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Hsu, Pi-Shan; Chang, Te-Jeng; Wu, Ming-Hsiung – International Journal of Distance Education Technologies, 2009
The level of learners' expertise has been used as a metric and diagnostic mechanism of instruction. This metric influences mental effort directly according to the applications of cognitive load theory. Cognitive efficiency, an optimal measurement technique of expertise, was developed by Kalyuga and Sweller to replace instructional efficiency in…
Descriptors: Electronic Learning, Measurement Techniques, Expertise, Cognitive Processes
Wuttke, Heinz-Dietrich; Henke, Karsten – Interactive Technology and Smart Education, 2009
Purpose: The content, provided in learning management systems (LMS), is often text oriented as in a usual textbook, extended by some animations and links. Hands on activities and experiments are not possible. The paper aims to give an overview about the concept to couple smart simulation and assessment tools with an LMS to provide a more…
Descriptors: Feedback (Response), Experiential Learning, Student Evaluation, Teaching Methods
Buzzi, Marina, