a new means of skill training and knowledge acquisition, encouraging both academia and industry to invest resources in the adoption of this system. Traditionally, most pre- and post-adoption tasks related to evaluation are carried out from the viewpoints of technology. Since users have been…

Development and Testing of a M-Learning System for the Professional Development of Academics through Design-Based Action Research

ERIC Educational Resources Information Center

Keskin, Nilgun Ozdamar; Kuzu, Abdullah

2015-01-01

In the present study, a mobile learning system for the professional development of academics was developed by design based action research, and the perceptions and experiences of the academics using this system were examined. In the first phase of this design-based action research, the research question was defined. In the second phase, a…

75 FR 52373 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-25

... Administration. Type of Review: NEW. Title of Collection: Evaluation of the Technology-Based Learning Grants. OMB... technology based learning. The initiative increases worker access to training while stimulating the development of innovative models and uses for technology based learning in the public workforce system. For...

Grading for Understanding--Standards-Based Grading

ERIC Educational Resources Information Center

Zimmerman, Todd

2017-01-01

Standards-based grading (SBG), sometimes called learning objectives-based assessment (LOBA), is an assessment model that relies on students demonstrating mastery of learning objectives (sometimes referred to as standards). The goal of this grading system is to focus students on mastering learning objectives rather than on accumulating points. I…

Fixed Point Learning Based Intelligent Traffic Control System

NASA Astrophysics Data System (ADS)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems.

PubMed

Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

2016-01-01

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

PubMed Central

Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

2016-01-01

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning. PMID:27445958

Are Accessible Distance Learning Systems Useful for All Students?: Our Experience with IMES, an Accessible Web-Based Learning System

ERIC Educational Resources Information Center

Iglesias, Ana; Moreno, Lourdes; Cuadra, Dolores; Castro, Elena

2013-01-01

Nowadays the use of distance learning systems is widely extended in engineering education. Moreover, most of them use multimedia resources that sometimes are the only educational material available to provide certain educational knowledge to the students. Unfortunately, most of the current educational systems and their educational content present…

Are Accessible Distance Learning Systems Useful for All Students?: Our Experience with IMES, an Accessible Web-Based Learning System

ERIC Educational Resources Information Center

Iglesias, Ana; Moreno, Lourdes; Castro, Elena; Cuadra, Dolores

2014-01-01

Nowadays the use of distance learning systems is widely extended in engineering education. Moreover, most of them use multimedia resources that sometimes are the only educational material available to provide certain educational knowledge to the students. Unfortunately, most of the current educational systems and their educational content present…

A Selection System and Catalog for Instructional Media and Devices.

ERIC Educational Resources Information Center

Boucher, Brian G.; And Others

A system is presented which facilitates the selection of training media and devices based on the requirements of specific learning objectives. The system consists of the use of a set of descriptive parameters which are common to both learning objectives and media. The system allows the essential intent of learning objectives to be analyzed in…

COED Transactions, Vol. X, No. 11, November 1978. A Microprocesser-Based Interactive Learning System.

ERIC Educational Resources Information Center

Mitchell, Eugene E., Ed.

A Microcomputer-Implemented Design Aid and Simulator (MIDAS) has been developed and used as an interactive learning system by electrical engineering students at the freshman and sophomore level. Evaluation of the system indicates that a great potential exists in the area of dedicated, inexpensive, interactive learning systems. User acceptance has…

Usability Evaluation of a Web-Based Learning System

ERIC Educational Resources Information Center

Nguyen, Thao

2012-01-01

The paper proposes a contingent, learner-centred usability evaluation method and a prototype tool of such systems. This is a new usability evaluation method for web-based learning systems using a set of empirically-supported usability factors and can be done effectively with limited resources. During the evaluation process, the method allows for…

A Chatbot for a Dialogue-Based Second Language Learning System

ERIC Educational Resources Information Center

Huang, Jin-Xia; Lee, Kyung-Soon; Kwon, Oh-Woog; Kim, Young-Kil

2017-01-01

This paper presents a chatbot for a Dialogue-Based Computer-Assisted second Language Learning (DB-CALL) system. A DB-CALL system normally leads dialogues by asking questions according to given scenarios. User utterances outside the scenarios are normally considered as semantically improper and simply rejected. In this paper, we assume that raising…

Collaborative Learning and Knowledge-Construction through a Knowledge-Based WWW Authoring Tool.

ERIC Educational Resources Information Center

Haugsjaa, Erik

This paper outlines hurdles to using the World Wide Web for learning, specifically in a collaborative knowledge-construction environment. Theoretical solutions based directly on existing Web environments, as well as on research and system prototypes in the areas of Intelligent Tutoring Systems (ITS) and ITS authoring systems, are suggested. Topics…

Intelligent control based on fuzzy logic and neural net theory

NASA Technical Reports Server (NTRS)

Lee, Chuen-Chien

1991-01-01

In the conception and design of intelligent systems, one promising direction involves the use of fuzzy logic and neural network theory to enhance such systems' capability to learn from experience and adapt to changes in an environment of uncertainty and imprecision. Here, an intelligent control scheme is explored by integrating these multidisciplinary techniques. A self-learning system is proposed as an intelligent controller for dynamical processes, employing a control policy which evolves and improves automatically. One key component of the intelligent system is a fuzzy logic-based system which emulates human decision making behavior. It is shown that the system can solve a fairly difficult control learning problem. Simulation results demonstrate that improved learning performance can be achieved in relation to previously described systems employing bang-bang control. The proposed system is relatively insensitive to variations in the parameters of the system environment.

Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy.

PubMed

Tian, Yuling; Zhang, Hongxian

2016-01-01

For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic-there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.

Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy

PubMed Central

Tian, Yuling; Zhang, Hongxian

2016-01-01

For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic–there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions. PMID:27487242

Cognitive Tools for Assessment and Learning in a High Information Flow Environment.

ERIC Educational Resources Information Center

Lajoie, Susanne P.; Azevedo, Roger; Fleiszer, David M.

1998-01-01

Describes the development of a simulation-based intelligent tutoring system for nurses working in a surgical intensive care unit. Highlights include situative learning theories and models of instruction, modeling expertise, complex decision making, linking theories of learning to the design of computer-based learning environments, cognitive task…

Ontology Mappings to Improve Learning Resource Search

ERIC Educational Resources Information Center

Gasevic, Dragan; Hatala, Marek

2006-01-01

This paper proposes an ontology mapping-based framework that allows searching for learning resources using multiple ontologies. The present applications of ontologies in e-learning use various ontologies (eg, domain, curriculum, context), but they do not give a solution on how to interoperate e-learning systems based on different ontologies. The…

Visualising Learning Design in LAMS: A Historical View

ERIC Educational Resources Information Center

Dalziel, James

2011-01-01

The Learning Activity Management System (LAMS) provides a web-based environment for the creation, sharing, running and monitoring of Learning Designs. A central feature of LAMS is the visual authoring environment, where educators use a drag-and-drop environment to create sequences of learning activities. The visualisation is based on boxes…

Correcting Misconceptions on Electronics: Effects of a Simulation-Based Learning Environment Backed by a Conceptual Change Model

ERIC Educational Resources Information Center

Chen, Yu-Lung; Pan, Pei-Rong; Sung, Yao-Ting; Chang, Kuo-En

2013-01-01

Computer simulation has significant potential as a supplementary tool for effective conceptual-change learning based on the integration of technology and appropriate instructional strategies. This study elucidates misconceptions in learning on diodes and constructs a conceptual-change learning system that incorporates…

Web 2.0 systems supporting childhood chronic disease management: design guidelines based on information behaviour and social learning theories.

PubMed

Ekberg, Joakim; Ericson, Leni; Timpka, Toomas; Eriksson, Henrik; Nordfeldt, Sam; Hanberger, Lena; Ludvigsson, Johnny

2010-04-01

Self-directed learning denotes that the individual is in command of what should be learned and why it is important. In this study, guidelines for the design of Web 2.0 systems for supporting diabetic adolescents' every day learning needs are examined in light of theories about information behaviour and social learning. A Web 2.0 system was developed to support a community of practice and social learning structures were created to support building of relations between members on several levels in the community. The features of the system included access to participation in the culture of diabetes management practice, entry to information about the community and about what needs to be learned to be a full practitioner or respected member in the community, and free sharing of information, narratives and experience-based knowledge. After integration with the key elements derived from theories of information behaviour, a preliminary design guideline document was formulated.

Project MAPP. The Vocabulary Booklet # 1. Implementing the Instructional Program: A Competency-Based Adult Education Learning System.

ERIC Educational Resources Information Center

Maryland State Dept. of Education, Baltimore.

This booklet is intended to help adults master the basic and life skill vocabulary needed to meet the simple communication demands of daily life. It is designed to assist adult basic education (ABE) teachers in the implementation of a competency-based learning system that emphasizes the integration of basic and life skills learning. The booklet…

Adaptive WTA with an analog VLSI neuromorphic learning chip.

PubMed

Häfliger, Philipp

2007-03-01

In this paper, we demonstrate how a particular spike-based learning rule (where exact temporal relations between input and output spikes of a spiking model neuron determine the changes of the synaptic weights) can be tuned to express rate-based classical Hebbian learning behavior (where the average input and output spike rates are sufficient to describe the synaptic changes). This shift in behavior is controlled by the input statistic and by a single time constant. The learning rule has been implemented in a neuromorphic very large scale integration (VLSI) chip as part of a neurally inspired spike signal image processing system. The latter is the result of the European Union research project Convolution AER Vision Architecture for Real-Time (CAVIAR). Since it is implemented as a spike-based learning rule (which is most convenient in the overall spike-based system), even if it is tuned to show rate behavior, no explicit long-term average signals are computed on the chip. We show the rule's rate-based Hebbian learning ability in a classification task in both simulation and chip experiment, first with artificial stimuli and then with sensor input from the CAVIAR system.

The Impact of CMS Quality on the Outcomes of E-Learning Systems in Higher Education: An Empirical Study

ERIC Educational Resources Information Center

Kim, Kihyun; Trimi, Silvana; Park, Hyesung; Rhee, Shanggeun

2012-01-01

Course Management Systems (CMSs) in higher education have emerged as one of the most widely adopted e-learning platforms. This study examines the success of e-learning CMSs based on user satisfaction and benefits. Using DeLone and McLean's information system success model as a theoretical framework, we analyze the success of e-learning CMSs in…

Adapting Instruction to Individual Learner Differences: A Research Paradigm for Computer-Based Instruction.

ERIC Educational Resources Information Center

Mills, Steven C.; Ragan, Tillman J.

This paper examines a research paradigm that is particularly suited to experimentation-related computer-based instruction and integrated learning systems. The main assumption of the model is that one of the most powerful capabilities of computer-based instruction, and specifically of integrated learning systems, is the capacity to adapt…

A Web-Based Tutor for Java™: Evidence of Meaningful Learning

ERIC Educational Resources Information Center

Emurian, Henry H.

2006-01-01

Students in a graduate class and an undergraduate class in Information Systems completed a Web-based programmed instruction tutor that taught a simple Java applet as the first technical training exercise in a computer programming course. The tutor is a competency-based instructional system for individualized distance learning. When a student…

Content-Based VLE Designs Improve Learning Efficiency in Constructivist Statistics Education

PubMed Central

Wessa, Patrick; De Rycker, Antoon; Holliday, Ian Edward

2011-01-01

Background We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE) in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses), which required us to develop a specific–purpose Statistical Learning Environment (SLE) based on Reproducible Computing and newly developed Peer Review (PR) technology. Objectives The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. Methods Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. Results The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under investigation. The findings demonstrate that a content–based design outperforms the traditional VLE–based design. PMID:21998652

Learning-based position control of a closed-kinematic chain robot end-effector

NASA Technical Reports Server (NTRS)

Nguyen, Charles C.; Zhou, Zhen-Lei

1990-01-01

A trajectory control scheme whose design is based on learning theory, for a six-degree-of-freedom (DOF) robot end-effector built to study robotic assembly of NASA hardwares in space is presented. The control scheme consists of two control systems: the feedback control system and the learning control system. The feedback control system is designed using the concept of linearization about a selected operating point, and the method of pole placement so that the closed-loop linearized system is stabilized. The learning control scheme consisting of PD-type learning controllers, provides additional inputs to improve the end-effector performance after each trial. Experimental studies performed on a 2 DOF end-effector built at CUA, for three tracking cases show that actual trajectories approach desired trajectories as the number of trials increases. The tracking errors are substantially reduced after only five trials.

Humanoids Learning to Walk: A Natural CPG-Actor-Critic Architecture.

PubMed

Li, Cai; Lowe, Robert; Ziemke, Tom

2013-01-01

The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value.

Humanoids Learning to Walk: A Natural CPG-Actor-Critic Architecture

PubMed Central

Li, Cai; Lowe, Robert; Ziemke, Tom

2013-01-01

The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value. PMID:23675345

Adaptive Semantic and Social Web-based learning and assessment environment for the STEM

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Atchison, Chris; Sunderraman, Rajshekhar

2014-05-01

We are building a cloud- and Semantic Web-based personalized, adaptive learning environment for the STEM fields that integrates and leverages Social Web technologies to allow instructors and authors of learning material to collaborate in semi-automatic development and update of their common domain and task ontologies and building their learning resources. The semi-automatic ontology learning and development minimize issues related to the design and maintenance of domain ontologies by knowledge engineers who do not have any knowledge of the domain. The social web component of the personal adaptive system will allow individual and group learners to interact with each other and discuss their own learning experience and understanding of course material, and resolve issues related to their class assignments. The adaptive system will be capable of representing key knowledge concepts in different ways and difficulty levels based on learners' differences, and lead to different understanding of the same STEM content by different learners. It will adapt specific pedagogical strategies to individual learners based on their characteristics, cognition, and preferences, allow authors to assemble remotely accessed learning material into courses, and provide facilities for instructors to assess (in real time) the perception of students of course material, monitor their progress in the learning process, and generate timely feedback based on their understanding or misconceptions. The system applies a set of ontologies that structure the learning process, with multiple user friendly Web interfaces. These include the learning ontology (models learning objects, educational resources, and learning goal); context ontology (supports adaptive strategy by detecting student situation), domain ontology (structures concepts and context), learner ontology (models student profile, preferences, and behavior), task ontologies, technological ontology (defines devices and places that surround the student), pedagogy ontology, and learner ontology (defines time constraint, comment, profile).

Fuzzy self-learning control for magnetic servo system

NASA Technical Reports Server (NTRS)

Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.

1994-01-01

It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.

An Assessment of the Army Officer Education System From an Adult Learning Perspective

DTIC Science & Technology

2005-05-26

learning 2 Brockett, Ralph, and Roger Hiemstra. "Bridging the Theory -Practice Gap in Self-Directed... Learning ." In Self-Directed Learning : From Theory to Practice, edited by S. Brookfield. New Directions for Continuing Education No. 25. (San...offers conclusions and recommendations about the Army Officer Education System based on analysis from adult learning theory . Statement of the

A Rule-Based System for Hybrid Search and Delivery of Learning Objects to Learners

ERIC Educational Resources Information Center

Biletskiy, Yevgen; Baghi, Hamidreza; Steele, Jarrett; Vovk, Ruslan

2012-01-01

Purpose: Presently, searching the internet for learning material relevant to ones own interest continues to be a time-consuming task. Systems that can suggest learning material (learning objects) to a learner would reduce time spent searching for material, and enable the learner to spend more time for actual learning. The purpose of this paper is…

Indirect decentralized learning control

NASA Technical Reports Server (NTRS)

Longman, Richard W.; Lee, Soo C.; Phan, M.

1992-01-01

The new field of learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented a theory of indirect learning control based on use of indirect adaptive control concepts employing simultaneous identification and control. This paper develops improved indirect learning control algorithms, and studies the use of such controllers in decentralized systems. The original motivation of the learning control field was learning in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. The basic result of the paper is to show that stability of the indirect learning controllers for all subsystems when the coupling between subsystems is turned off, assures convergence to zero tracking error of the decentralized indirect learning control of the coupled system, provided that the sample time in the digital learning controller is sufficiently short.

Ontology-Based Multimedia Authoring Tool for Adaptive E-Learning

ERIC Educational Resources Information Center

Deng, Lawrence Y.; Keh, Huan-Chao; Liu, Yi-Jen

2010-01-01

More video streaming technologies supporting distance learning systems are becoming popular among distributed network environments. In this paper, the authors develop a multimedia authoring tool for adaptive e-learning by using characterization of extended media streaming technologies. The distributed approach is based on an ontology-based model.…

A Web-Based Learning System for Software Test Professionals

ERIC Educational Resources Information Center

Wang, Minhong; Jia, Haiyang; Sugumaran, V.; Ran, Weijia; Liao, Jian

2011-01-01

Fierce competition, globalization, and technology innovation have forced software companies to search for new ways to improve competitive advantage. Web-based learning is increasingly being used by software companies as an emergent approach for enhancing the skills of knowledge workers. However, the current practice of Web-based learning is…

Study of distributed learning as a solution to category proliferation in Fuzzy ARTMAP based neural systems.

PubMed

Parrado-Hernández, Emilio; Gómez-Sánchez, Eduardo; Dimitriadis, Yannis A

2003-09-01

An evaluation of distributed learning as a means to attenuate the category proliferation problem in Fuzzy ARTMAP based neural systems is carried out, from both qualitative and quantitative points of view. The study involves two original winner-take-all (WTA) architectures, Fuzzy ARTMAP and FasArt, and their distributed versions, dARTMAP and dFasArt. A qualitative analysis of the distributed learning properties of dARTMAP is made, focusing on the new elements introduced to endow Fuzzy ARTMAP with distributed learning. In addition, a quantitative study on a selected set of classification problems points out that problems have to present certain features in their output classes in order to noticeably reduce the number of recruited categories and achieve an acceptable classification accuracy. As part of this analysis, distributed learning was successfully adapted to a member of the Fuzzy ARTMAP family, FasArt, and similar procedures can be used to extend distributed learning capabilities to other Fuzzy ARTMAP based systems.

Web-Based Learning Information System for Web 3.0

NASA Astrophysics Data System (ADS)

Rego, Hugo; Moreira, Tiago; García-Peñalvo, Francisco Jose

With the emergence of Web/eLearning 3.0 we have been developing/adjusting AHKME in order to face this great challenge. One of our goals is to allow the instructional designer and teacher to access standardized resources and evaluate the possibility of integration and reuse in eLearning systems, not only content but also the learning strategy. We have also integrated some collaborative tools for the adaptation of resources, as well as the collection of feedback from users to provide feedback to the system. We also provide tools for the instructional designer to create/customize specifications/ontologies to give structure and meaning to resources, manual and automatic search with recommendation of resources and instructional design based on the context, as well as recommendation of adaptations in learning resources. We also consider the concept of mobility and mobile technology applied to eLearning, allowing access by teachers and students to learning resources, regardless of time and space.

Agent-based traffic management and reinforcement learning in congested intersection network.

DOT National Transportation Integrated Search

2012-08-01

This study evaluates the performance of traffic control systems based on reinforcement learning (RL), also called approximate dynamic programming (ADP). Two algorithms have been selected for testing: 1) Q-learning and 2) approximate dynamic programmi...

Web-Based Learning System for Developing and Assessing Clinical Diagnostic Skills for Dermatology Residency Program

ERIC Educational Resources Information Center

Kuo, Fan-Ray; Chin, Yi-Ying; Lee, Chao-Hsien; Chiu, Yu-Hsien; Hong, Chien-Hu; Lee, Kuang-Lieh; Ho, Wen-Hsien; Lee, Chih-Hung

2016-01-01

Few studies have explored the learning difficulties and misconceptions that students encounter when using information and communication technology for e-learning. To address this issue, this research developed a system for evaluating the learning efficiency of medical students by applying two-tier diagnosis assessment. The effectiveness of the…

A Methodology to Obtain Learning Effective Laboratories with Learning Management System Integration

ERIC Educational Resources Information Center

Ruano, Ildefonso; Gamez, Javier; Dormido, Sebastian; Gomez, Juan

2016-01-01

Online laboratories are useful and valuable resources in high education, especially in engineering studies. This work presents a methodology to create effective laboratories for learning that interact with a Learning Management System (LMS) to achieve advanced integration. It is based on pedagogical aspects and considers not only the laboratory…

Utilizing Learners' Negative Ratings in Semantic Content-Based Recommender System for e-Learning Forum

ERIC Educational Resources Information Center

Albatayneh, Naji Ahmad; Ghauth, Khairil Imran; Chua, Fang-Fang

2018-01-01

Nowadays, most of e-learning systems embody online discussion forums as a medium for collaborative learning that supports knowledge sharing and information exchanging between learners. The exponential growth of the available shared information in e-learning online discussion forums has caused a difficulty for learners in discovering interesting…

The Effectiveness of the Game-Based Learning System for the Improvement of American Sign Language Using Kinect

ERIC Educational Resources Information Center

Kamnardsiri, Teerawat; Hongsit, Ler-on; Khuwuthyakorn, Pattaraporn; Wongta, Noppon

2017-01-01

This paper investigated students' achievement for learning American Sign Language (ASL), using two different methods. There were two groups of samples. The first experimental group (Group A) was the game-based learning for ASL, using Kinect. The second control learning group (Group B) was the traditional face-to-face learning method, generally…

Accreditation of Prior Experiential Learning as a Catalyst for Lifelong Learning: Analysis and Proposals Based on French Experiments

ERIC Educational Resources Information Center

Sanseau, Pierre-Yves; Ansart, Sandrine

2013-01-01

In this paper, the researchers analyse how lifelong learning can be enriched and develop a different perspective based on the experiment involving the accreditation of prior experiential learning (APEL) conducted in France at the university level. The French system for the accreditation of prior experiential learning, called Validation des Acquis…

The Effects of Online Interactive Games on High School Students' Achievement and Motivation in History Learning

ERIC Educational Resources Information Center

Lin, Kuan-Cheng; Wei, Yu Che; Hung, Jason C.

2012-01-01

Many studies demonstrate that Digital Game Based Learning (DGBL) can foster learning effect. The purpose of this study is to survey whether the online game in junior high school students can encourage learning effect in Taiwan's History. So, the research applied Interactive Game-based Learning System (IGLS) to junior high history teaching as an…

Barriers of the Development of Web-Based Training in Agricultural Higher Education System in Iran: A Case Study of Hamadan Bu Ali Sina University, Iran

ERIC Educational Resources Information Center

Saadi, Heshmatollah; Mirzayi, Khalil; Movahedi, Reza

2016-01-01

Recently, higher education systems seek to use network-based and Internet-based information technologies in education, teaching and learning. E-learning in Iran higher education system has been started since 2003, however, its development has been very slow. The present study is a survey research. The participants of the study are faculty members,…

Model-free and model-based reward prediction errors in EEG.

PubMed

Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

2018-05-24

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

Automatic Dialogue Scoring for a Second Language Learning System

ERIC Educational Resources Information Center

Huang, Jin-Xia; Lee, Kyung-Soon; Kwon, Oh-Woog; Kim, Young-Kil

2016-01-01

This paper presents an automatic dialogue scoring approach for a Dialogue-Based Computer-Assisted Language Learning (DB-CALL) system, which helps users learn language via interactive conversations. The system produces overall feedback according to dialogue scoring to help the learner know which parts should be more focused on. The scoring measures…

Architecture of an E-Learning System with Embedded Authoring Support.

ERIC Educational Resources Information Center

Baudry, Andreas; Bungenstock, Michael; Mertsching, Barbel

This paper introduces an architecture for an e-learning system with an embedded authoring system. Based on the metaphor of a construction kit, this approach offers a general solution for specific content creation and publication. The learning resources are IMS "Content Packages" with a special structure to separate content and presentation. These…

Understanding Motivational System in Open Learning: Learners' Engagement with a Traditional Chinese-Based Open Educational Resource System

ERIC Educational Resources Information Center

Huang, Wenhao David; Wu, Chorng-Guang

2017-01-01

Learning has embraced the "open" process in recent years, as many educational resources are made available for free online. Existing research, however, has not provided sufficient evidence to systematically improve open learning interactions and engagement in open educational resource (OER) systems. This deficiency presents two…

A Design Quality Learning Unit in Relational Data Modeling Based on Thriving Systems Properties

ERIC Educational Resources Information Center

Waguespack, Leslie J.

2013-01-01

This paper presents a learning unit that addresses quality design in relational data models. The focus on modeling allows the learning to span analysis, design, and implementation enriching pedagogy across the systems development life cycle. Thriving Systems Theory presents fifteen choice properties that convey design quality in models integrating…

Transcranial infrared laser stimulation improves rule-based, but not information-integration, category learning in humans.

PubMed

Blanco, Nathaniel J; Saucedo, Celeste L; Gonzalez-Lima, F

2017-03-01

This is the first randomized, controlled study comparing the cognitive effects of transcranial laser stimulation on category learning tasks. Transcranial infrared laser stimulation is a new non-invasive form of brain stimulation that shows promise for wide-ranging experimental and neuropsychological applications. It involves using infrared laser to enhance cerebral oxygenation and energy metabolism through upregulation of the respiratory enzyme cytochrome oxidase, the primary infrared photon acceptor in cells. Previous research found that transcranial infrared laser stimulation aimed at the prefrontal cortex can improve sustained attention, short-term memory, and executive function. In this study, we directly investigated the influence of transcranial infrared laser stimulation on two neurobiologically dissociable systems of category learning: a prefrontal cortex mediated reflective system that learns categories using explicit rules, and a striatally mediated reflexive learning system that forms gradual stimulus-response associations. Participants (n=118) received either active infrared laser to the lateral prefrontal cortex or sham (placebo) stimulation, and then learned one of two category structures-a rule-based structure optimally learned by the reflective system, or an information-integration structure optimally learned by the reflexive system. We found that prefrontal rule-based learning was substantially improved following transcranial infrared laser stimulation as compared to placebo (treatment X block interaction: F(1, 298)=5.117, p=0.024), while information-integration learning did not show significant group differences (treatment X block interaction: F(1, 288)=1.633, p=0.202). These results highlight the exciting potential of transcranial infrared laser stimulation for cognitive enhancement and provide insight into the neurobiological underpinnings of category learning. Copyright © 2017 Elsevier Inc. All rights reserved.

BlueSky Cloud Framework: An E-Learning Framework Embracing Cloud Computing

NASA Astrophysics Data System (ADS)

Dong, Bo; Zheng, Qinghua; Qiao, Mu; Shu, Jian; Yang, Jie

Currently, E-Learning has grown into a widely accepted way of learning. With the huge growth of users, services, education contents and resources, E-Learning systems are facing challenges of optimizing resource allocations, dealing with dynamic concurrency demands, handling rapid storage growth requirements and cost controlling. In this paper, an E-Learning framework based on cloud computing is presented, namely BlueSky cloud framework. Particularly, the architecture and core components of BlueSky cloud framework are introduced. In BlueSky cloud framework, physical machines are virtualized, and allocated on demand for E-Learning systems. Moreover, BlueSky cloud framework combines with traditional middleware functions (such as load balancing and data caching) to serve for E-Learning systems as a general architecture. It delivers reliable, scalable and cost-efficient services to E-Learning systems, and E-Learning organizations can establish systems through these services in a simple way. BlueSky cloud framework solves the challenges faced by E-Learning, and improves the performance, availability and scalability of E-Learning systems.

Combining Computational Modeling and Neuroimaging to Examine Multiple Category Learning Systems in the Brain

PubMed Central

Nomura, Emi M.; Reber, Paul J.

2012-01-01

Considerable evidence has argued in favor of multiple neural systems supporting human category learning, one based on conscious rule inference and one based on implicit information integration. However, there have been few attempts to study potential system interactions during category learning. The PINNACLE (Parallel Interactive Neural Networks Active in Category Learning) model incorporates multiple categorization systems that compete to provide categorization judgments about visual stimuli. Incorporating competing systems requires inclusion of cognitive mechanisms associated with resolving this competition and creates a potential credit assignment problem in handling feedback. The hypothesized mechanisms make predictions about internal mental states that are not always reflected in choice behavior, but may be reflected in neural activity. Two prior functional magnetic resonance imaging (fMRI) studies of category learning were re-analyzed using PINNACLE to identify neural correlates of internal cognitive states on each trial. These analyses identified additional brain regions supporting the two types of category learning, regions particularly active when the systems are hypothesized to be in maximal competition, and found evidence of covert learning activity in the “off system” (the category learning system not currently driving behavior). These results suggest that PINNACLE provides a plausible framework for how competing multiple category learning systems are organized in the brain and shows how computational modeling approaches and fMRI can be used synergistically to gain access to cognitive processes that support complex decision-making machinery. PMID:24962771

Construction of teacher knowledge in context: Preparing elementary teachers to teach mathematics and science

NASA Astrophysics Data System (ADS)

Lowery, Maye Norene Vail

1998-12-01

The purposes of this study were to further the understanding of how preservice teacher construct teacher knowledge and pedagogical content knowledge of elementary mathematics and science and to determine the extent of that knowledge in a school-based setting. Preservice teachers, university instructors, inservice teachers, and other school personnel were involved in this context-specific study. Evidence of the preservice teachers' knowledge construction (its acquisition, its dimensions, and the social context) was collected through the use of a qualitative methodology. Collected data included individual and group interviews, course documents, artifacts, and preservice teaching portfolios. Innovative aspects of this integrated mathematics and science elementary methods course included standards-based instruction with immediate access to field experiences. Grade-level teams of preservice and inservice teachers planned and implemented lessons in mathematics and science for elementary students. An on-site, portable classroom building served as a mathematics and science teaching and learning laboratory. A four-stage analysis was performed, revealing significant patterns of learning. An ecosystem of learning within a constructivist learning environment was identified to contain three systems: the university system; the school system; and the cohort of learners system. A mega system for the construction of teacher knowledge was revealed in the final analysis. Learning venues were discovered to be the conduits of learning in a situated learning context. Analysis and synthesis of data revealed an extensive acquisition of teacher knowledge and pedagogical content knowledge through identified learning components. Patience, flexibility, and communication were identified as necessities for successful teaching. Learning components included: collaboration with inservice teachers; implementation of discovery learning and hands-on/minds-on learning; small groupwork; lesson planning; classroom management; and application of standards-based instruction. Prolonged, extensive classroom involvement provided familiarity with the ability levels of elementary students. Gains in positive attitudes and confidence in teaching mathematics and science were identified as direct results of this experience. This may be attributed to the immersion in the school-based setting (hands-on) and the standards-based approach (minds-on) methods course. The results are written in case study form using thick description with an emphasis on preservice teachers.

Linear decentralized learning control

NASA Technical Reports Server (NTRS)

Lee, Soo C.; Longman, Richard W.; Phan, Minh

1992-01-01

The new field of learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this task. The simplest forms of learning control are based on the same concept as integral control, but operating in the domain of the repetitions of the task. This paper studies the use of such controllers in a decentralized system, such as a robot with the controller for each link acting independently. The basic result of the paper is to show that stability of the learning controllers for all subsystems when the coupling between subsystems is turned off, assures stability of the decentralized learning in the coupled system, provided that the sample time in the digital learning controller is sufficiently short.

Outcomes from Building System Courseware for Teaching and Testing in a Discipline-Based Human Structure Curriculum

ERIC Educational Resources Information Center

Reilly, Frank D.

2011-01-01

This study investigated the educational benefits of system-based lecture notes and interactive learning objects in a peripheral nervous system component of a traditional first-year medical school human anatomy course. The impetus for the investigation was anecdotal evidence suggesting enhanced learner satisfaction with the learning resources.…

GenieTutor: A Computer Assisted Second-Language Learning System Based on Semantic and Grammar Correctness Evaluations

ERIC Educational Resources Information Center

Kwon, Oh-Woog; Lee, Kiyoung; Kim, Young-Kil; Lee, Yunkeun

2015-01-01

This paper introduces a Dialog-Based Computer-Assisted second-Language Learning (DB-CALL) system using semantic and grammar correctness evaluations and the results of its experiment. While the system dialogues with English learners about a given topic, it automatically evaluates the grammar and content properness of their English utterances, then…

Proposing a Web-Based Tutorial System to Teach Malay Language Braille Code to the Sighted

ERIC Educational Resources Information Center

Wah, Lee Lay; Keong, Foo Kok

2010-01-01

The "e-KodBrailleBM Tutorial System" is a web-based tutorial system which is specially designed to teach, facilitate and support the learning of Malay Language Braille Code to individuals who are sighted. The targeted group includes special education teachers, pre-service teachers, and parents. Learning Braille code involves memorisation…

Supporting Self-Regulated Personalised Learning through Competence-Based Knowledge Space Theory

ERIC Educational Resources Information Center

Steiner, Christina M.; Nussbaumer, Alexander; Albert, Dietrich

2009-01-01

This article presents two current research trends in e-learning that at first sight appear to compete. Competence-Based Knowledge Space Theory (CBKST) provides a knowledge representation framework which, since its invention by Doignon & Falmagne, has been successfully applied in various e-learning systems (for example, Adaptive Learning with…

Work-Based Learning and Work-Integrated Learning: Fostering Engagement with Employers

ERIC Educational Resources Information Center

Atkinson, Georgina

2016-01-01

Work-based learning and the inclusion of the world of work into tertiary students' learning lie at the heart of the Australian vocational education and training (VET) system. Traditionally this has been through apprenticeships and traineeships, which have a strong focus on "on-the-job" training, but also through "work-oriented"…

A FAQ-Based e-Learning Environment to Support Japanese Language Learning

ERIC Educational Resources Information Center

Liu, Yuqin; Yin, Chengjiu; Ogata, Hiroaki; Qiao, Guojun; Yano, Yoneo

2011-01-01

In traditional classes, having many questions from learners is important because these questions indicate difficult points for learners and for teachers. This paper proposes a FAQ-based e-Learning environment to support Japanese language learning that focuses on learner questions. This knowledge sharing system enables learners to interact and…

One Giant Leap for Categorizers: One Small Step for Categorization Theory

PubMed Central

Smith, J. David; Ell, Shawn W.

2015-01-01

We explore humans’ rule-based category learning using analytic approaches that highlight their psychological transitions during learning. These approaches confirm that humans show qualitatively sudden psychological transitions during rule learning. These transitions contribute to the theoretical literature contrasting single vs. multiple category-learning systems, because they seem to reveal a distinctive learning process of explicit rule discovery. A complete psychology of categorization must describe this learning process, too. Yet extensive formal-modeling analyses confirm that a wide range of current (gradient-descent) models cannot reproduce these transitions, including influential rule-based models (e.g., COVIS) and exemplar models (e.g., ALCOVE). It is an important theoretical conclusion that existing models cannot explain humans’ rule-based category learning. The problem these models have is the incremental algorithm by which learning is simulated. Humans descend no gradient in rule-based tasks. Very different formal-modeling systems will be required to explain humans’ psychology in these tasks. An important next step will be to build a new generation of models that can do so. PMID:26332587

A Comparison of the neural correlates that underlie rule-based and information-integration category learning.

PubMed

Carpenter, Kathryn L; Wills, Andy J; Benattayallah, Abdelmalek; Milton, Fraser

2016-10-01

The influential competition between verbal and implicit systems (COVIS) model proposes that category learning is driven by two competing neural systems-an explicit, verbal, system, and a procedural-based, implicit, system. In the current fMRI study, participants learned either a conjunctive, rule-based (RB), category structure that is believed to engage the explicit system, or an information-integration category structure that is thought to preferentially recruit the implicit system. The RB and information-integration category structures were matched for participant error rate, the number of relevant stimulus dimensions, and category separation. Under these conditions, considerable overlap in brain activation, including the prefrontal cortex, basal ganglia, and the hippocampus, was found between the RB and information-integration category structures. Contrary to the predictions of COVIS, the medial temporal lobes and in particular the hippocampus, key regions for explicit memory, were found to be more active in the information-integration condition than in the RB condition. No regions were more activated in RB than information-integration category learning. The implications of these results for theories of category learning are discussed. Hum Brain Mapp 37:3557-3574, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Students Learn Systems-Based Care and Facilitate System Change as Stakeholders in a Free Clinic Experience

ERIC Educational Resources Information Center

Colbert, Colleen Y.; Ogden, Paul E.; Lowe, Darla; Moffitt, Michael J.

2010-01-01

Systems-based practice (SBP) is rarely taught or evaluated during medical school, yet is one of the required competencies once students enter residency. We believe Texas A&M College of Medicine students learn about systems issues informally, as they care for patients at a free clinic in Temple, TX. The mandatory free clinic rotation is part of…

Evaluating Web-Based Learning Systems

ERIC Educational Resources Information Center

Pergola, Teresa M.; Walters, L. Melissa

2011-01-01

Accounting educators continuously seek ways to effectively integrate instructional technology into accounting coursework as a means to facilitate active learning environments and address the technology-driven learning preferences of the current generation of students. Most accounting textbook publishers now provide interactive, web-based learning…

Web-Education Systems in Europe. ZIFF Papiere.

ERIC Educational Resources Information Center

Paulsen, Morten; Keegan, Desmond; Dias, Ana; Dias, Paulo; Pimenta, Pedro; Fritsch, Helmut; Follmer, Holger; Micincova, Maria; Olsen, Gro-Anett

This document contains the following papers on Web-based education systems in Europe: (1) "European Experiences with Learning Management Systems" (Morten Flate Paulsen and Desmond Keegan); (2) "Online Education Systems: Definition of Terms" (Morten Flate Paulsen); (3) "Learning Management Systems (LMS) Used in Southern…

Designing a Syntax-Based Retrieval System for Supporting Language Learning

ERIC Educational Resources Information Center

Tsao, Nai-Lung; Kuo, Chin-Hwa; Wible, David; Hung, Tsung-Fu

2009-01-01

In this paper, we propose a syntax-based text retrieval system for on-line language learning and use a fast regular expression search engine as its main component. Regular expression searches provide more scalable querying and search results than keyword-based searches. However, without a well-designed index scheme, the execution time of regular…

I CAN Learn[R] Pre-Algebra and Algebra. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2009

2009-01-01

The I CAN Learn[R] Education System is an interactive, self-paced, mastery-based software system that includes the I CAN Learn[R] Fundamentals of Math (5th-6th grade math) curriculum, the I CAN Learn[R] Pre-Algebra curriculum, and the I CAN Learn[R] Algebra curriculum. College algebra credit is also available to students in participating schools…

Deep learning in mammography and breast histology, an overview and future trends.

PubMed

Hamidinekoo, Azam; Denton, Erika; Rampun, Andrik; Honnor, Kate; Zwiggelaar, Reyer

2018-07-01

Recent improvements in biomedical image analysis using deep learning based neural networks could be exploited to enhance the performance of Computer Aided Diagnosis (CAD) systems. Considering the importance of breast cancer worldwide and the promising results reported by deep learning based methods in breast imaging, an overview of the recent state-of-the-art deep learning based CAD systems developed for mammography and breast histopathology images is presented. In this study, the relationship between mammography and histopathology phenotypes is described, which takes biological aspects into account. We propose a computer based breast cancer modelling approach: the Mammography-Histology-Phenotype-Linking-Model, which develops a mapping of features/phenotypes between mammographic abnormalities and their histopathological representation. Challenges are discussed along with the potential contribution of such a system to clinical decision making and treatment management. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Applying ergonomics to systems: some documented "lessons learned".

PubMed

Hendrick, Hal W

2008-07-01

Based on evidence accumulated during the author's 45 years of professional experience, the author presents 23 important "lessons learned" regarding applying ergonomics to systems. Documented results from reported cases or other evidence are presented to validate each of these practical learning points.

NAWeb 2000: Web-Based Learning - On Track! International Conference on Web-Based Learning. (6th, New Brunswick, Canada, October 14-17, 2000).

ERIC Educational Resources Information Center

Hall, Richard., Ed.

This proceedings of the Sixth International Conference on Web-Based Learning, NAWeb 2000, includes the following papers: "Is a Paradigm Shift Required To Effectively Teach Web-Based Instruction?"; "Issues in Courseware Reuse for a Web-Based Information System"; "The Digital Curriculum Database: Meeting the Needs of Industry and the Challenge of…

Version Control in Project-Based Learning

ERIC Educational Resources Information Center

Milentijevic, Ivan; Ciric, Vladimir; Vojinovic, Oliver

2008-01-01

This paper deals with the development of a generalized model for version control systems application as a support in a range of project-based learning methods. The model is given as UML sequence diagram and described in detail. The proposed model encompasses a wide range of different project-based learning approaches by assigning a supervisory…

Group Formation Based on Learning Styles: Can It Improve Students' Teamwork?

ERIC Educational Resources Information Center

Kyprianidou, Maria; Demetriadis, Stavros; Tsiatsos, Thrasyvoulos; Pombortsis, Andreas

2012-01-01

This work explores the impact of teacher-led heterogeneous group formation on students' teamwork, based on students' learning styles. Fifty senior university students participated in a project-based course with two key organizational features: first, a web system (PEGASUS) was developed to help students identify their learning styles and…

The Effect of Virtual versus Traditional Learning in Achieving Competency-Based Skills

ERIC Educational Resources Information Center

Mosalanejad, Leili; Shahsavari, Sakine; Sobhanian, Saeed; Dastpak, Mehdi

2012-01-01

Background: By rapid developing of the network technology, the internet-based learning methods are substituting the traditional classrooms making them expand to the virtual network learning environment. The purpose of this study was to determine the effectiveness of virtual systems on competency-based skills of first-year nursing students.…

Project Based Learning in Multi-Grade Class

ERIC Educational Resources Information Center

Ciftci, Sabahattin; Baykan, Ayse Aysun

2013-01-01

The purpose of this study is to evaluate project based learning in multi-grade classes. This study, based on a student-centered learning approach, aims to analyze students' and parents' interpretations. The study was done in a primary village school belonging to the Centre of Batman, already adapting multi-grade classes in their education system,…

Combining Adaptive Hypermedia with Project and Case-Based Learning

ERIC Educational Resources Information Center

Papanikolaou, Kyparisia; Grigoriadou, Maria

2009-01-01

In this article we investigate the design of educational hypermedia based on constructivist learning theories. According to the principles of project and case-based learning we present the design rational of an Adaptive Educational Hypermedia system prototype named MyProject; learners working with MyProject undertake a project and the system…

Migrating Learning Management Systems in Higher Education: Faculty Members' Perceptions of System Usage and Training When Transitioning from Blackboard Vista to Desire2Learn

ERIC Educational Resources Information Center

Rucker, Ryan D.; Frass, Lydia R.

2017-01-01

This study examined a migration from Blackboard Vista to Desire2Learn (D2L) within a multiuniversity system. Faculty members' perceptions from two of the systems' colleges were evaluated using a questionnaire based on Davis' technology acceptance model. Researchers analyzed responses for differences in system usage experience of faculty and in…

Problem-Based Learning in Teaching Chemistry: Enthalpy Changes in Systems

ERIC Educational Resources Information Center

Ayyildiz, Yildizay; Tarhan, Leman

2018-01-01

Background: Problem-based learning (PBL) as a teaching strategy has recently become quite widespread in especially chemistry classes. Research has found that students, from elementary through college, have many alternative conceptions regarding "enthalpy changes in systems." Although there are several studies focused on identifying…

Supporting online learning with games

NASA Astrophysics Data System (ADS)

Yao, JingTao; Kim, DongWon; Herbert, Joseph P.

2007-04-01

This paper presents a study on Web-based learning support systems that is enhanced with two major subsystems: a Web-based learning game and a learning-oriented Web search. The Internet and theWeb may be considered as a first resource for students seeking for information and help. However, much of the information available online is not related to the course contents or is wrong in the worse case. The search subsystem aims to provide students with precise, relative and adaptable documents about certain courses or classes. Therefore, students do not have to spend time to verify the relationship of documents to the class. The learning game subsystem stimulates students to study, enables students to review their studies and to perform self-evaluation through a Web-based learning game such as a treasure hunt game. During the challenge and entertaining learning and evaluation process, it is hoped that students will eventually understand and master the course concepts easily. The goal of developing such a system is to provide students with an efficient and effective learning environment.

A fuzzy classifier system for process control

NASA Technical Reports Server (NTRS)

Karr, C. L.; Phillips, J. C.

1994-01-01

A fuzzy classifier system that discovers rules for controlling a mathematical model of a pH titration system was developed by researchers at the U.S. Bureau of Mines (USBM). Fuzzy classifier systems successfully combine the strengths of learning classifier systems and fuzzy logic controllers. Learning classifier systems resemble familiar production rule-based systems, but they represent their IF-THEN rules by strings of characters rather than in the traditional linguistic terms. Fuzzy logic is a tool that allows for the incorporation of abstract concepts into rule based-systems, thereby allowing the rules to resemble the familiar 'rules-of-thumb' commonly used by humans when solving difficult process control and reasoning problems. Like learning classifier systems, fuzzy classifier systems employ a genetic algorithm to explore and sample new rules for manipulating the problem environment. Like fuzzy logic controllers, fuzzy classifier systems encapsulate knowledge in the form of production rules. The results presented in this paper demonstrate the ability of fuzzy classifier systems to generate a fuzzy logic-based process control system.

Memory and learning behaviors mimicked in nanogranular SiO2-based proton conductor gated oxide-based synaptic transistors

NASA Astrophysics Data System (ADS)

Wan, Chang Jin; Zhu, Li Qiang; Zhou, Ju Mei; Shi, Yi; Wan, Qing

2013-10-01

In neuroscience, signal processing, memory and learning function are established in the brain by modifying ionic fluxes in neurons and synapses. Emulation of memory and learning behaviors of biological systems by nanoscale ionic/electronic devices is highly desirable for building neuromorphic systems or even artificial neural networks. Here, novel artificial synapses based on junctionless oxide-based protonic/electronic hybrid transistors gated by nanogranular phosphorus-doped SiO2-based proton-conducting films are fabricated on glass substrates by a room-temperature process. Short-term memory (STM) and long-term memory (LTM) are mimicked by tuning the pulse gate voltage amplitude. The LTM process in such an artificial synapse is due to the proton-related interfacial electrochemical reaction. Our results are highly desirable for building future neuromorphic systems or even artificial networks via electronic elements.In neuroscience, signal processing, memory and learning function are established in the brain by modifying ionic fluxes in neurons and synapses. Emulation of memory and learning behaviors of biological systems by nanoscale ionic/electronic devices is highly desirable for building neuromorphic systems or even artificial neural networks. Here, novel artificial synapses based on junctionless oxide-based protonic/electronic hybrid transistors gated by nanogranular phosphorus-doped SiO2-based proton-conducting films are fabricated on glass substrates by a room-temperature process. Short-term memory (STM) and long-term memory (LTM) are mimicked by tuning the pulse gate voltage amplitude. The LTM process in such an artificial synapse is due to the proton-related interfacial electrochemical reaction. Our results are highly desirable for building future neuromorphic systems or even artificial networks via electronic elements. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr02987e

A service based adaptive U-learning system using UX.

PubMed

Jeong, Hwa-Young; Yi, Gangman

2014-01-01

In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users' tailored materials according to their learning style. That is, we analyzed the user's data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques.

A Service Based Adaptive U-Learning System Using UX

PubMed Central

Jeong, Hwa-Young

2014-01-01

In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users' tailored materials according to their learning style. That is, we analyzed the user's data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques. PMID:25147832

Trend of E-Learning: The Service Mashup

ERIC Educational Resources Information Center

Yen, Neil Y.; Shih, Timothy K.; Jin, Qun; Hsu, Hui-Huang; Chao, Louis R.

2010-01-01

With the improvement of internet technologies and multimedia resources, traditional learning has been replaced by distance learning, web-based learning or others' e-learning learning styles. According to distance learning, there are many research organizations and companies who make efforts in developing the relevant systems. But they lack…

The Interactivity Effect in Multimedia Learning

ERIC Educational Resources Information Center

Evans, Chris; Gibbons, Nicola J.

2007-01-01

The aim of this study was to determine whether the addition of interactivity to a computer-based learning package enhances the learning process. A sample of 33 (22 male and 11 female) undergraduates on a Business and Management degree used a multimedia system to learn about the operation of a bicycle pump. The system consisted of a labelled…

Combining Collaborative Learning with Learning Management Systems in Teaching Programming Language

ERIC Educational Resources Information Center

Cavus, Nadire; Uzunboylu, Huseyin; Ibrahim, Dogan

2006-01-01

The development of collaborative studies in learning has led to a renewed interest in the field of web-based education. In this experimental study, a highly interactive and collaborative teaching environment was created using Moodle, a learning management system with two types of Collaborative Tools (CTs): Standard CT and Advanced CT to create a…

On the Push-Pull Mobile Learning of Electric Welding

ERIC Educational Resources Information Center

Chung, Chih-Chao; Dzan, Wei-Yuan; Cheng, Yuh-Ming; Lou, Shi-Jer

2017-01-01

This study aims to explore the learning effects and attitudes of students in the course electric welding practice in a university of science and technology to which the push-pull technology-based mobile learning system is applied. In this study, the push-pull technology is adopted to establish a mobile learning system and develop the Push-pull…

The Mirror Neuron System and Observational Learning: Implications for the Effectiveness of Dynamic Visualizations

ERIC Educational Resources Information Center

van Gog, Tamara; Paas, Fred; Marcus, Nadine; Ayres, Paul; Sweller, John

2009-01-01

Learning by observing and imitating others has long been recognized as constituting a powerful learning strategy for humans. Recent findings from neuroscience research, more specifically on the mirror neuron system, begin to provide insight into the neural bases of learning by observation and imitation. These findings are discussed here, along…

An Effective Profile Based Video Browsing System for e-Learning

ERIC Educational Resources Information Center

Premaratne, S. C.; Karunaratna, D. D.; Hewagamage, K. P.

2007-01-01

E-learning has acquired a prime place in many discussions recently. A number of research efforts around the world are trying to enhance education and training through improving e-learning facilities. This paper briefly explains one such attempt aimed at designing a system to support video clips in e-learning and explains how profiles of the…

Effective Trust-Aware E-learning Recommender System Based on Learning Styles and Knowledge Levels

ERIC Educational Resources Information Center

Dwivedi, Pragya; Bharadwaj, Kamal K.

2013-01-01

In the age of information explosion, e-learning recommender systems (ELRSs) have emerged as the most essential tool to deliver personalized learning resources to learners. Due to enormous amount of information on the web, learner faces problem in searching right information. ELRSs deal with the problem of information overload effectively and…

A Multi-Modal Digital Game-Based Learning Environment for Hospitalized Children with Chronic Illnesses.

ERIC Educational Resources Information Center

Chin, Jui-Chih; Tsuei, Mengping

2014-01-01

The aim of this study was to explore the digital game-based learning for children with chronic illnesses in the hospital settings. The design-based research and qualitative methods were applied. Three eight-year-old children with leukemia participated in this study. In the first phase, the multi-user game-based learning system was developed and…

A review on machine learning principles for multi-view biological data integration.

PubMed

Li, Yifeng; Wu, Fang-Xiang; Ngom, Alioune

2018-03-01

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.

Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

ERIC Educational Resources Information Center

Thompson, Kate; Reimann, Peter

2010-01-01

A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

Data-Driven H∞ Control for Nonlinear Distributed Parameter Systems.

PubMed

Luo, Biao; Huang, Tingwen; Wu, Huai-Ning; Yang, Xiong

2015-11-01

The data-driven H∞ control problem of nonlinear distributed parameter systems is considered in this paper. An off-policy learning method is developed to learn the H∞ control policy from real system data rather than the mathematical model. First, Karhunen-Loève decomposition is used to compute the empirical eigenfunctions, which are then employed to derive a reduced-order model (ROM) of slow subsystem based on the singular perturbation theory. The H∞ control problem is reformulated based on the ROM, which can be transformed to solve the Hamilton-Jacobi-Isaacs (HJI) equation, theoretically. To learn the solution of the HJI equation from real system data, a data-driven off-policy learning approach is proposed based on the simultaneous policy update algorithm and its convergence is proved. For implementation purpose, a neural network (NN)- based action-critic structure is developed, where a critic NN and two action NNs are employed to approximate the value function, control, and disturbance policies, respectively. Subsequently, a least-square NN weight-tuning rule is derived with the method of weighted residuals. Finally, the developed data-driven off-policy learning approach is applied to a nonlinear diffusion-reaction process, and the obtained results demonstrate its effectiveness.

Experimental Verification of Electric Drive Technologies Based on Artificial Intelligence Tools

NASA Technical Reports Server (NTRS)

Rubaai, Ahmed; Ricketts, Daniel; Kotaru, Raj; Thomas, Robert; Noga, Donald F. (Technical Monitor); Kankam, Mark D. (Technical Monitor)

2000-01-01

In this report, a fully integrated prototype of a flight servo control system is successfully developed and implemented using brushless dc motors. The control system is developed by the fuzzy logic theory, and implemented with a multilayer neural network. First, a neural network-based architecture is introduced for fuzzy logic control. The characteristic rules and their membership functions of fuzzy systems are represented as the processing nodes in the neural network structure. The network structure and the parameter learning are performed simultaneously and online in the fuzzy-neural network system. The structure learning is based on the partition of input space. The parameter learning is based on the supervised gradient decent method, using a delta adaptation law. Using experimental setup, the performance of the proposed control system is evaluated under various operating conditions. Test results are presented and discussed in the report. The proposed learning control system has several advantages, namely, simple structure and learning capability, robustness and high tracking performance and few nodes at hidden layers. In comparison with the PI controller, the proposed fuzzy-neural network system can yield a better dynamic performance with shorter settling time, and without overshoot. Experimental results have shown that the proposed control system is adaptive and robust in responding to a wide range of operating conditions. In summary, the goal of this study is to design and implement-advanced servosystems to actuate control surfaces for flight vehicles, namely, aircraft and helicopters, missiles and interceptors, and mini- and micro-air vehicles.

A SCORM Thin Client Architecture for E-Learning Systems Based on Web Services

ERIC Educational Resources Information Center

Casella, Giovanni; Costagliola, Gennaro; Ferrucci, Filomena; Polese, Giuseppe; Scanniello, Giuseppe

2007-01-01

In this paper we propose an architecture of e-learning systems characterized by the use of Web services and a suitable middleware component. These technical infrastructures allow us to extend the system with new services as well as to integrate and reuse heterogeneous software e-learning components. Moreover, they let us better support the…

Clustering and Profiling Students According to Their Interactions with an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Harley, Jason M.; Trevors, Gregory J.; Azevedo, Roger

2013-01-01

In this paper, we present the results obtained using a clustering algorithm (Expectation-Maximization) on data collected from 106 college students learning about the circulatory system with MetaTutor, an agent-based Intelligent Tutoring System (ITS) designed to foster self-regulated learning (SRL). The three extracted clusters were validated and…

Improved Modeling of Intelligent Tutoring Systems Using Ant Colony Optimization

ERIC Educational Resources Information Center

Rastegarmoghadam, Mahin; Ziarati, Koorush

2017-01-01

Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…

Natural Interaction Based Online Military Boxing Learning System

ERIC Educational Resources Information Center

Yang, Chenglei; Wang, Lu; Sun, Bing; Yin, Xu; Wang, Xiaoting; Liu, Li; Lu, Lin

2013-01-01

Military boxing, a kind of Chinese martial arts, is widespread and health beneficial. In this paper, the authors introduce a military boxing learning system realized by 3D motion capture, Web3D and 3D interactive technologies. The interactions with the system are natural and intuitive. Users can observe and learn the details of each action of the…

Development of a Diagnostic and Remedial Learning System Based on an Enhanced Concept--Effect Model

ERIC Educational Resources Information Center

Panjaburees, Patcharin; Triampo, Wannapong; Hwang, Gwo-Jen; Chuedoung, Meechoke; Triampo, Darapond

2013-01-01

With the rapid advances in computer technology during recent years, researchers have demonstrated the pivotal influences of computer-assisted diagnostic systems on student learning performance improvement. This research aims to develop a Diagnostic and Remedial Learning System (DRLS) for an algebra course in a Thai lower secondary school context…

Experiences of Two Multidisciplinary Team Members of Systemic Consultations in a Community Learning Disability Service

ERIC Educational Resources Information Center

Johnson, Clair; Viljoen, Nina

2017-01-01

Background: Systemic approaches can be useful in working with people with learning disabilities and their network. The evidence base for these approaches within the field of learning disabilities, however, is currently limited. Materials and Methods: This article presents part of a service evaluation of systemic consultations in a Community…

CAI: A Model for the Comparison and Selection of Integrated Learning Systems in Large School Districts.

ERIC Educational Resources Information Center

Resta, Paul E.; Rost, Paul

The Albuquerque (New Mexico) Public Schools conducted a three-year study of integrated computer-based learning systems, including WICAT, Dolphin, PLATO, CCC, and DEGEM. Through cooperation with the Education Consolidation Improvement Act Chapter 1 program, four large integrated learning systems (ILS) were purchased and studied. They were installed…

Analytical learning and term-rewriting systems

NASA Technical Reports Server (NTRS)

Laird, Philip; Gamble, Evan

1990-01-01

Analytical learning is a set of machine learning techniques for revising the representation of a theory based on a small set of examples of that theory. When the representation of the theory is correct and complete but perhaps inefficient, an important objective of such analysis is to improve the computational efficiency of the representation. Several algorithms with this purpose have been suggested, most of which are closely tied to a first order logical language and are variants of goal regression, such as the familiar explanation based generalization (EBG) procedure. But because predicate calculus is a poor representation for some domains, these learning algorithms are extended to apply to other computational models. It is shown that the goal regression technique applies to a large family of programming languages, all based on a kind of term rewriting system. Included in this family are three language families of importance to artificial intelligence: logic programming, such as Prolog; lambda calculus, such as LISP; and combinatorial based languages, such as FP. A new analytical learning algorithm, AL-2, is exhibited that learns from success but is otherwise quite different from EBG. These results suggest that term rewriting systems are a good framework for analytical learning research in general, and that further research should be directed toward developing new techniques.

Game-powered machine learning

PubMed Central

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-01-01

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the “wisdom of the crowds.” Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., “funky jazz with saxophone,” “spooky electronica,” etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data. PMID:22460786

Game-powered machine learning.

PubMed

Barrington, Luke; Turnbull, Douglas; Lanckriet, Gert

2012-04-24

Searching for relevant content in a massive amount of multimedia information is facilitated by accurately annotating each image, video, or song with a large number of relevant semantic keywords, or tags. We introduce game-powered machine learning, an integrated approach to annotating multimedia content that combines the effectiveness of human computation, through online games, with the scalability of machine learning. We investigate this framework for labeling music. First, a socially-oriented music annotation game called Herd It collects reliable music annotations based on the "wisdom of the crowds." Second, these annotated examples are used to train a supervised machine learning system. Third, the machine learning system actively directs the annotation games to collect new data that will most benefit future model iterations. Once trained, the system can automatically annotate a corpus of music much larger than what could be labeled using human computation alone. Automatically annotated songs can be retrieved based on their semantic relevance to text-based queries (e.g., "funky jazz with saxophone," "spooky electronica," etc.). Based on the results presented in this paper, we find that actively coupling annotation games with machine learning provides a reliable and scalable approach to making searchable massive amounts of multimedia data.

Application of Project-Based Learning (PBL) to the Teaching of Electrical Power Systems Engineering

ERIC Educational Resources Information Center

Hosseinzadeh, N.; Hesamzadeh, M. R.

2012-01-01

Project-based learning (PBL), a learning environment in which projects drive learning, has been successfully used in various courses in the educational programs of different disciplines. However, concerns have been raised as to the breadth of the content covered and, in particular, whether PBL can be applied to specialized subjects without…

Educational Data Mining and Problem-Based Learning

ERIC Educational Resources Information Center

Walldén, Sari; Mäkinen, Erkki

2014-01-01

This paper considers the use of log data provided by learning management systems when studying whether students obey the problem-based learning (PBL) method. Log analysis turns out to be a valuable tool in measuring the use of the learning material of interest. It gives reliable figures concerning not only the number of use sessions but also the…

How to Represent Adaptation in e-Learning with IMS Learning Design

ERIC Educational Resources Information Center

Burgos, Daniel; Tattersall, Colin; Koper, Rob

2007-01-01

Adaptation in e-learning has been an important research topic for the last few decades in computer-based education. In adaptivity the behaviour of the user triggers some actions in the system that guides the learning process. In adaptability, the user makes changes and takes decisions. Progressing from computer-based training and adaptive…

A New Design Approach to Game-Based Learning

ERIC Educational Resources Information Center

Larsen, Lasse Juel

2012-01-01

This paper puts forward a new design perspective for game-based learning. The general idea is to abandon the long sought-after dream of designing a closed learning system, where students in both primary and secondary school could learn--without the interference of teachers--whatever subject they wanted while sitting in front of a computer. This…

Shared Values as Anchors of a Learning Community: A Case Study in Information Systems Design

ERIC Educational Resources Information Center

Giordano, Daniela

2004-01-01

This paper examines the role in both individual and organizational learning of the system of values sustained by a community undertaking a design task. The discussion is based on the results of a longitudinal study of a community of novice information system designers supported by a Web-based shared design memory which allows reuse of design…

MHEG Based Distance Learning System on Information Superhighway.

ERIC Educational Resources Information Center

Lee, SeiHoon; Yoon, KyungSeob; Wang, ChangJong

As the need for distance education grows, requirements for the development of high-speed network-based real-time distance learning systems increases. MHEG-5 is the fifth part of the MHEG (Multimedia and Hypermedia information coding Experts Group) standard, and it defines a final-form representation for application interchange. This paper…

Assessing and Analyzing the Effects of WBLP on Learning Processes and Achievements: Using the Electronic Portfolio for Authentic Assessment on University Students' Learning.

ERIC Educational Resources Information Center

Chang, Chi-Cheng

A Web-Based Learning Portfolio (WBLP) was evaluated through practical teaching process to understand if the WBLP system helps students to grasp the learning process and enhances learning outcomes. The evaluation results reveal that this WBLP system has been more useful for students to obtain the feedback from other students than from their…

An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

PubMed

Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

2018-01-01

A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

Motion Recognition and Modifying Motion Generation for Imitation Robot Based on Motion Knowledge Formation

NASA Astrophysics Data System (ADS)

Okuzawa, Yuki; Kato, Shohei; Kanoh, Masayoshi; Itoh, Hidenori

A knowledge-based approach to imitation learning of motion generation for humanoid robots and an imitative motion generation system based on motion knowledge learning and modification are described. The system has three parts: recognizing, learning, and modifying parts. The first part recognizes an instructed motion distinguishing it from the motion knowledge database by the continuous hidden markov model. When the motion is recognized as being unfamiliar, the second part learns it using locally weighted regression and acquires a knowledge of the motion. When a robot recognizes the instructed motion as familiar or judges that its acquired knowledge is applicable to the motion generation, the third part imitates the instructed motion by modifying a learned motion. This paper reports some performance results: the motion imitation of several radio gymnastics motions.

Brain computer interface learning for systems based on electrocorticography and intracortical microelectrode arrays.

PubMed

Hiremath, Shivayogi V; Chen, Weidong; Wang, Wei; Foldes, Stephen; Yang, Ying; Tyler-Kabara, Elizabeth C; Collinger, Jennifer L; Boninger, Michael L

2015-01-01

A brain-computer interface (BCI) system transforms neural activity into control signals for external devices in real time. A BCI user needs to learn to generate specific cortical activity patterns to control external devices effectively. We call this process BCI learning, and it often requires significant effort and time. Therefore, it is important to study this process and develop novel and efficient approaches to accelerate BCI learning. This article reviews major approaches that have been used for BCI learning, including computer-assisted learning, co-adaptive learning, operant conditioning, and sensory feedback. We focus on BCIs based on electrocorticography and intracortical microelectrode arrays for restoring motor function. This article also explores the possibility of brain modulation techniques in promoting BCI learning, such as electrical cortical stimulation, transcranial magnetic stimulation, and optogenetics. Furthermore, as proposed by recent BCI studies, we suggest that BCI learning is in many ways analogous to motor and cognitive skill learning, and therefore skill learning should be a useful metaphor to model BCI learning.

Learning and tuning fuzzy logic controllers through reinforcements.

PubMed

Berenji, H R; Khedkar, P

1992-01-01

A method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. It is shown that: the generalized approximate-reasoning-based intelligent control (GARIC) architecture learns and tunes a fuzzy logic controller even when only weak reinforcement, such as a binary failure signal, is available; introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. The GARIC architecture is applied to a cart-pole balancing system and demonstrates significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

A Classification Model and an Open E-Learning System Based on Intuitionistic Fuzzy Sets for Instructional Design Concepts

ERIC Educational Resources Information Center

Güyer, Tolga; Aydogdu, Seyhmus

2016-01-01

This study suggests a classification model and an e-learning system based on this model for all instructional theories, approaches, models, strategies, methods, and technics being used in the process of instructional design that constitutes a direct or indirect resource for educational technology based on the theory of intuitionistic fuzzy sets…

Applications of a Time Sequence Mechanism in the Simulation Cases of a Web-Based Medical Problem-Based Learning System

ERIC Educational Resources Information Center

Chen, Lih-Shyang; Cheng, Yuh-Ming; Weng, Sheng-Feng; Chen, Yong-Guo; Lin, Chyi-Her

2009-01-01

The prevalence of Internet applications nowadays has led many medical schools and centers to incorporate computerized Problem-Based Learning (PBL) methods into their training curricula. However, many of these PBL systems do not truly reflect the situations which practitioners may actually encounter in a real medical environment, and hence their…

Using a web-based system for the continuous distance education in cytopathology.

PubMed

Stergiou, Nikolaos; Georgoulakis, Giannis; Margari, Niki; Aninos, Dionisios; Stamataki, Melina; Stergiou, Efi; Pouliakis, Abraam; Karakitsos, Petros

2009-12-01

The evolution of information technologies and telecommunications has made the World Wide Web a low cost and easily accessible tool for the dissemination of information and knowledge. Continuous Medical Education (CME) sites dedicated in cytopathology field are rather poor, they do not succeed in following the constant changes and lack the ability of providing cytopathologists with a dynamic learning environment, adaptable to the development of cytopathology. Learning methods including skills such as decision making, reasoning and problem solving are critical in the development of such a learning environment. The objectives of this study are (1) to demonstrate on the basis of a web-based training system the successful application of traditional learning theories and methods and (2) to effectively evaluate users' perception towards the educational program, using a combination of observers, theories and methods. Trainees are given the opportunity to browse through the educational material, collaborate in synchronous and asynchronous mode, practice their skills through problems and tasks and test their knowledge using the self-evaluation tool. On the other hand, the trainers are responsible for editing learning material, attending students' progress and organizing the problem-based and task-based scenarios. The implementation of the web-based training system is based on the three-tier architecture and uses an Apache Tomcat web server and a MySQL database server. By December 2008, CytoTrainer's learning environment contains two courses in cytopathology: Gynaecological Cytology and Thyroid Cytology offering about 2000 digital images and 20 case sessions. Our evaluation method is a combination of both qualitative and quantitative approaches to explore how the various parts of the system and students' attitudes work together. Trainees approved of the course's content, methodology and learning activities. The triangulation of evaluation methods revealed that the training program is suitable for the continuous distance education in cytopathology and that it has improved the trainees' skills in diagnostic cytopathology. The web-based training system can be successfully involved in the continuous distance education in cytopathology. It provides the opportunity to access learning material from any place at any time and supports the acquisition of diagnostic knowledge.

Addressing Learning Disabilities with UDL and Technology: Strategic Reader

ERIC Educational Resources Information Center

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…

MISESS: Web-Based Examination, Evaluation, and Guidance

ERIC Educational Resources Information Center

Tanrikulu, Zuhal

2006-01-01

Many universities are reevaluating their traditional educational methods and providing pedagogical material through the Internet. Some Web-based systems offer a constructionist learning environment, for example, where students can learn by designing their own objects. Providing effective, convenient technology to support learning is important, and…

The Development of Inquiry Learning Materials to Complete Content Life System Organization in Junior High School Students

NASA Astrophysics Data System (ADS)

Mayasari, F.; Raharjo; Supardi, Z. A. I.

2018-01-01

This research aims to develop the material eligibility to complete the inquiry learning of student in the material organization system of junior high school students. Learning materials developed include syllabi, lesson plans, students’ textbook, worksheets, and learning achievement test. This research is the developmental research which employ Dick and Carey model to develop learning material. The experiment was done in Junior High School 4 Lamongan regency using One Group Pretest-Posttest Design. The data collection used validation, observation, achievement test, questionnaire administration, and documentation. Data analysis techniques used quantitative and qualitative descriptive.The results showed that the developed learning material was valid and can be used. Learning activity accomplished with good category, where student activities were observed. The aspects of attitudes were observed during the learning process are honest, responsible, and confident. Student learning achievement gained an average of 81, 85 in complete category, with N-Gain 0, 75 for a high category. The activities and student response to learning was very well categorized. Based on the results, this researcher concluded that the device classified as feasible of inquiry-based learning (valid, practical, and effective) system used on the material organization of junior high school students.

Modelling and Optimizing Mathematics Learning in Children

ERIC Educational Resources Information Center

Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus

2013-01-01

This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…

Employer Involvement in Work-Based Learning Programs.

ERIC Educational Resources Information Center

Bailey, Thomas; Hughes, Katherine

A 3-year research project focused on whether sufficient numbers of employers could be recruited to create a national school-to-work system with a substantial work-based learning component as called for by the 1994 School-to-Work Opportunities Act. Research methods were as follows: case studies of 12 work-based learning programs at 9 sites located…

Evaluating Listening and Speaking Skills in a Mobile Game-Based Learning Environment with Situational Contexts

ERIC Educational Resources Information Center

Hwang, Wu-Yuin; Shih, Timothy K.; Ma, Zhao-Heng; Shadiev, Rustam; Chen, Shu-Yu

2016-01-01

Game-based learning activities that facilitate students' listening and speaking skills were designed in this study. To participate in learning activities, students in the control group used traditional methods, while students in the experimental group used a mobile system. In our study, we looked into the feasibility of mobile game-based learning…

A Personalized Recommendation-Based Mobile Learning Approach to Improving the Reading Performance of EFL Students

ERIC Educational Resources Information Center

Hsu, Ching-Kun; Hwang, Gwo-Jen; Chang, Chih-Kai

2013-01-01

In this paper, a personalized recommendation-based mobile language learning approach is proposed. A mobile learning system has been developed based on the approach by providing a reading material recommendation mechanism for guiding EFL (English as Foreign Language) students to read articles that match their preferences and knowledge levels, and a…

Model-based learning and the contribution of the orbitofrontal cortex to the model-free world

PubMed Central

McDannald, Michael A.; Takahashi, Yuji K.; Lopatina, Nina; Pietras, Brad W.; Jones, Josh L.; Schoenbaum, Geoffrey

2012-01-01

Learning is proposed to occur when there is a discrepancy between reward prediction and reward receipt. At least two separate systems are thought to exist: one in which predictions are proposed to be based on model-free or cached values; and another in which predictions are model-based. A basic neural circuit for model-free reinforcement learning has already been described. In the model-free circuit the ventral striatum (VS) is thought to supply a common-currency reward prediction to midbrain dopamine neurons that compute prediction errors and drive learning. In a model-based system, predictions can include more information about an expected reward, such as its sensory attributes or current, unique value. This detailed prediction allows for both behavioral flexibility and learning driven by changes in sensory features of rewards alone. Recent evidence from animal learning and human imaging suggests that, in addition to model-free information, the VS also signals model-based information. Further, there is evidence that the orbitofrontal cortex (OFC) signals model-based information. Here we review these data and suggest that the OFC provides model-based information to this traditional model-free circuitry and offer possibilities as to how this interaction might occur. PMID:22487030

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.

PubMed

Han, Xu; Kim, Jung-jae; Kwoh, Chee Keong

2016-01-01

Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for state-of-the-art supervised learning systems. Active learning is to choose the most informative documents for the supervised learning in order to reduce the amount of required manual annotations. Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. They also did not consider the evidence of event participants, which might be a clue for the presence of events in unlabeled documents. Moreover, the confidence scores of events produced by event extraction systems are not reliable for ranking documents in terms of informativity for supervised learning. We here propose a novel committee-based active learning method that supports multi-event extraction tasks and employs a new statistical method for informativity estimation instead of using the confidence scores from event extraction systems. Our method is based on a committee of two systems as follows: We first employ an event extraction system to filter potential false negatives among unlabeled documents, from which the system does not extract any event. We then develop a statistical method to rank the potential false negatives of unlabeled documents 1) by using a language model that measures the probabilities of the expression of multiple events in documents and 2) by using a named entity recognition system that locates the named entities that can be event arguments (e.g. proteins). The proposed method further deals with unknown words in test data by using word similarity measures. We also apply our active learning method for the task of named entity recognition. We evaluate the proposed method against the BioNLP Shared Tasks datasets, and show that our method can achieve better performance than such previous methods as entropy and Gibbs error based methods and a conventional committee-based method. We also show that the incorporation of named entity recognition into the active learning for event extraction and the unknown word handling further improve the active learning method. In addition, the adaptation of the active learning method into named entity recognition tasks also improves the document selection for manual annotation of named entities.

KBGIS-2: A knowledge-based geographic information system

NASA Technical Reports Server (NTRS)

Smith, T.; Peuquet, D.; Menon, S.; Agarwal, P.

1986-01-01

The architecture and working of a recently implemented knowledge-based geographic information system (KBGIS-2) that was designed to satisfy several general criteria for the geographic information system are described. The system has four major functions that include query-answering, learning, and editing. The main query finds constrained locations for spatial objects that are describable in a predicate-calculus based spatial objects language. The main search procedures include a family of constraint-satisfaction procedures that use a spatial object knowledge base to search efficiently for complex spatial objects in large, multilayered spatial data bases. These data bases are represented in quadtree form. The search strategy is designed to reduce the computational cost of search in the average case. The learning capabilities of the system include the addition of new locations of complex spatial objects to the knowledge base as queries are answered, and the ability to learn inductively definitions of new spatial objects from examples. The new definitions are added to the knowledge base by the system. The system is currently performing all its designated tasks successfully, although currently implemented on inadequate hardware. Future reports will detail the performance characteristics of the system, and various new extensions are planned in order to enhance the power of KBGIS-2.

Building Knowledge Structures by Testing Helps Children With Mathematical Learning Difficulty.

PubMed

Zhang, Yiyun; Zhou, Xinlin

2016-01-01

Mathematical learning difficulty (MLD) is prevalent in the development of mathematical abilities. Previous interventions for children with MLD have focused on number sense or basic mathematical skills. This study investigated whether mathematical performance of fifth grade children with MLD could be improved by developing knowledge structures by testing using a web-based curriculum learning system. A total of 142 children with MLD were recruited; half of the children were in the experimental group (using the system), and the other half were in the control group (not using the system). The children were encouraged to use the web-based learning system at home for at least a 15-min session, at least once a week, for one and a half months. The mean accumulated time of testing on the system for children in the experimental group was 56.2 min. Children in the experimental group had significantly higher scores on their final mathematical examination compared to the control group. The results suggest that web-based curriculum learning through testing that promotes the building of knowledge structures for a mathematical course was helpful for children with MLD. © Hammill Institute on Disabilities 2014.

Agile Development of Various Computational Power Adaptive Web-Based Mobile-Learning Software Using Mobile Cloud Computing

ERIC Educational Resources Information Center

Zadahmad, Manouchehr; Yousefzadehfard, Parisa

2016-01-01

Mobile Cloud Computing (MCC) aims to improve all mobile applications such as m-learning systems. This study presents an innovative method to use web technology and software engineering's best practices to provide m-learning functionalities hosted in a MCC-learning system as service. Components hosted by MCC are used to empower developers to create…

International-Domestic Student Differences in Learning: Use of Classroom Response Systems in China versus in Canada

ERIC Educational Resources Information Center

Fan, Hong; Power, Jeffrey W.; Song, Xiaofei

2017-01-01

This study compares the impact of audience response systems (clickers) on the learning experience and classroom behavior of Chinese and Canadian students. Based on differences in student learning styles, which are rooted in the differences in national cultures, we predict that clicker technology will result in a more positive learning experience,…

The Effect of Feedback Delay and Feedback Type on Perceptual Category Learning: The Limits of Multiple Systems

ERIC Educational Resources Information Center

Dunn, John C.; Newell, Ben R.; Kalish, Michael L.

2012-01-01

Evidence that learning rule-based (RB) and information-integration (II) category structures can be dissociated across different experimental variables has been used to support the view that such learning is supported by multiple learning systems. Across 4 experiments, we examined the effects of 2 variables, the delay between response and feedback…

Speech-Enabled Tools for Augmented Interaction in E-Learning Applications

ERIC Educational Resources Information Center

Selouani, Sid-Ahmed A.; Lê, Tang-Hô; Benahmed, Yacine; O'Shaughnessy, Douglas

2008-01-01

This article presents systems that use speech technology, to emulate the one-on-one interaction a student can get from a virtual instructor. A web-based learning tool, the Learn IN Context (LINC+) system, designed and used in a real mixed-mode learning context for a computer (C++ language) programming course taught at the Université de Moncton…

Engineering Lessons Learned and Systems Engineering Applications

NASA Technical Reports Server (NTRS)

Gill, Paul S.; Garcia, Danny; Vaughan, William W.

2005-01-01

Systems Engineering is fundamental to good engineering, which in turn depends on the integration and application of engineering lessons learned and technical standards. Thus, good Systems Engineering also depends on systems engineering lessons learned from within the aerospace industry being documented and applied. About ten percent of the engineering lessons learned documented in the NASA Lessons Learned Information System are directly related to Systems Engineering. A key issue associated with lessons learned datasets is the communication and incorporation of this information into engineering processes. Systems Engineering has been defined (EINIS-632) as "an interdisciplinary approach encompassing the entire technical effort to evolve and verify an integrated and life-cycle balanced set of system people, product, and process solutions that satisfy customer needs". Designing reliable space-based systems has always been a goal for NASA, and many painful lessons have been learned along the way. One of the continuing functions of a system engineer is to compile development and operations "lessons learned" documents and ensure their integration into future systems development activities. They can produce insights and information for risk identification identification and characterization. on a new project. Lessons learned files from previous projects are especially valuable in risk

Knowledge acquisition and learning process description in context of e-learning

NASA Astrophysics Data System (ADS)

Kiselev, B. G.; Yakutenko, V. A.; Yuriev, M. A.

2017-01-01

This paper investigates the problem of design of e-learning and MOOC systems. It describes instructional design-based approaches to e-learning systems design: IMS Learning Design, MISA and TELOS. To solve this problem we present Knowledge Field of Educational Environment with Competence boundary conditions - instructional engineering method for self-learning systems design. It is based on the simplified TELOS approach and enables a user to create their individual learning path by choosing prerequisite and target competencies. The paper provides the ontology model for the described instructional engineering method, real life use cases and the classification of the presented model. Ontology model consists of 13 classes and 15 properties. Some of them are inherited from Knowledge Field of Educational Environment and some are new and describe competence boundary conditions and knowledge validation objects. Ontology model uses logical constraints and is described using OWL 2 standard. To give TELOS users better understanding of our approach we list mapping between TELOS and KFEEC.

Assessing eLearning Systems Success in Nigeria: An Application of the DeLone and McLean Information Systems Success Model

ERIC Educational Resources Information Center

Yakubu, M. Nasiru; Dasuki, Salihu Ibrahim

2018-01-01

Aim/Purpose: This study is based on the DeLone and McLean's Information Systems Success (D&M ISS) model, which was modified to determine the success factors responsible for the acceptance of an e-learning system called Canvas by students of a Nigerian University. Background: The adoption of eLearning has been under studied within the context…

The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

PubMed

Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

2016-02-01

Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

Designing a Knowledge Mobilization Strategy: Leading through Influence

ERIC Educational Resources Information Center

Reid, Steven

2015-01-01

As district leaders consider professional learning opportunities for educators, mobilizing new thought and actions across an entire system is a vexing challenge. Classroom-based learning may unfortunately be viewed as juxtaposed to district-based learning. It becomes essential for district leaders to develop knowledge mobilization strategies which…

Learning from Multiple Collaborating Intelligent Tutors: An Agent-based Approach.

ERIC Educational Resources Information Center

Solomos, Konstantinos; Avouris, Nikolaos

1999-01-01

Describes an open distributed multi-agent tutoring system (MATS) and discusses issues related to learning in such open environments. Topics include modeling a one student-many teachers approach in a computer-based learning context; distributed artificial intelligence; implementation issues; collaboration; and user interaction. (Author/LRW)

Leadership for Nursing Work-Based Mobile Learning

ERIC Educational Resources Information Center

Fahlman, Dorothy

2016-01-01

This paper reflects on work-based mobile learning in the Canadian healthcare system for registered nurses' ongoing skills development and continuing professional development. It calls on distributed leadership to address the organizational contextual factors for making this mode of learning sustainable. [For the full proceedings, see ED571335.

Tryout and Evaluation of Prototype LMS (Learning Mastery System) Training System Under Exclusive Use Agreement.

ERIC Educational Resources Information Center

McDonald, Cheryl; Hylton, John A.

In 1970-1971 Learning Mastery System (LMS) materials were made available to schools within the state of California under an Exclusive Use Agreement. The LMS is a set of materials and procedures prepared by the Southwest Regional Laboratory (SWRL) as an objectives-based framework to assist in managing the learning activities of existing reading…

Blogs and Social Network Sites as Activity Systems: Exploring Adult Informal Learning Process through Activity Theory Framework

ERIC Educational Resources Information Center

Heo, Gyeong Mi; Lee, Romee

2013-01-01

This paper uses an Activity Theory framework to explore adult user activities and informal learning processes as reflected in their blogs and social network sites (SNS). Using the assumption that a web-based space is an activity system in which learning occurs, typical features of the components were investigated and each activity system then…

Mobile Learning Environment with Short Messaging Service: Application to a Campus Environment in a Developing Country

ERIC Educational Resources Information Center

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

2013-01-01

Purpose: The purpose of this paper is to discuss how to integrate secure, open-source and mobile-based system with the Moodle learning management system (MLMS) then describe the implementation of a campus-wide mobile learning environment with short messaging system (SMS) and how this platform is incorporated with the student's learning…

An overview of game-based learning in building services engineering education

NASA Astrophysics Data System (ADS)

Alanne, Kari

2016-03-01

To ensure proper competence development and short graduation times for engineering students, it is essential that the study motivation is encouraged by new learning methods. In game-based learning, the learner's engagement is increased and learning is made meaningful by applying game-like features such as competition and rewarding through virtual promotions or achievement badges. In this paper, the state of the art of game-based learning in building services engineering education at university level is reviewed and discussed. A systematic literature review indicates that educational games have been reported in the field of related disciplines, such as mechanical and civil engineering. The development of system-level educational games that realistically simulate work life in building services engineering is still in its infancy. Novel rewarding practices and more comprehensive approaches entailing the state-of-the-art information tools such as building information modelling, geographic information systems, building management systems and augmented reality are needed in the future.

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

NASA Technical Reports Server (NTRS)

Chen, Alexander Y.

1990-01-01

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations.

Finding accurate frontiers: A knowledge-intensive approach to relational learning

NASA Technical Reports Server (NTRS)

Pazzani, Michael; Brunk, Clifford

1994-01-01

An approach to analytic learning is described that searches for accurate entailments of a Horn Clause domain theory. A hill-climbing search, guided by an information based evaluation function, is performed by applying a set of operators that derive frontiers from domain theories. The analytic learning system is one component of a multi-strategy relational learning system. We compare the accuracy of concepts learned with this analytic strategy to concepts learned with an analytic strategy that operationalizes the domain theory.

The Role of Age and Executive Function in Auditory Category Learning

PubMed Central

Reetzke, Rachel; Maddox, W. Todd; Chandrasekaran, Bharath

2015-01-01

Auditory categorization is a natural and adaptive process that allows for the organization of high-dimensional, continuous acoustic information into discrete representations. Studies in the visual domain have identified a rule-based learning system that learns and reasons via a hypothesis-testing process that requires working memory and executive attention. The rule-based learning system in vision shows a protracted development, reflecting the influence of maturing prefrontal function on visual categorization. The aim of the current study is two-fold: (a) to examine the developmental trajectory of rule-based auditory category learning from childhood through adolescence, into early adulthood; and (b) to examine the extent to which individual differences in rule-based category learning relate to individual differences in executive function. Sixty participants with normal hearing, 20 children (age range, 7–12), 21 adolescents (age range, 13–19), and 19 young adults (age range, 20–23), learned to categorize novel dynamic ripple sounds using trial-by-trial feedback. The spectrotemporally modulated ripple sounds are considered the auditory equivalent of the well-studied Gabor patches in the visual domain. Results revealed that auditory categorization accuracy improved with age, with young adults outperforming children and adolescents. Computational modeling analyses indicated that the use of the task-optimal strategy (i.e. a conjunctive rule-based learning strategy) improved with age. Notably, individual differences in executive flexibility significantly predicted auditory category learning success. The current findings demonstrate a protracted development of rule-based auditory categorization. The results further suggest that executive flexibility coupled with perceptual processes play important roles in successful rule-based auditory category learning. PMID:26491987

Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

NASA Astrophysics Data System (ADS)

Ibrahim, Wael Refaat Anis

The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an alarm is instigated predicting the advent of system abnormal operation. The incoming data could be compared to previous trends as well as matched to trends developed through computer simulations and stored using fuzzy learning.

Control of magnetic bearing systems via the Chebyshev polynomial-based unified model (CPBUM) neural network.

PubMed

Jeng, J T; Lee, T T

2000-01-01

A Chebyshev polynomial-based unified model (CPBUM) neural network is introduced and applied to control a magnetic bearing systems. First, we show that the CPBUM neural network not only has the same capability of universal approximator, but also has faster learning speed than conventional feedforward/recurrent neural network. It turns out that the CPBUM neural network is more suitable in the design of controller than the conventional feedforward/recurrent neural network. Second, we propose the inverse system method, based on the CPBUM neural networks, to control a magnetic bearing system. The proposed controller has two structures; namely, off-line and on-line learning structures. We derive a new learning algorithm for each proposed structure. The experimental results show that the proposed neural network architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

Using Websites Wisely

ERIC Educational Resources Information Center

Coiro, Julie; Fogleman, Jay

2011-01-01

Online resources can deepen student learning--if teachers design the right tasks and learner supports. In this article, the authors look at instructional websites teachers will want to use with their students. They focus on three types of web-based learning environments--(1) informational reading systems; (2) interactive learning systems; and (3)…

Embodied Perspective Taking in Learning about Complex Systems

ERIC Educational Resources Information Center

Soylu, Firat; Holbert, Nathan; Brady, Corey; Wilensky, Uri

2017-01-01

In this paper we present a learning design approach that leverages perspective-taking to help students learn about complex systems. We define perspective-taking as projecting one's identity onto external entities (both animate and inanimate) in an effort to predict and anticipate events based on ecological cues, to automatically sense the…

Course Evaluation: Reconfigurations for Learning with Learning Management Systems

ERIC Educational Resources Information Center

Park, Ji Yong

2014-01-01

The introduction of online delivery platforms such as learning management systems (LMS) in tertiary education has changed the methods and modes of curriculum delivery and communication. While course evaluation methods have also changed from paper-based in-class-administered methods to largely online-administered methods, the data collection…

Cost Optimization in E-Learning-Based Education Systems: Implementation and Learning Sequence

ERIC Educational Resources Information Center

Fazlollahtabar, Hamed; Yousefpoor, Narges

2009-01-01

Increasing the effectiveness of e-learning has become one of the most practically and theoretically important issues within both educational engineering and information system fields. The development of information technologies has contributed to growth in online training as an important education method. The online training environment enables…

A Web-Based Virtual Classroom System Model

ERIC Educational Resources Information Center

Adewale, Olumide S.; Ibam, Emmanuel O.; Alese, B. K.

2012-01-01

The population of students all over the world is growing without a proportionate increase in teaching/learning resources/infrastructure. There is also much quest for learning in an environment that provides equal opportunities to all learners. The need to provide an equal opportunity learning environment that will hitherto improve the system of…

Development and Evaluation of HawkLearn: A Next Generation Learning Management System

ERIC Educational Resources Information Center

Round, Kimberlee L.

2013-01-01

Cloud-based computing in higher education has the potential to impact institutions on a myriad of fronts, including technology governance, flexibility, financial, and intellectual property. As the demand for blended and online education increases, institutions are considering expedient approaches to implementing learning management systems (LMSs).…

Process Systems Engineering Education: Learning by Research

ERIC Educational Resources Information Center

Abbas, A.; Alhammadi, H. Y.; Romagnoli, J. A.

2009-01-01

In this paper, we discuss our approach in teaching the final-year course Process Systems Engineering. Students are given ownership of the course by transferring to them the responsibility of learning. A project-based group environment stimulates learning while solving a real engineering problem. We discuss postgraduate student involvement and how…

Differential impact of relevant and irrelevant dimension primes on rule-based and information-integration category learning.

PubMed

Grimm, Lisa R; Maddox, W Todd

2013-11-01

Research has identified multiple category-learning systems with each being "tuned" for learning categories with different task demands and each governed by different neurobiological systems. Rule-based (RB) classification involves testing verbalizable rules for category membership while information-integration (II) classification requires the implicit learning of stimulus-response mappings. In the first study to directly test rule priming with RB and II category learning, we investigated the influence of the availability of information presented at the beginning of the task. Participants viewed lines that varied in length, orientation, and position on the screen, and were primed to focus on stimulus dimensions that were relevant or irrelevant to the correct classification rule. In Experiment 1, we used an RB category structure, and in Experiment 2, we used an II category structure. Accuracy and model-based analyses suggested that a focus on relevant dimensions improves RB task performance later in learning while a focus on an irrelevant dimension improves II task performance early in learning. © 2013.

The organization of an autonomous learning system

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1988-01-01

The organization of systems that learn from experience is examined, human beings and animals being prime examples of such systems. How is their information processing organized. They build an internal model of the world and base their actions on the model. The model is dynamic and predictive, and it includes the systems' own actions and their effects. In modeling such systems, a large pattern of features represents a moment of the system's experience. Some of the features are provided by the system's senses, some control the system's motors, and the rest have no immediate external significance. A sequence of such patterns then represents the system's experience over time. By storing such sequences appropriately in memory, the system builds a world model based on experience. In addition to the essential function of memory, fundamental roles are played by a sensory system that makes raw information about the world suitable for memory storage and by a motor system that affects the world. The relation of sensory and motor systems to the memory is discussed, together with how favorable actions can be learned and unfavorable actions can be avoided. Results in classical learning theory are explained in terms of the model, more advanced forms of learning are discussed, and the relevance of the model to the frame problem of robotics is examined.

Student Cognitive Difficulties and Mental Model Development of Complex Earth and Environmental Systems

NASA Astrophysics Data System (ADS)

Sell, K.; Herbert, B.; Schielack, J.

2004-05-01

Students organize scientific knowledge and reason about environmental issues through manipulation of mental models. The nature of the environmental sciences, which are focused on the study of complex, dynamic systems, may present cognitive difficulties to students in their development of authentic, accurate mental models of environmental systems. The inquiry project seeks to develop and assess the coupling of information technology (IT)-based learning with physical models in order to foster rich mental model development of environmental systems in geoscience undergraduate students. The manipulation of multiple representations, the development and testing of conceptual models based on available evidence, and exposure to authentic, complex and ill-constrained problems were the components of investigation utilized to reach the learning goals. Upper-level undergraduate students enrolled in an environmental geology course at Texas A&M University participated in this research which served as a pilot study. Data based on rubric evaluations interpreted by principal component analyses suggest students' understanding of the nature of scientific inquiry is limited and the ability to cross scales and link systems proved problematic. Results categorized into content knowledge and cognition processes where reasoning, critical thinking and cognitive load were driving factors behind difficulties in student learning. Student mental model development revealed multiple misconceptions and lacked complexity and completeness to represent the studied systems. Further, the positive learning impacts of the implemented modules favored the physical model over the IT-based learning projects, likely due to cognitive load issues. This study illustrates the need to better understand student difficulties in solving complex problems when using IT, where the appropriate scaffolding can then be implemented to enhance student learning of the earth system sciences.

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

ERIC Educational Resources Information Center

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…

Student Reflections as Artifacts of Self-Regulatory Behaviors for Learning: A Tale of Two Courses

ERIC Educational Resources Information Center

Bigenho, Christopher William

2011-01-01

The rapid growth of online and blended learning environments in both higher education and K-12, along with the development of innovative game based, narrative driven, problem-based learning (PBL) systems known as Alternate Reality Games (AltRG), has led to the need to understand student's abilities to self-regulate their learning behaviors…

Designing Online Learning. Knowledge Series: A Topical, Start-Up Guide to Distance Education Practice and Delivery.

ERIC Educational Resources Information Center

Mishra, Sanjaya

The term "online learning" refers to an Internet- or intranet-based teaching and learning system designed for World Wide Web-based delivery without face-to-face contact between teacher and learner. The Internet is the backbone of online learning. The following media are available to designers of online courses: text; graphics and images;…

Intelligent fault-tolerant controllers

NASA Technical Reports Server (NTRS)

Huang, Chien Y.

1987-01-01

A system with fault tolerant controls is one that can detect, isolate, and estimate failures and perform necessary control reconfiguration based on this new information. Artificial intelligence (AI) is concerned with semantic processing, and it has evolved to include the topics of expert systems and machine learning. This research represents an attempt to apply AI to fault tolerant controls, hence, the name intelligent fault tolerant control (IFTC). A generic solution to the problem is sought, providing a system based on logic in addition to analytical tools, and offering machine learning capabilities. The advantages are that redundant system specific algorithms are no longer needed, that reasonableness is used to quickly choose the correct control strategy, and that the system can adapt to new situations by learning about its effects on system dynamics.

Can model-free reinforcement learning explain deontological moral judgments?

PubMed

Ayars, Alisabeth

2016-05-01

Dual-systems frameworks propose that moral judgments are derived from both an immediate emotional response, and controlled/rational cognition. Recently Cushman (2013) proposed a new dual-system theory based on model-free and model-based reinforcement learning. Model-free learning attaches values to actions based on their history of reward and punishment, and explains some deontological, non-utilitarian judgments. Model-based learning involves the construction of a causal model of the world and allows for far-sighted planning; this form of learning fits well with utilitarian considerations that seek to maximize certain kinds of outcomes. I present three concerns regarding the use of model-free reinforcement learning to explain deontological moral judgment. First, many actions that humans find aversive from model-free learning are not judged to be morally wrong. Moral judgment must require something in addition to model-free learning. Second, there is a dearth of evidence for central predictions of the reinforcement account-e.g., that people with different reinforcement histories will, all else equal, make different moral judgments. Finally, to account for the effect of intention within the framework requires certain assumptions which lack support. These challenges are reasonable foci for future empirical/theoretical work on the model-free/model-based framework. Copyright © 2016 Elsevier B.V. All rights reserved.

The Process, Dialogues, and Attitudes of Vocational Engineering High School Students in a Web Problem-Based Learning (WPBL) System

ERIC Educational Resources Information Center

Tseng, Kuo-Hung; Chang, Chi-Cheng; Lou, Shi-Jer

2012-01-01

This study aims to explore how high school students collaboratively solve problems in a web problem-based learning (WPBL) system in an 8-week digital logic course using discourse analysis. Employing in-depth interviews, this study also investigated the students' attitudes toward the WPBL system. The number of teaching assistants' responses had a…

Underspecification-Based Grammatical Feedback Generation Tailored to the Learner's Current Acquisition Level in an e-Learning System for German as Second Language

ERIC Educational Resources Information Center

Harbusch, Karin; Cameran, Christel-Joy; Härtel, Johannes

2014-01-01

We present a new feedback strategy implemented in a natural language generation-based e-learning system for German as a second language (L2). Although the system recognizes a large proportion of the grammar errors in learner-produced written sentences, its automatically generated feedback only addresses errors against rules that are relevant at…

Artificial neural networks and approximate reasoning for intelligent control in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

Fuzzy Q-Learning for Generalization of Reinforcement Learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

Fuzzy Q-Learning, introduced earlier by the author, is an extension of Q-Learning into fuzzy environments. GARIC is a methodology for fuzzy reinforcement learning. In this paper, we introduce GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Q-Learning and at the local level, each agent learns and operates based on GARIC. GARIC-Q improves the speed and applicability of Fuzzy Q-Learning through generalization of input space by using fuzzy rules and bridges the gap between Q-Learning and rule based intelligent systems.

Aberrant Learning Achievement Detection Based on Person-Fit Statistics in Personalized e-Learning Systems

ERIC Educational Resources Information Center

Liu, Ming-Tsung; Yu, Pao-Ta

2011-01-01

A personalized e-learning service provides learning content to fit learners' individual differences. Learning achievements are influenced by cognitive as well as non-cognitive factors such as mood, motivation, interest, and personal styles. This paper proposes the Learning Caution Indexes (LCI) to detect aberrant learning patterns. The philosophy…

Dual-learning systems during speech category learning

PubMed Central

Chandrasekaran, Bharath; Yi, Han-Gyol; Maddox, W. Todd

2013-01-01

Dual-systems models of visual category learning posit the existence of an explicit, hypothesis-testing ‘reflective’ system, as well as an implicit, procedural-based ‘reflexive’ system. The reflective and reflexive learning systems are competitive and neurally dissociable. Relatively little is known about the role of these domain-general learning systems in speech category learning. Given the multidimensional, redundant, and variable nature of acoustic cues in speech categories, our working hypothesis is that speech categories are learned reflexively. To this end, we examined the relative contribution of these learning systems to speech learning in adults. Native English speakers learned to categorize Mandarin tone categories over 480 trials. The training protocol involved trial-by-trial feedback and multiple talkers. Experiment 1 and 2 examined the effect of manipulating the timing (immediate vs. delayed) and information content (full vs. minimal) of feedback. Dual-systems models of visual category learning predict that delayed feedback and providing rich, informational feedback enhance reflective learning, while immediate and minimally informative feedback enhance reflexive learning. Across the two experiments, our results show feedback manipulations that targeted reflexive learning enhanced category learning success. In Experiment 3, we examined the role of trial-to-trial talker information (mixed vs. blocked presentation) on speech category learning success. We hypothesized that the mixed condition would enhance reflexive learning by not allowing an association between talker-related acoustic cues and speech categories. Our results show that the mixed talker condition led to relatively greater accuracies. Our experiments demonstrate that speech categories are optimally learned by training methods that target the reflexive learning system. PMID:24002965

Automatic multi-organ segmentation using learning-based segmentation and level set optimization.

PubMed

Kohlberger, Timo; Sofka, Michal; Zhang, Jingdan; Birkbeck, Neil; Wetzl, Jens; Kaftan, Jens; Declerck, Jérôme; Zhou, S Kevin

2011-01-01

We present a novel generic segmentation system for the fully automatic multi-organ segmentation from CT medical images. Thereby we combine the advantages of learning-based approaches on point cloud-based shape representation, such a speed, robustness, point correspondences, with those of PDE-optimization-based level set approaches, such as high accuracy and the straightforward prevention of segment overlaps. In a benchmark on 10-100 annotated datasets for the liver, the lungs, and the kidneys we show that the proposed system yields segmentation accuracies of 1.17-2.89 mm average surface errors. Thereby the level set segmentation (which is initialized by the learning-based segmentations) contributes with an 20%-40% increase in accuracy.

Rethinking Health Professions Education through the Lens of Interprofessional Practice and Education

ERIC Educational Resources Information Center

Brandt, Barbara F.

2018-01-01

Using adult learning principles, health professions educators are well positioned to create interprofessional learning systems for collaborative, team-based practice in the transforming health-care system.

A Customizable Language Learning Support System Using Ontology-Driven Engine

ERIC Educational Resources Information Center

Wang, Jingyun; Mendori, Takahiko; Xiong, Juan

2013-01-01

This paper proposes a framework for web-based language learning support systems designed to provide customizable pedagogical procedures based on the analysis of characteristics of both learner and course. This framework employs a course-centered ontology and a teaching method ontology as the foundation for the student model, which includes learner…

Effects of Web-Based Interactive Modules on Engineering Students' Learning Motivations

ERIC Educational Resources Information Center

Bai, Haiyan; Aman, Amjad; Xu, Yunjun; Orlovskaya, Nina; Zhou, Mingming

2016-01-01

The purpose of this study is to assess the impact of a newly developed modules, Interactive Web-Based Visualization Tools for Gluing Undergraduate Fuel Cell Systems Courses system (IGLU), on learning motivations of engineering students using two samples (n[subscript 1] = 144 and n[subscript 2] = 135) from senior engineering classes. The…

Integrating Soft Skill Competencies through Project-Based Learning across the Information Systems Curriculum

ERIC Educational Resources Information Center

Woodward, Belle S.; Sendall, Patricia; Ceccucci, Wendy

2010-01-01

Contemporary Information Systems graduates will be more marketable in the workplace upon graduation if they have combined competencies in both technical and soft skills: interpersonal communication, teamwork, time management, planning and organizational skills. Team and project-based learning can be used to incorporate soft skill competencies with…

Evaluating Automatic Speech Recognition-Based Language Learning Systems: A Case Study

ERIC Educational Resources Information Center

van Doremalen, Joost; Boves, Lou; Colpaert, Jozef; Cucchiarini, Catia; Strik, Helmer

2016-01-01

The purpose of this research was to evaluate a prototype of an automatic speech recognition (ASR)-based language learning system that provides feedback on different aspects of speaking performance (pronunciation, morphology and syntax) to students of Dutch as a second language. We carried out usability reviews, expert reviews and user tests to…

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

ERIC Educational Resources Information Center

Schumacher, Thomas

2015-01-01

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

Automated Classification of Radiology Reports for Acute Lung Injury: Comparison of Keyword and Machine Learning Based Natural Language Processing Approaches.

PubMed

Solti, Imre; Cooke, Colin R; Xia, Fei; Wurfel, Mark M

2009-11-01

This paper compares the performance of keyword and machine learning-based chest x-ray report classification for Acute Lung Injury (ALI). ALI mortality is approximately 30 percent. High mortality is, in part, a consequence of delayed manual chest x-ray classification. An automated system could reduce the time to recognize ALI and lead to reductions in mortality. For our study, 96 and 857 chest x-ray reports in two corpora were labeled by domain experts for ALI. We developed a keyword and a Maximum Entropy-based classification system. Word unigram and character n-grams provided the features for the machine learning system. The Maximum Entropy algorithm with character 6-gram achieved the highest performance (Recall=0.91, Precision=0.90 and F-measure=0.91) on the 857-report corpus. This study has shown that for the classification of ALI chest x-ray reports, the machine learning approach is superior to the keyword based system and achieves comparable results to highest performing physician annotators.

Automated Classification of Radiology Reports for Acute Lung Injury: Comparison of Keyword and Machine Learning Based Natural Language Processing Approaches

PubMed Central

Solti, Imre; Cooke, Colin R.; Xia, Fei; Wurfel, Mark M.

2010-01-01

This paper compares the performance of keyword and machine learning-based chest x-ray report classification for Acute Lung Injury (ALI). ALI mortality is approximately 30 percent. High mortality is, in part, a consequence of delayed manual chest x-ray classification. An automated system could reduce the time to recognize ALI and lead to reductions in mortality. For our study, 96 and 857 chest x-ray reports in two corpora were labeled by domain experts for ALI. We developed a keyword and a Maximum Entropy-based classification system. Word unigram and character n-grams provided the features for the machine learning system. The Maximum Entropy algorithm with character 6-gram achieved the highest performance (Recall=0.91, Precision=0.90 and F-measure=0.91) on the 857-report corpus. This study has shown that for the classification of ALI chest x-ray reports, the machine learning approach is superior to the keyword based system and achieves comparable results to highest performing physician annotators. PMID:21152268

Validating the ACE Model for Evaluating Student Performance Using a Teaching-Learning Process Based on Computational Modeling Systems

ERIC Educational Resources Information Center

Louzada, Alexandre Neves; Elia, Marcos da Fonseca; Sampaio, Fábio Ferrentini; Vidal, Andre Luiz Pestana

2014-01-01

The aim of this work is to adapt and test, in a Brazilian public school, the ACE model proposed by Borkulo for evaluating student performance as a teaching-learning process based on computational modeling systems. The ACE model is based on different types of reasoning involving three dimensions. In addition to adapting the model and introducing…

Ontology-Based Learner Categorization through Case Based Reasoning and Fuzzy Logic

ERIC Educational Resources Information Center

Sarwar, Sohail; García-Castro, Raul; Qayyum, Zia Ul; Safyan, Muhammad; Munir, Rana Faisal

2017-01-01

Learner categorization has a pivotal role in making e-learning systems a success. However, learner characteristics exploited at abstract level of granularity by contemporary techniques cannot categorize the learners effectively. In this paper, an architecture of e-learning framework has been presented that exploits the machine learning based…

Learning Disabilities: A Neurobiological Perspective in Humans.

ERIC Educational Resources Information Center

Bonnet, Kenneth A.

1989-01-01

The mechanisms of both language-based and non-language-based learning disabilities are presented within the framework of central nervous system development and the compromises to that development that arise from genetic, hormonal, antibody, medication, and postnatal compromises. Also reviewed is the need for a taxonomy of learning disabilities.…

ICCE/ICCAI 2000 Full & Short Papers (Web-Based Learning).

ERIC Educational Resources Information Center

2000

This document contains full and short papers on World Wide Web-based learning from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction). Topics covered include: design and development of CAL (Computer Assisted Learning) systems; design and development of WBI (Web-Based…

Creating Effective Web-Based Learning Environments: Relevant Research and Practice

ERIC Educational Resources Information Center

Wijekumar, Kay

2005-01-01

Web-based learning environments are a great asset only if they are designed well and used as intended. The urgency to create courses in response to the growing demand for online learning has resulted in a hurried push to drop PowerPoint notes into Web-based course management systems (WBCMSs), devise an electronic quiz, put together a few…

A presentation system for just-in-time learning in radiology.

PubMed

Kahn, Charles E; Santos, Amadeu; Thao, Cheng; Rock, Jayson J; Nagy, Paul G; Ehlers, Kevin C

2007-03-01

There is growing interest in bringing medical educational materials to the point of care. We sought to develop a system for just-in-time learning in radiology. A database of 34 learning modules was derived from previously published journal articles. Learning objectives were specified for each module, and multiple-choice test items were created. A web-based system-called TEMPO-was developed to allow radiologists to select and view the learning modules. Web services were used to exchange clinical context information between TEMPO and the simulated radiology work station. Preliminary evaluation was conducted using the System Usability Scale (SUS) questionnaire. TEMPO identified learning modules that were relevant to the age, sex, imaging modality, and body part or organ system of the patient being viewed by the radiologist on the simulated clinical work station. Users expressed a high degree of satisfaction with the system's design and user interface. TEMPO enables just-in-time learning in radiology, and can be extended to create a fully functional learning management system for point-of-care learning in radiology.

Adaptive learning and control for MIMO system based on adaptive dynamic programming.

PubMed

Fu, Jian; He, Haibo; Zhou, Xinmin

2011-07-01

Adaptive dynamic programming (ADP) is a promising research field for design of intelligent controllers, which can both learn on-the-fly and exhibit optimal behavior. Over the past decades, several generations of ADP design have been proposed in the literature, which have demonstrated many successful applications in various benchmarks and industrial applications. While many of the existing researches focus on multiple-inputs-single-output system with steepest descent search, in this paper we investigate a generalized multiple-input-multiple-output (GMIMO) ADP design for online learning and control, which is more applicable to a wide range of practical real-world applications. Furthermore, an improved weight-updating algorithm based on recursive Levenberg-Marquardt methods is presented and embodied in the GMIMO approach to improve its performance. Finally, we test the performance of this approach based on a practical complex system, namely, the learning and control of the tension and height of the looper system in a hot strip mill. Experimental results demonstrate that the proposed approach can achieve effective and robust performance.

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

PubMed

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.

An expert system shell for inferring vegetation characteristics: The learning system (tasks C and D)

NASA Technical Reports Server (NTRS)

Harrison, P. Ann; Harrison, Patrick R.

1992-01-01

This report describes the implementation of a learning system that uses a data base of historical cover type reflectance data taken at different solar zenith angles and wavelengths to learn class descriptions of classes of cover types. It has been integrated with the VEG system and requires that the VEG system be loaded to operate. VEG is the NASA VEGetation workbench - an expert system for inferring vegetation characteristics from reflectance data. The learning system provides three basic options. Using option one, the system learns class descriptions of one or more classes. Using option two, the system learns class descriptions of one or more classes and then uses the learned classes to classify an unknown sample. Using option three, the user can test the system's classification performance. The learning system can also be run in an automatic mode. In this mode, options two and three are executed on each sample from an input file. The system was developed using KEE. It is menu driven and contains a sophisticated window and mouse driven interface which guides the user through various computations. Input and output file management and data formatting facilities are also provided.

SoS Navigator 2.0: A Context-Based Approach to System-of-Systems Challenges

DTIC Science & Technology

2008-06-01

in a Postindustrial Age. MIT Press, 1984. [ Kolb 1984] Kolb , David A. Experiential Learning : Experience as the Source of Learning and Develop- ment...terms of experiential learning , and the work of Rosen [Rosen 1991] in terms of the relational approach to understanding anticipa- tive systems. Our...Supporting Techniques and Tools 17  3.2  The Learning /Transformation Cycle 19  3.3  Summary of SoS Navigator Processes and Techniques 20  4  Case Summaries 22

Prefrontal cortex as a meta-reinforcement learning system.

PubMed

Wang, Jane X; Kurth-Nelson, Zeb; Kumaran, Dharshan; Tirumala, Dhruva; Soyer, Hubert; Leibo, Joel Z; Hassabis, Demis; Botvinick, Matthew

2018-06-01

Over the past 20 years, neuroscience research on reward-based learning has converged on a canonical model, under which the neurotransmitter dopamine 'stamps in' associations between situations, actions and rewards by modulating the strength of synaptic connections between neurons. However, a growing number of recent findings have placed this standard model under strain. We now draw on recent advances in artificial intelligence to introduce a new theory of reward-based learning. Here, the dopamine system trains another part of the brain, the prefrontal cortex, to operate as its own free-standing learning system. This new perspective accommodates the findings that motivated the standard model, but also deals gracefully with a wider range of observations, providing a fresh foundation for future research.

Online EEG-Based Workload Adaptation of an Arithmetic Learning Environment.

PubMed

Walter, Carina; Rosenstiel, Wolfgang; Bogdan, Martin; Gerjets, Peter; Spüler, Martin

2017-01-01

In this paper, we demonstrate a closed-loop EEG-based learning environment, that adapts instructional learning material online, to improve learning success in students during arithmetic learning. The amount of cognitive workload during learning is crucial for successful learning and should be held in the optimal range for each learner. Based on EEG data from 10 subjects, we created a prediction model that estimates the learner's workload to obtain an unobtrusive workload measure. Furthermore, we developed an interactive learning environment that uses the prediction model to estimate the learner's workload online based on the EEG data and adapt the difficulty of the learning material to keep the learner's workload in an optimal range. The EEG-based learning environment was used by 13 subjects to learn arithmetic addition in the octal number system, leading to a significant learning effect. The results suggest that it is feasible to use EEG as an unobtrusive measure of cognitive workload to adapt the learning content. Further it demonstrates that a promptly workload prediction is possible using a generalized prediction model without the need for a user-specific calibration.

eLearning in education and advanced training in neuroradiology: introduction of a web-based teaching and learning application.

PubMed

Zajaczek, J E W; Götz, F; Kupka, T; Behrends, M; Haubitz, B; Donnerstag, F; Rodt, T; Walter, G F; Matthies, H K; Becker, H

2006-09-01

New information technologies offer the possibility of major improvements in the professional education and advanced training of physicians. The web-based, multimedia teaching and learning application Schoolbook has been created and utilized for neuroradiology. Schoolbook is technically based as a content management system and is realized in a LAMP environment. The content is generated with the help of the developed system and stored in a database. The layout is defined by a PHP application, and the webpages are generated from the system. Schoolbook is realized as an authoring tool so that it can be integrated into daily practice. This enables the teacher to autonomously process the content into the web-based application which is used for lectures, seminars and self-study. A multimedia case library is the central building block of Schoolbook for neuroradiology, whereby the learner is provided with original diagnostic and therapeutic data from numerous individual cases. The user can put individual emphasis on key learning points as there are various ways to work with the case histories. Besides the case-based way of teaching and learning, a systematically structured way of dealing with the content is available. eLearning offers various opportunities for teaching and learning in academic and scientific as well as in economic contexts. Web-based applications such as Schoolbook may be beneficial not only for basic university education but also for the realization of international educational programmes such as the European Master of Medical Science with a major in neuroradiology.

Genetic algorithm based fuzzy control of spacecraft autonomous rendezvous

NASA Technical Reports Server (NTRS)

Karr, C. L.; Freeman, L. M.; Meredith, D. L.

1990-01-01

The U.S. Bureau of Mines is currently investigating ways to combine the control capabilities of fuzzy logic with the learning capabilities of genetic algorithms. Fuzzy logic allows for the uncertainty inherent in most control problems to be incorporated into conventional expert systems. Although fuzzy logic based expert systems have been used successfully for controlling a number of physical systems, the selection of acceptable fuzzy membership functions has generally been a subjective decision. High performance fuzzy membership functions for a fuzzy logic controller that manipulates a mathematical model simulating the autonomous rendezvous of spacecraft are learned using a genetic algorithm, a search technique based on the mechanics of natural genetics. The membership functions learned by the genetic algorithm provide for a more efficient fuzzy logic controller than membership functions selected by the authors for the rendezvous problem. Thus, genetic algorithms are potentially an effective and structured approach for learning fuzzy membership functions.

Outcomes from building system courseware for teaching and testing in a discipline-based human structure curriculum.

PubMed

Reilly, Frank D

2011-01-01

This study investigated the educational benefits of system-based lecture notes and interactive learning objects in a peripheral nervous system component of a traditional first-year medical school human anatomy course. The impetus for the investigation was anecdotal evidence suggesting enhanced learner satisfaction with the learning resources. Retrospective review of existing data from 2006 to 2009 was undertaken to quantify (1) the effects of Web-based system courseware on examination item performance, and (2) differences among learner opinions regarding the benefit level of the five different types of interactive learning objects as evaluated by instructional design questionnaires. Interactive patient-based case studies (IPCS) and review games (Games), simulated interactive patients (SIP), flashcards, and unit quizzes (Quizzes) developed in-house have been peer-reviewed and published in MedEdPORTAL. Statistics included one-way analysis of variance, Tukey's post hoc test, and power meta-analysis (d). Examination item analysis scores remained significantly higher (P ≤ 0.05; d = 0.3938) for learners receiving the instructional treatment incorporating system-based lecture notes and interactive learning objects than for those not receiving this treatment. Using questionnaires with a five-point Likert scale, students reported favorably on the benefit level of all learning objects. They rated the SIP and IPCS significantly higher (P ≤0.05) and games significantly lower (P ≤ 0.05) than in previous years, indicating a change in learner preferences. This study reaffirms that online system-based instructional techniques improve student examination performance and overall student satisfaction. Learners indicated stronger preferences for SIP and IPCS over exercises encouraging passive memorization of anatomical content. Copyright © 2011 American Association of Anatomists.

OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

NASA Astrophysics Data System (ADS)

Pedrazzoli, Attilio

2010-06-01

AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

Towards case-based medical learning in radiological decision making using content-based image retrieval

PubMed Central

2011-01-01

Background Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. Methods We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. Results We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. Conclusions The IBCR-RE paradigm incorporates a novel combination of essential aspects of diagnostic learning in radiology: (i) Provision of work-relevant experiences in a training environment integrated into the radiologist's working context; (ii) Up-to-date training cases that do not require cumbersome preparation because they are provided by routinely generated electronic medical records; (iii) Support of the way adults learn while remaining suitable for the patient- and problem-oriented nature of medicine. Future work will address unanswered questions to complete the implementation of the IRMAdiag trainer. PMID:22032775

Towards case-based medical learning in radiological decision making using content-based image retrieval.

PubMed

Welter, Petra; Deserno, Thomas M; Fischer, Benedikt; Günther, Rolf W; Spreckelsen, Cord

2011-10-27

Radiologists' training is based on intensive practice and can be improved with the use of diagnostic training systems. However, existing systems typically require laboriously prepared training cases and lack integration into the clinical environment with a proper learning scenario. Consequently, diagnostic training systems advancing decision-making skills are not well established in radiological education. We investigated didactic concepts and appraised methods appropriate to the radiology domain, as follows: (i) Adult learning theories stress the importance of work-related practice gained in a team of problem-solvers; (ii) Case-based reasoning (CBR) parallels the human problem-solving process; (iii) Content-based image retrieval (CBIR) can be useful for computer-aided diagnosis (CAD). To overcome the known drawbacks of existing learning systems, we developed the concept of image-based case retrieval for radiological education (IBCR-RE). The IBCR-RE diagnostic training is embedded into a didactic framework based on the Seven Jump approach, which is well established in problem-based learning (PBL). In order to provide a learning environment that is as similar as possible to radiological practice, we have analysed the radiological workflow and environment. We mapped the IBCR-RE diagnostic training approach into the Image Retrieval in Medical Applications (IRMA) framework, resulting in the proposed concept of the IRMAdiag training application. IRMAdiag makes use of the modular structure of IRMA and comprises (i) the IRMA core, i.e., the IRMA CBIR engine; and (ii) the IRMAcon viewer. We propose embedding IRMAdiag into hospital information technology (IT) infrastructure using the standard protocols Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7). Furthermore, we present a case description and a scheme of planned evaluations to comprehensively assess the system. The IBCR-RE paradigm incorporates a novel combination of essential aspects of diagnostic learning in radiology: (i) Provision of work-relevant experiences in a training environment integrated into the radiologist's working context; (ii) Up-to-date training cases that do not require cumbersome preparation because they are provided by routinely generated electronic medical records; (iii) Support of the way adults learn while remaining suitable for the patient- and problem-oriented nature of medicine. Future work will address unanswered questions to complete the implementation of the IRMAdiag trainer.

Security Enhancement Using Cache Based Reauthentication in WiMAX Based E-Learning System

PubMed Central

Rajagopal, Chithra; Bhuvaneshwaran, Kalaavathi

2015-01-01

WiMAX networks are the most suitable for E-Learning through their Broadcast and Multicast Services at rural areas. Authentication of users is carried out by AAA server in WiMAX. In E-Learning systems the users must be forced to perform reauthentication to overcome the session hijacking problem. The reauthentication of users introduces frequent delay in the data access which is crucial in delaying sensitive applications such as E-Learning. In order to perform fast reauthentication caching mechanism known as Key Caching Based Authentication scheme is introduced in this paper. Even though the cache mechanism requires extra storage to keep the user credentials, this type of mechanism reduces the 50% of the delay occurring during reauthentication. PMID:26351658

Security Enhancement Using Cache Based Reauthentication in WiMAX Based E-Learning System.

PubMed

Rajagopal, Chithra; Bhuvaneshwaran, Kalaavathi

2015-01-01

WiMAX networks are the most suitable for E-Learning through their Broadcast and Multicast Services at rural areas. Authentication of users is carried out by AAA server in WiMAX. In E-Learning systems the users must be forced to perform reauthentication to overcome the session hijacking problem. The reauthentication of users introduces frequent delay in the data access which is crucial in delaying sensitive applications such as E-Learning. In order to perform fast reauthentication caching mechanism known as Key Caching Based Authentication scheme is introduced in this paper. Even though the cache mechanism requires extra storage to keep the user credentials, this type of mechanism reduces the 50% of the delay occurring during reauthentication.

Learning about systems-based practice in the informal curriculum: a case study in an academic pediatric continuity clinic.

PubMed

Balmer, Dorene; Ruzek, Sheryl; Ludwig, Stephen; Giardino, Angelo P

2007-01-01

Pediatric residents learn about systems-based practice (SBP) explicitly in the formal curriculum and implicitly in the informal curriculum as they engage in practice alongside physician faculty. Recent studies describe innovative ways to address SBP in the formal curriculum for SBP, but the informal curriculum has not been explored. We examined what, and how, third-year pediatric residents learn about SBP in the informal curriculum at one continuity clinic, and to consider how this learning aligns with the formal curriculum. A case study involving 10 third-year pediatric residents and 10 continuity preceptors was conducted at one continuity clinic, housed in a community-based, pediatric primary care center. Data were derived from 5 months (100 hours) of direct observation in the precepting room at the case clinic, semistructured interviews with residents (before and after observation) and with preceptors (after observation). Interview transcripts and notes from observation were inductively coded and analyzed for major themes. Two themes emerged in the informal curriculum. Residents perceived "our system," the academic health system in which they trained and practiced as separate and distinct from the "real system," the larger, societal context of health care. Residents also understood SBP as a commitment to helping individual patients and families navigate the complexities of "our system," dealing with issues that concerned them. Residents learn important lessons about SBP in the informal curriculum in continuity clinic. These lessons may reinforce some elements of the competency-based formal curriculum for SBP, but challenge others.

`Not hard to sway': a case study of student engagement in two large engineering classes

NASA Astrophysics Data System (ADS)

Shekhar, Prateek; Borrego, Maura

2018-07-01

Although engineering education research has empirically validated the effectiveness of active learning in improving student learning over traditional lecture-based methods, the adoption of active learning in classrooms has been slow. One of the greatest reported barriers is student resistance towards engagement in active learning exercises. This paper argues that the level of student engagement in active learning classrooms is an interplay of social and physical classroom characteristics. Using classroom observations and instructor interviews, this study describes the influence of the interaction of student response systems and classroom layout on student engagement in two large active-learning-based engineering classrooms. The findings suggest that the use of different student response systems in combination with cluster-style seating arrangements can increase student engagement in large classrooms.

Discovering Fine-grained Sentiment in Suicide Notes

PubMed Central

Wang, Wenbo; Chen, Lu; Tan, Ming; Wang, Shaojun; Sheth, Amit P.

2012-01-01

This paper presents our solution for the i2b2 sentiment classification challenge. Our hybrid system consists of machine learning and rule-based classifiers. For the machine learning classifier, we investigate a variety of lexical, syntactic and knowledge-based features, and show how much these features contribute to the performance of the classifier through experiments. For the rule-based classifier, we propose an algorithm to automatically extract effective syntactic and lexical patterns from training examples. The experimental results show that the rule-based classifier outperforms the baseline machine learning classifier using unigram features. By combining the machine learning classifier and the rule-based classifier, the hybrid system gains a better trade-off between precision and recall, and yields the highest micro-averaged F-measure (0.5038), which is better than the mean (0.4875) and median (0.5027) micro-average F-measures among all participating teams. PMID:22879770

[Online continuing medical education based on national disease management guidelines. The e-learning platform leitlinien-wissen.de].

PubMed

Vollmar, H C; Schürer-Maly, C-C; Lelgemann, M; Koneczny, N; Koch, M; Butzlaff, M

2006-05-01

Effective translation of relevant knowledge into clinical practice is essential for modern health care systems. National Disease Management Guidelines (NDMG) are considered relevant instruments to support this transfer. To implement NDMG Internet-based continuing medical education (CME), modules and online case-based learning objects were designed and published. To ensure high quality the contents are based on NDMG and subjected to multi-step review processes. Presentation on the web was realized through a modified content management system. To obtain a CME certificate, completing an online questionnaire using a four-point Likert scale was mandatory. Between June 2003 and April 2005, 3,105 physicians were registered and used the platform: 95% of the physicians expressed positive feedback in the evaluation questionnaire, and 35% actually used the corresponding NDMG in practice. This prompted the development of interactive medical case-based learning objects as a second learning pathway. An Internet platform for CME including case-based learning objects can be a helpful tool to assure the provision of scientific knowledge for patient care.

Fuzzy and neural control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1992-01-01

Fuzzy logic and neural networks provide new methods for designing control systems. Fuzzy logic controllers do not require a complete analytical model of a dynamic system and can provide knowledge-based heuristic controllers for ill-defined and complex systems. Neural networks can be used for learning control. In this chapter, we discuss hybrid methods using fuzzy logic and neural networks which can start with an approximate control knowledge base and refine it through reinforcement learning.

Organizational Factors that Influence E-Learning Development and Implementation in the Corporate Context

ERIC Educational Resources Information Center

Wang, Feng-Kwei; Schwen, Thomas

2003-01-01

In the context of Autoparts, a multinational manufacturer for automotive electronics, Lotus Notes was employed to create an e-learning system. This system was titled "Using Notes for Case-based Learning Environments" (UNCLE). The UNCLE project attempted to encapsulate knowledge and understanding of those organizational factors that might influence…

Life-Long Cyberlearning System: A Pilot Project for the "Learning Society" in the ROC.

ERIC Educational Resources Information Center

Han, Huei-Wen; Wang, Yen-Chao

1999-01-01

Provides an overview of the implementation of lifelong learning in Taiwan, Republic of China (ROC) as part of its educational reform policy and describes a pilot project, the Lifelong Cyberlearning System. Highlights include planning architecture, Web-based learning technology, professional education, industrial and corporate assistance, and…

Effects of "Handep" Cooperative Learning Based on Indigenous Knowledge on Mathematical Problem Solving Skill

ERIC Educational Resources Information Center

Demitra; Sarjoko

2018-01-01

Indigenous people of Dayak tribe in Kalimantan, Indonesia have traditionally relied on a system of mutual cooperation called "handep." The cultural context has an influence on students mathematics learning. The "handep" system might be suitable for modern learning situations to develop mathematical problem-solving skill. The…

An Activity-Based Learning Approach for Key Geographical Information Systems (GIS) Concepts

ERIC Educational Resources Information Center

Srivastava, Sanjeev Kumar; Tait, Cynthia

2012-01-01

This study presents the effect of active learning methods of concepts in geographical information systems where students participated in a series of interlocked learning experiences. These activities spanned several teaching weeks and involved the creation of a hand drawn map that was scanned and geo-referenced with locations' coordinates derived…

A Distributed Intelligent E-Learning System

ERIC Educational Resources Information Center

Kristensen, Terje

2016-01-01

An E-learning system based on a multi-agent (MAS) architecture combined with the Dynamic Content Manager (DCM) model of E-learning, is presented. We discuss the benefits of using such a multi-agent architecture. Finally, the MAS architecture is compared with a pure service-oriented architecture (SOA). This MAS architecture may also be used within…

Real-Time Interactive Social Environments: A Review of BT's Generic Learning Platform.

ERIC Educational Resources Information Center

Gardner, Michael; Ward, Holly

1999-01-01

Describes the development of a generic learning platform for online distance learning and explains RISE (Real-time Interactive Social Environments), a Web-based system. Reports results of trials at the University of Hull Language Institute in an English as a Foreign Language course that investigated system usability, teacher roles, and student…

A Novel Architecture for E-Learning Knowledge Assessment Systems

ERIC Educational Resources Information Center

Gierlowski, Krzysztof; Nowicki, Krzysztof

2009-01-01

In this article we propose a novel e-learning system, dedicated strictly to knowledge assessment tasks. In its functioning it utilizes web-based technologies, but its design differs radically from currently popular e-learning solutions which rely mostly on thin-client architecture. Our research proved that such architecture, while well suited for…

Collective Learning: A Way over the Ridge to a New Organizational Attractor

ERIC Educational Resources Information Center

Backstrom, Tomas

2004-01-01

A theoretical model of collective learning has been developed based on complex systems theory. The need for collective learning is illustrated by an empirical study of an "unsuccessful" organizational-renewal project in a Swedish Telecom firm. The conclusion, using chaordic systems thinking as a diagnostic framework, is that its interior…

ICT Competence-Based Learning Object Recommendations for Teachers

ERIC Educational Resources Information Center

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…

A Multimedia English Learning System Using HMMs to Improve Phonemic Awareness for English Learning

ERIC Educational Resources Information Center

Lai, Yen-Shou; Tsai, Hung-Hsu; Yu, Pao-Ta

2009-01-01

This paper proposes a multimedia English learning (MEL) system, based on Hidden Markov Models (HMMs) and mastery theory strategy, for teaching students with the aim of enhancing their English phonetic awareness and pronunciation. It can analyze phonetic structures, identify and capture pronunciation errors to provide students with targeted advice…

eFSM--a novel online neural-fuzzy semantic memory model.

PubMed

Tung, Whye Loon; Quek, Chai

2010-01-01

Fuzzy rule-based systems (FRBSs) have been successfully applied to many areas. However, traditional fuzzy systems are often manually crafted, and their rule bases that represent the acquired knowledge are static and cannot be trained to improve the modeling performance. This subsequently leads to intensive research on the autonomous construction and tuning of a fuzzy system directly from the observed training data to address the knowledge acquisition bottleneck, resulting in well-established hybrids such as neural-fuzzy systems (NFSs) and genetic fuzzy systems (GFSs). However, the complex and dynamic nature of real-world problems demands that fuzzy rule-based systems and models be able to adapt their parameters and ultimately evolve their rule bases to address the nonstationary (time-varying) characteristics of their operating environments. Recently, considerable research efforts have been directed to the study of evolving Tagaki-Sugeno (T-S)-type NFSs based on the concept of incremental learning. In contrast, there are very few incremental learning Mamdani-type NFSs reported in the literature. Hence, this paper presents the evolving neural-fuzzy semantic memory (eFSM) model, a neural-fuzzy Mamdani architecture with a data-driven progressively adaptive structure (i.e., rule base) based on incremental learning. Issues related to the incremental learning of the eFSM rule base are carefully investigated, and a novel parameter learning approach is proposed for the tuning of the fuzzy set parameters in eFSM. The proposed eFSM model elicits highly interpretable semantic knowledge in the form of Mamdani-type if-then fuzzy rules from low-level numeric training data. These Mamdani fuzzy rules define the computing structure of eFSM and are incrementally learned with the arrival of each training data sample. New rules are constructed from the emergence of novel training data and obsolete fuzzy rules that no longer describe the recently observed data trends are pruned. This enables eFSM to maintain a current and compact set of Mamdani-type if-then fuzzy rules that collectively generalizes and describes the salient associative mappings between the inputs and outputs of the underlying process being modeled. The learning and modeling performances of the proposed eFSM are evaluated using several benchmark applications and the results are encouraging.

Imaging evidence for disturbances in multiple learning and memory systems in persons with autism spectrum disorders.

PubMed

Goh, Suzanne; Peterson, Bradley S

2012-03-01

The aim of this article is to review neuroimaging studies of autism spectrum disorders (ASD) that examine declarative, socio-emotional, and procedural learning and memory systems. We conducted a search of PubMed from 1996 to 2010 using the terms 'autism,''learning,''memory,' and 'neuroimaging.' We limited our review to studies correlating learning and memory function with neuroimaging features of the brain. The early literature supports the following preliminary hypotheses: (1) abnormalities of hippocampal subregions may contribute to autistic deficits in episodic and relational memory; (2) disturbances to an amygdala-based network (which may include the fusiform gyrus, superior temporal cortex, and mirror neuron system) may contribute to autistic deficits in socio-emotional learning and memory; and (3) abnormalities of the striatum may contribute to developmental dyspraxia in individuals with ASD. Characterizing the disturbances to learning and memory systems in ASD can inform our understanding of the neural bases of autistic behaviors and the phenotypic heterogeneity of ASD. © The Authors. Developmental Medicine & Child Neurology © 2012 Mac Keith Press.

Developing Learning Tool of Control System Engineering Using Matrix Laboratory Software Oriented on Industrial Needs

NASA Astrophysics Data System (ADS)

Isnur Haryudo, Subuh; Imam Agung, Achmad; Firmansyah, Rifqi

2018-04-01

The purpose of this research is to develop learning media of control technique using Matrix Laboratory software with industry requirement approach. Learning media serves as a tool for creating a better and effective teaching and learning situation because it can accelerate the learning process in order to enhance the quality of learning. Control Techniques using Matrix Laboratory software can enlarge the interest and attention of students, with real experience and can grow independent attitude. This research design refers to the use of research and development (R & D) methods that have been modified by multi-disciplinary team-based researchers. This research used Computer based learning method consisting of computer and Matrix Laboratory software which was integrated with props. Matrix Laboratory has the ability to visualize the theory and analysis of the Control System which is an integration of computing, visualization and programming which is easy to use. The result of this instructional media development is to use mathematical equations using Matrix Laboratory software on control system application with DC motor plant and PID (Proportional-Integral-Derivative). Considering that manufacturing in the field of Distributed Control systems (DCSs), Programmable Controllers (PLCs), and Microcontrollers (MCUs) use PID systems in production processes are widely used in industry.

Extended Relation Metadata for SCORM-Based Learning Content Management Systems

ERIC Educational Resources Information Center

Lu, Eric Jui-Lin; Horng, Gwoboa; Yu, Chia-Ssu; Chou, Ling-Ying

2010-01-01

To increase the interoperability and reusability of learning objects, Advanced Distributed Learning Initiative developed a model called Content Aggregation Model (CAM) to describe learning objects and express relationships between learning objects. However, the suggested relations defined in the CAM can only describe structure-oriented…

Radiologists' preferences for just-in-time learning.

PubMed

Kahn, Charles E; Ehlers, Kevin C; Wood, Beverly P

2006-09-01

Effective learning can occur at the point of care, when opportunities arise to acquire information and apply it to a clinical problem. To assess interest in point-of-care learning, we conducted a survey to explore radiologists' attitudes and preferences regarding the use of just-in-time learning (JITL) in radiology. Following Institutional Review Board approval, we invited 104 current radiology residents and 86 radiologists in practice to participate in a 12-item Internet-based survey to assess their attitudes toward just-in-time learning. Voluntary participation in the survey was solicited by e-mail; respondents completed the survey on a web-based form. Seventy-nine physicians completed the questionnaire, including 47 radiology residents and 32 radiologists in practice; the overall response rate was 42%. Respondents generally expressed a strong interest for JITL: 96% indicated a willingness to try such a system, and 38% indicated that they definitely would use a JITL system. They expressed a preference for learning interventions of 5-10 min in length. Current and recent radiology trainees have expressed a strong interest in just-in-time learning. The information from this survey should be useful in pursuing the design of learning interventions and systems for delivering just-in-time learning to radiologists.

Approach for Using Learner Satisfaction to Evaluate the Learning Adaptation Policy

ERIC Educational Resources Information Center

Jeghal, Adil; Oughdir, Lahcen; Tairi, Hamid; Radouane, Abdelhay

2016-01-01

The learning adaptation is a very important phase in a learning situation in human learning environments. This paper presents the authors' approach used to evaluate the effectiveness of learning adaptive systems. This approach is based on the analysis of learner satisfaction notices collected by a questionnaire on a learning situation; to analyze…

Exploring Learner Attitudes toward Web-Based Recommendation Learning Service System for Interdisciplinary Applications

ERIC Educational Resources Information Center

Chen, Hong-Ren; Huang, Jhen-Gang

2012-01-01

The booming digital-content industry has resulted in an increasing number of e-learning Internet websites that provide online learning services. Recommendations for learning sites are used by diverse learners to identify the most appropriate learning resources. However, research into recommendations about learning has concentrated primarily on…

The Evaluation of the Cognitive Learning Process of the Renewed Bloom Taxonomy Using a Web Based Expert System

ERIC Educational Resources Information Center

Goksu, Idris

2016-01-01

The aim of this study is to develop the Web Based Expert System (WBES) which provides analyses and reports based on the cognitive processes of Renewed Bloom Taxonomy (RBT), and to put forward the impact of the supportive education provided in line with these reports, on the academic achievement and mastery learning state of the students. The study…

Competency-Based Accounting Instruction

ERIC Educational Resources Information Center

Graham, John E.

1977-01-01

Shows how the proposed model (an individualized competency based learning system) can be used effectively to produce a course in accounting principles which adapts to different entering competencies and to different rates and styles of learning. (TA)

A recommendation module to help teachers build courses through the Moodle Learning Management System

NASA Astrophysics Data System (ADS)

Limongelli, Carla; Lombardi, Matteo; Marani, Alessandro; Sciarrone, Filippo; Temperini, Marco

2016-01-01

In traditional e-learning, teachers design sets of Learning Objects (LOs) and organize their sequencing; the material implementing the LOs could be either built anew or adopted from elsewhere (e.g. from standard-compliant repositories) and reused. This task is applicable also when the teacher works in a system for personalized e-learning. In this case, the burden actually increases: for instance, the LOs may need adaptation to the system, through additional metadata. This paper presents a module that gives some support to the operations of retrieving, analyzing, and importing LOs from a set of standard Learning Objects Repositories, acting as a recommending system. In particular, it is designed to support the teacher in the phases of (i) retrieval of LOs, through a keyword-based search mechanism applied to the selected repositories; (ii) analysis of the returned LOs, whose information is enriched by a concept of relevance metric, based on both the results of the searching operation and the data related to the previous use of the LOs in the courses managed by the Learning Management System; and (iii) LO importation into the course under construction.

Study on Practical Application of Turboprop Engine Condition Monitoring and Fault Diagnostic System Using Fuzzy-Neuro Algorithms

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong; Kim, Keunwoo

2013-03-01

The Neural Networks is mostly used to engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measuring performance data, and proposes a fault diagnostic system using the base performance model and artificial intelligent methods such as Fuzzy and Neural Networks. Each real engine performance model, which is named as the base performance model that can simulate a new engine performance, is inversely made using its performance test data. Therefore the condition monitoring of each engine can be more precisely carried out through comparison with measuring performance data. The proposed diagnostic system identifies firstly the faulted components using Fuzzy Logic, and then quantifies faults of the identified components using Neural Networks leaned by fault learning data base obtained from the developed base performance model. In leaning the measuring performance data of the faulted components, the FFBP (Feed Forward Back Propagation) is used. In order to user's friendly purpose, the proposed diagnostic program is coded by the GUI type using MATLAB.

Free-access open-source e-learning in comprehensive neurosurgery skills training.

PubMed

Jotwani, Payal; Srivastav, Vinkle; Tripathi, Manjul; Deo, Rama Chandra; Baby, Britty; Damodaran, Natesan; Singh, Ramandeep; Suri, Ashish; Bettag, Martin; Roy, Tara Sankar; Busert, Christoph; Mehlitz, Marcus; Lalwani, Sanjeev; Garg, Kanwaljeet; Paul, Kolin; Prasad, Sanjiva; Banerjee, Subhashis; Kalra, Prem; Kumar, Subodh; Sharma, Bhavani Shankar; Mahapatra, Ashok Kumar

2014-01-01

Since the end of last century, technology has taken a front seat in dispersion of medical education. Advancements of technology in neurosurgery and traditional training methods are now being challenged by legal and ethical concerns of patient safety, resident work-hour restriction and cost of operating-room time. To supplement the existing neurosurgery education pattern, various e-learning platforms are introduced as structured, interactive learning system. This study focuses on the concept, formulation, development and impact of web based learning platforms dedicated to neurosurgery discipline to disseminate education, supplement surgical knowledge and improve skills of neurosurgeons. 'Neurosurgery Education and Training School (NETS), e-learning platform' has integration of web-based technologies like 'Content Management System' for organizing the education material and 'Learning Management System' for updating neurosurgeons. NETS discussion forum networks neurosurgeons, neuroscientists and neuro-technologists across the globe facilitating collaborative translational research. Multi-authored neurosurgical e-learning material supplements the deficiencies of regular time-bound education. Interactive open-source, global, free-access e-learning platform of NETS has around 1) 425 visitors/month from 73 countries; ratio of new visitors to returning visitors 42.3; 57.7 (2); 64,380 views from 190 subscribers for surgical videos, 3-D animation, graphics based training modules (3); average 402 views per post. The e-Learning platforms provide updated educational content that make them "quick, surf, find and extract" resources. e-Learning tools like web-based education, social interactive platform and question-answer forum will save unnecessary expenditure of time and travel of neurosurgeons seeking knowledge. The need for free access platforms is more pronounced for the neurosurgeons and patients in developing nations.

Aging Affects Acquisition and Reversal of Reward-Based Associative Learning

ERIC Educational Resources Information Center

Weiler, Julia A.; Bellebaum, Christian; Daum, Irene

2008-01-01

Reward-based associative learning is mediated by a distributed network of brain regions that are dependent on the dopaminergic system. Age-related changes in key regions of this system, the striatum and the prefrontal cortex, may adversely affect the ability to use reward information for the guidance of behavior. The present study investigated the…

Game-Based Experiential Learning in Online Management Information Systems Classes Using Intel's IT Manager 3

ERIC Educational Resources Information Center

Bliemel, Michael; Ali-Hassan, Hossam

2014-01-01

For several years, we used Intel's flash-based game "IT Manager 3: Unseen Forces" as an experiential learning tool, where students had to act as a manager making real-time prioritization decisions about repairing computer problems, training and upgrading systems with better technologies as well as managing increasing numbers of technical…

Antecedents of Continued Usage Intentions of Web-Based Learning Management System in Tanzania

ERIC Educational Resources Information Center

Lwoga, Edda Tandi; Komba, Mercy

2015-01-01

Purpose: The purpose of this paper is to examine factors that predict students' continued usage intention of web-based learning management systems (LMS) in Tanzania, with a specific focus on the School of Business of Mzumbe University. Specifically, the study investigated major predictors of actual usage and continued usage intentions of…

The Role of Peer Influence and Perceived Quality of Teaching in Faculty Acceptance of Web-Based Learning Management Systems

ERIC Educational Resources Information Center

Salajan, Florin D.; Welch, Anita G.; Ray, Chris M.; Peterson, Claudette

2015-01-01

This study's primary investigation is the impact of "peer influence" and "perceived quality of teaching" on faculty members' usage of web-based learning management systems within the Technology Acceptance Model (TAM) framework. These factors are entered into an extended TAM as external variables impacting on the core constructs…

A Corpus-Based System of Error Detection and Revision Suggestion for Spanish Learners in Taiwan: A Case Study

ERIC Educational Resources Information Center

Lu, Hui-Chuan; Chu, Yu-Hsin; Chang, Cheng-Yu

2013-01-01

Compared with English learners, Spanish learners have fewer resources for automatic error detection and revision and following the current integrative Computer Assisted Language Learning (CALL), we combined corpus-based approach and CALL to create the System of Error Detection and Revision Suggestion (SEDRS) for learning Spanish. Through…

Supporting Active Learning in an Undergraduate Geotechnical Engineering Course Using Group-Based Audience Response Systems Quizzes

ERIC Educational Resources Information Center

Donohue, Shane

2014-01-01

The use of audience response systems (ARSs) or "clickers" in higher education has increased over the recent years, predominantly owing to their ability to actively engage students, for promoting individual and group learning, and for providing instantaneous feedback to students and teachers. This paper describes how group-based ARS…

Knowledge Based Artificial Augmentation Intelligence Technology: Next Step in Academic Instructional Tools for Distance Learning

ERIC Educational Resources Information Center

Crowe, Dale; LaPierre, Martin; Kebritchi, Mansureh

2017-01-01

With augmented intelligence/knowledge based system (KBS) it is now possible to develop distance learning applications to support both curriculum and administrative tasks. Instructional designers and information technology (IT) professionals are now moving from the programmable systems era that started in the 1950s to the cognitive computing era.…

Critical Success Factors for Adoption of Web-Based Learning Management Systems in Tanzania

ERIC Educational Resources Information Center

Lwoga, Edda Tandi

2014-01-01

This paper examines factors that predict students' continual usage intention of web-based learning content management systems in Tanzania, with a specific focus at Muhimbili University of Health and Allied Science (MUHAS). This study sent a questionnaire surveys to 408 first year undergraduate students, with a rate of return of 66.7. This study…

Support patient search on pathology reports with interactive online learning based data extraction.

PubMed

Zheng, Shuai; Lu, James J; Appin, Christina; Brat, Daniel; Wang, Fusheng

2015-01-01

Structural reporting enables semantic understanding and prompt retrieval of clinical findings about patients. While synoptic pathology reporting provides templates for data entries, information in pathology reports remains primarily in narrative free text form. Extracting data of interest from narrative pathology reports could significantly improve the representation of the information and enable complex structured queries. However, manual extraction is tedious and error-prone, and automated tools are often constructed with a fixed training dataset and not easily adaptable. Our goal is to extract data from pathology reports to support advanced patient search with a highly adaptable semi-automated data extraction system, which can adjust and self-improve by learning from a user's interaction with minimal human effort. We have developed an online machine learning based information extraction system called IDEAL-X. With its graphical user interface, the system's data extraction engine automatically annotates values for users to review upon loading each report text. The system analyzes users' corrections regarding these annotations with online machine learning, and incrementally enhances and refines the learning model as reports are processed. The system also takes advantage of customized controlled vocabularies, which can be adaptively refined during the online learning process to further assist the data extraction. As the accuracy of automatic annotation improves overtime, the effort of human annotation is gradually reduced. After all reports are processed, a built-in query engine can be applied to conveniently define queries based on extracted structured data. We have evaluated the system with a dataset of anatomic pathology reports from 50 patients. Extracted data elements include demographical data, diagnosis, genetic marker, and procedure. The system achieves F-1 scores of around 95% for the majority of tests. Extracting data from pathology reports could enable more accurate knowledge to support biomedical research and clinical diagnosis. IDEAL-X provides a bridge that takes advantage of online machine learning based data extraction and the knowledge from human's feedback. By combining iterative online learning and adaptive controlled vocabularies, IDEAL-X can deliver highly adaptive and accurate data extraction to support patient search.

GA-based fuzzy reinforcement learning for control of a magnetic bearing system.

PubMed

Lin, C T; Jou, C P

2000-01-01

This paper proposes a TD (temporal difference) and GA (genetic algorithm)-based reinforcement (TDGAR) learning method and applies it to the control of a real magnetic bearing system. The TDGAR learning scheme is a new hybrid GA, which integrates the TD prediction method and the GA to perform the reinforcement learning task. The TDGAR learning system is composed of two integrated feedforward networks. One neural network acts as a critic network to guide the learning of the other network (the action network) which determines the outputs (actions) of the TDGAR learning system. The action network can be a normal neural network or a neural fuzzy network. Using the TD prediction method, the critic network can predict the external reinforcement signal and provide a more informative internal reinforcement signal to the action network. The action network uses the GA to adapt itself according to the internal reinforcement signal. The key concept of the TDGAR learning scheme is to formulate the internal reinforcement signal as the fitness function for the GA such that the GA can evaluate the candidate solutions (chromosomes) regularly, even during periods without external feedback from the environment. This enables the GA to proceed to new generations regularly without waiting for the arrival of the external reinforcement signal. This can usually accelerate the GA learning since a reinforcement signal may only be available at a time long after a sequence of actions has occurred in the reinforcement learning problem. The proposed TDGAR learning system has been used to control an active magnetic bearing (AMB) system in practice. A systematic design procedure is developed to achieve successful integration of all the subsystems including magnetic suspension, mechanical structure, and controller training. The results show that the TDGAR learning scheme can successfully find a neural controller or a neural fuzzy controller for a self-designed magnetic bearing system.

Problem-Based Learning in Formal and Informal Learning Environments

ERIC Educational Resources Information Center

Shimic, Goran; Jevremovic, Aleksandar

2012-01-01

Problem-based learning (PBL) is a student-centered instructional strategy in which students solve problems and reflect on their experiences. Different domains need different approaches in the design of PBL systems. Therefore, we present one case study in this article: A Java Programming PBL. The application is developed as an additional module for…

Rationale, Design and Implementation of a Computer Vision-Based Interactive E-Learning System

ERIC Educational Resources Information Center

Xu, Richard Y. D.; Jin, Jesse S.

2007-01-01

This article presents a schematic application of computer vision technologies to e-learning that is synchronous, peer-to-peer-based, and supports an instructor's interaction with non-computer teaching equipments. The article first discusses the importance of these focused e-learning areas, where the properties include accurate bidirectional…

Knowledge Acquisition at Work. IEE Brief Number 2.

ERIC Educational Resources Information Center

Scribner, Sylvia; Sachs, Patricia

An exploratory investigation attempted to determine how learning at work actually takes place and in what ways learning on the job differs from classroom learning. The study was based on extensive observations and interviews over a 5-year period at two manufacturing plants that implemented a computer-based system known as Manufacturing Resource…

Effects of Unidirectional vs. Reciprocal Teaching Strategies on Web-Based Computer Programming Learning

ERIC Educational Resources Information Center

Shadiev, Rustam; Hwang, Wu-Yuin; Yeh, Shih-Ching; Yang, Stephen J. H.; Wang, Jing-Liang; Han, Lin; Hsu, Guo-Liang

2014-01-01

This study aimed to investigate an effectiveness of unidirectional and reciprocal teaching strategies on programming learning supported by web-based learning system (VPen); particularly, how differently effective these two teaching strategies would work. In this study novice programmers were exposed to three different conditions: 1) applying no…

Design, Implementation, and Evaluation of GIS-Based Learning Materials in an Introductory Geoscience Course.

ERIC Educational Resources Information Center

Hall-Wallace, Michelle K.; McAuliffe, Carla M.

2002-01-01

Investigates student learning that occurred with a Geographic Information Systems (GIS) based module on plate tectonics and geologic hazards. Examines factors in the design and implementation of the materials that impacted student learning. Reports positive correlations between student' spatial ability and performance. Includes 17 references.…

Complexity-Based Learning and Teaching: A Case Study in Higher Education

ERIC Educational Resources Information Center

Fabricatore, Carlo; López, María Ximena

2014-01-01

This paper presents a learning and teaching strategy based on complexity science and explores its impacts on a higher education game design course. The strategy aimed at generating conditions fostering individual and collective learning in educational complex adaptive systems, and led the design of the course through an iterative and adaptive…

Establishment of a Digital Knowledge Conversion Architecture Design Learning with High User Acceptance

ERIC Educational Resources Information Center

Wu, Yun-Wu; Weng, Apollo; Weng, Kuo-Hua

2017-01-01

The purpose of this study is to design a knowledge conversion and management digital learning system for architecture design learning, helping students to share, extract, use and create their design knowledge through web-based interactive activities based on socialization, internalization, combination and externalization process in addition to…

Career Goal-Based E-Learning Recommendation Using Enhanced Collaborative Filtering and PrefixSpan

ERIC Educational Resources Information Center

Ma, Xueying; Ye, Lu

2018-01-01

This article describes how e-learning recommender systems nowadays have applied different kinds of techniques to recommend personalized learning content for users based on their preference, goals, interests and background information. However, the cold-start problem which exists in traditional recommendation algorithms are still left over in…

A Mindtool-Based Collaborative Learning Approach to Enhancing Students' Innovative Performance in Management Courses

ERIC Educational Resources Information Center

Wu, Chih-Hsiang; Hwang, Gwo-Jen; Kuo, Fan-Ray; Huang, Iwen

2013-01-01

Educators have indicated that creative teaching is the most important educational activity; nevertheless, most existing education systems fail to engage students in effective creative tasks. To address this issue, this study proposes a mind map based collaborative learning approach for supporting creative learning activities and enhancing…

Learning material recommendation based on case-based reasoning similarity scores

NASA Astrophysics Data System (ADS)

Masood, Mona; Mokmin, Nur Azlina Mohamed

2017-10-01

A personalized learning material recommendation is important in any Intelligent Tutoring System (ITS). Case-based Reasoning (CBR) is an Artificial Intelligent Algorithm that has been widely used in the development of ITS applications. This study has developed an ITS application that applied the CBR algorithm in the development process. The application has the ability to recommend the most suitable learning material to the specific student based on information in the student profile. In order to test the ability of the application in recommending learning material, two versions of the application were created. The first version displayed the most suitable learning material and the second version displayed the least preferable learning material. The results show the application has successfully assigned the students to the most suitable learning material.

New Ideas on the Design of the Web-Based Learning System Oriented to Problem Solving from the Perspective of Question Chain and Learning Community

ERIC Educational Resources Information Center

Zhang, Yin; Chu, Samuel K. W.

2016-01-01

In recent years, a number of models concerning problem solving systems have been put forward. However, many of them stress on technology and neglect the research of problem solving itself, especially the learning mechanism related to problem solving. In this paper, we analyze the learning mechanism of problem solving, and propose that when…

Inductive learning of thyroid functional states using the ID3 algorithm. The effect of poor examples on the learning result.

PubMed

Forsström, J

1992-01-01

The ID3 algorithm for inductive learning was tested using preclassified material for patients suspected to have a thyroid illness. Classification followed a rule-based expert system for the diagnosis of thyroid function. Thus, the knowledge to be learned was limited to the rules existing in the knowledge base of that expert system. The learning capability of the ID3 algorithm was tested with an unselected learning material (with some inherent missing data) and with a selected learning material (no missing data). The selected learning material was a subgroup which formed a part of the unselected learning material. When the number of learning cases was increased, the accuracy of the program improved. When the learning material was large enough, an increase in the learning material did not improve the results further. A better learning result was achieved with the selected learning material not including missing data as compared to unselected learning material. With this material we demonstrate a weakness in the ID3 algorithm: it can not find available information from good example cases if we add poor examples to the data.

Learning and tuning fuzzy logic controllers through reinforcements

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Khedkar, Pratap

1992-01-01

A new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. In particular, our Generalized Approximate Reasoning-based Intelligent Control (GARIC) architecture: (1) learns and tunes a fuzzy logic controller even when only weak reinforcements, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto, Sutton, and Anderson to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and has demonstrated significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong

2011-12-01

Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

Towards Scalable Deep Learning via I/O Analysis and Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pumma, Sarunya; Si, Min; Feng, Wu-Chun

Deep learning systems have been growing in prominence as a way to automatically characterize objects, trends, and anomalies. Given the importance of deep learning systems, researchers have been investigating techniques to optimize such systems. An area of particular interest has been using large supercomputing systems to quickly generate effective deep learning networks: a phase often referred to as “training” of the deep learning neural network. As we scale existing deep learning frameworks—such as Caffe—on these large supercomputing systems, we notice that the parallelism can help improve the computation tremendously, leaving data I/O as the major bottleneck limiting the overall systemmore » scalability. In this paper, we first present a detailed analysis of the performance bottlenecks of Caffe on large supercomputing systems. Our analysis shows that the I/O subsystem of Caffe—LMDB—relies on memory-mapped I/O to access its database, which can be highly inefficient on large-scale systems because of its interaction with the process scheduling system and the network-based parallel filesystem. Based on this analysis, we then present LMDBIO, our optimized I/O plugin for Caffe that takes into account the data access pattern of Caffe in order to vastly improve I/O performance. Our experimental results show that LMDBIO can improve the overall execution time of Caffe by nearly 20-fold in some cases.« less

Intelligent Image Based Computer Aided Education (IICAE)

NASA Astrophysics Data System (ADS)

David, Amos A.; Thiery, Odile; Crehange, Marion

1989-03-01

Artificial Intelligence (AI) has found its way into Computer Aided Education (CAE), and there are several systems constructed to put in evidence its interesting advantages. We believe that images (graphic or real) play an important role in learning. However, the use of images, outside their use as illustration, makes it necessary to have applications such as AI. We shall develop the application of AI in an image based CAE and briefly present the system under construction to put in evidence our concept. We shall also elaborate a methodology for constructing such a system. Futhermore we shall briefly present the pedagogical and psychological activities in a learning process. Under the pedagogical and psychological aspect of learning, we shall develop areas such as the importance of image in learning both as pedagogical objects as well as means for obtaining psychological information about the learner. We shall develop the learner's model, its use, what to build into it and how. Under the application of AI in an image based CAE, we shall develop the importance of AI in exploiting the knowledge base in the learning environment and its application as a means of implementing pedagogical strategies.

A Usability and Learnability Case Study of Glass Flight Deck Interfaces and Pilot Interactions through Scenario-based Training

NASA Astrophysics Data System (ADS)

De Cino, Thomas J., II

In the aviation industry, digitally produced and presented flight, navigation, and aircraft information is commonly referred to as glass flight decks. Glass flight decks are driven by computer-based subsystems and have long been a part of military and commercial aviation sectors. Over the past 15 years, the General Aviation (GA) sector of the aviation industry has become a recent beneficiary of the rapid advancement of computer-based glass flight deck (GFD) systems. While providing the GA pilot considerable enhancements in the quality of information about the status and operations of the aircraft, training pilots on the use of glass flight decks is often delivered with traditional methods (e.g. textbooks, PowerPoint presentations, user manuals, and limited computer-based training modules). These training methods have been reported as less than desirable in learning to use the glass flight deck interface. Difficulties in achieving a complete understanding of functional and operational characteristics of the GFD systems, acquiring a full understanding of the interrelationships of the varied subsystems, and handling the wealth of flight information provided have been reported. Documented pilot concerns of poor user experience and satisfaction, and problems with the learning the complex and sophisticated interface of the GFD are additional issues with current pilot training approaches. A case study was executed to explore ways to improve training using GFD systems at a Midwestern aviation university. The researcher investigated if variations in instructional systems design and training methods for learning glass flight deck technology would affect the perceptions and attitudes of pilots of the learnability (an attribute of usability) of the glass flight deck interface. Specifically, this study investigated the effectiveness of scenario-based training (SBT) methods to potentially improve pilot knowledge and understanding of a GFD system, and overall pilot user experience and satisfaction. Participants overwhelmingly reported positive learning experiences from scenario-based GFD systems flight training, noting that learning and knowledge construction were improved over other training received in the past. In contrast, participants rated the usability and learnability of the GFD training systems low, reporting various problems with the systems' interface, and the learnability (first-time use) of the complex GFD system. However, issues with usability of the GFD training systems did not reduce or change participant attitudes towards learning and mastering GFD systems; to the contrary, all participants requested additional coursework opportunities to train on GFD systems with the scenario-based flight training format.

Effects of interactive instructional techniques in a web-based peripheral nervous system component for human anatomy.

PubMed

Allen, Edwin B; Walls, Richard T; Reilly, Frank D

2008-02-01

This study investigated the effects of interactive instructional techniques in a web-based peripheral nervous system (PNS) component of a first year medical school human anatomy course. Existing data from 9 years of instruction involving 856 students were used to determine (1) the effect of web-based interactive instructional techniques on written exam item performance and (2) differences between student opinions of the benefit level of five different types of interactive learning objects used. The interactive learning objects included Patient Case studies, review Games, Simulated Interactive Patients (SIP), Flashcards, and unit Quizzes. Exam item analysis scores were found to be significantly higher (p < 0.05) for students receiving the instructional treatment incorporating the web-based interactive learning objects than for students not receiving this treatment. Questionnaires using a five-point Likert scale were analysed to determine student opinion ratings of the interactive learning objects. Students reported favorably on the benefit level of all learning objects. Students rated the benefit level of the Simulated Interactive Patients (SIP) highest, and this rating was significantly higher (p < 0.05) than all other learning objects. This study suggests that web-based interactive instructional techniques improve student exam performance. Students indicated a strong acceptance of Simulated Interactive Patient learning objects.

An e-Learning Theoretical Framework

ERIC Educational Resources Information Center

Aparicio, Manuela; Bacao, Fernando; Oliveira, Tiago

2016-01-01

E-learning systems have witnessed a usage and research increase in the past decade. This article presents the e-learning concepts ecosystem. It summarizes the various scopes on e-learning studies. Here we propose an e-learning theoretical framework. This theory framework is based upon three principal dimensions: users, technology, and services…

Learning Path Recommendation Based on Modified Variable Length Genetic Algorithm

ERIC Educational Resources Information Center

Dwivedi, Pragya; Kant, Vibhor; Bharadwaj, Kamal K.

2018-01-01

With the rapid advancement of information and communication technologies, e-learning has gained a considerable attention in recent years. Many researchers have attempted to develop various e-learning systems with personalized learning mechanisms for assisting learners so that they can learn more efficiently. In this context, curriculum sequencing…

Design of a Hypermedia-Based Educating System for the Construction of Knowledge

DTIC Science & Technology

1989-09-01

the variety they confront, promote short-term learning . This thesis provides the required background for developing an educating system which promotes...an effective educating system stems frm ever-increasing requirements for learning . Ine Total Quality Management (TQM) program, a Department of Defense...Japan has realized that best efforts ’nly pay off when the workforce is properly educated . Learning has become a pivotal element in the Japanese

Avatar Web-Based Self-Report Survey System Technology for Public Health Research: Technical Outcome Results and Lessons Learned.

PubMed

Savel, Craig; Mierzwa, Stan; Gorbach, Pamina M; Souidi, Samir; Lally, Michelle; Zimet, Gregory; Interventions, Aids

2016-01-01

This paper reports on a specific Web-based self-report data collection system that was developed for a public health research study in the United States. Our focus is on technical outcome results and lessons learned that may be useful to other projects requiring such a solution. The system was accessible from any device that had a browser that supported HTML5. Report findings include: which hardware devices, Web browsers, and operating systems were used; the rate of survey completion; and key considerations for employing Web-based surveys in a clinical trial setting.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Towards adaptation in e-learning 2.0

NASA Astrophysics Data System (ADS)

Cristea, Alexandra I.; Ghali, Fawaz

2011-04-01

This paper presents several essential steps from an overall study on shaping new ways of learning and teaching, by using the synergetic merger of three different fields: Web 2.0, e-learning and adaptation (in particular, personalisation to the learner). These novel teaching and learning ways-the latter focus of this paper-are reflected in and finally adding to various versions of the My Online Teacher 2.0 adaptive system. In particular, this paper focuses on a study of how to more effectively use and combine the recommendation of peers and content adaptation to enhance the learning outcome in e-learning systems based on Web 2.0. In order to better isolate and examine the effects of peer recommendation and adaptive content presentation, we designed experiments inspecting collaboration between individuals based on recommendation of peers who have greater knowledge, and compare this to adaptive content recommendation, as well as to "simple" learning in a system with a minimum of Web 2.0 support. Overall, the results of adding peer recommendation and adaptive content presentation were encouraging, and are further discussed in detail in this paper.

IS Success Model in E-Learning Context Based on Students' Perceptions

ERIC Educational Resources Information Center

Freeze, Ronald D.; Alshare, Khaled A.; Lane, Peggy L.; Wen, H. Joseph

2010-01-01

This study utilized the Information Systems Success (ISS) model in examining e-learning systems success. The study was built on the premise that system quality (SQ) and information quality (IQ) influence system use and user satisfaction, which in turn impact system success. A structural equation model (SEM), using LISREL, was used to test the…

Using a Dialogue System Based on Dialogue Maps for Computer Assisted Second Language Learning

ERIC Educational Resources Information Center

Choi, Sung-Kwon; Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun

2016-01-01

In order to use dialogue systems for computer assisted second-language learning systems, one of the difficult issues in such systems is how to construct large-scale dialogue knowledge that matches the dialogue modelling of a dialogue system. This paper describes how we have accomplished the short-term construction of large-scale and…

Learning Materials Recommendation Using Good Learners' Ratings and Content-Based Filtering

ERIC Educational Resources Information Center

Ghauth, Khairil Imran; Abdullah, Nor Aniza

2010-01-01

The enormity of the amount of learning materials in e-learning has led to the difficulty of locating suitable learning materials for a particular learning topic, creating the need for recommendation tools within a learning context. In this paper, we aim to address this need by proposing a novel e-learning recommender system framework that is based…

Continued use of an interactive computer game-based visual perception learning system in children with developmental delay.

PubMed

Lin, Hsien-Cheng; Chiu, Yu-Hsien; Chen, Yenming J; Wuang, Yee-Pay; Chen, Chiu-Ping; Wang, Chih-Chung; Huang, Chien-Ling; Wu, Tang-Meng; Ho, Wen-Hsien

2017-11-01

This study developed an interactive computer game-based visual perception learning system for special education children with developmental delay. To investigate whether perceived interactivity affects continued use of the system, this study developed a theoretical model of the process in which learners decide whether to continue using an interactive computer game-based visual perception learning system. The technology acceptance model, which considers perceived ease of use, perceived usefulness, and perceived playfulness, was extended by integrating perceived interaction (i.e., learner-instructor interaction and learner-system interaction) and then analyzing the effects of these perceptions on satisfaction and continued use. Data were collected from 150 participants (rehabilitation therapists, medical paraprofessionals, and parents of children with developmental delay) recruited from a single medical center in Taiwan. Structural equation modeling and partial-least-squares techniques were used to evaluate relationships within the model. The modeling results indicated that both perceived ease of use and perceived usefulness were positively associated with both learner-instructor interaction and learner-system interaction. However, perceived playfulness only had a positive association with learner-system interaction and not with learner-instructor interaction. Moreover, satisfaction was positively affected by perceived ease of use, perceived usefulness, and perceived playfulness. Thus, satisfaction positively affects continued use of the system. The data obtained by this study can be applied by researchers, designers of computer game-based learning systems, special education workers, and medical professionals. Copyright © 2017 Elsevier B.V. All rights reserved.

Visual Hybrid Development Learning System (VHDLS) framework for children with autism.

PubMed

Banire, Bilikis; Jomhari, Nazean; Ahmad, Rodina

2015-10-01

The effect of education on children with autism serves as a relative cure for their deficits. As a result of this, they require special techniques to gain their attention and interest in learning as compared to typical children. Several studies have shown that these children are visual learners. In this study, we proposed a Visual Hybrid Development Learning System (VHDLS) framework that is based on an instructional design model, multimedia cognitive learning theory, and learning style in order to guide software developers in developing learning systems for children with autism. The results from this study showed that the attention of children with autism increased more with the proposed VHDLS framework.

Task-Oriented Spoken Dialog System for Second-Language Learning

ERIC Educational Resources Information Center

Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun

2016-01-01

This paper introduces a Dialog-Based Computer Assisted second-Language Learning (DB-CALL) system using task-oriented dialogue processing technology. The system promotes dialogue with a second-language learner for a specific task, such as purchasing tour tickets, ordering food, passing through immigration, etc. The dialog system plays a role of a…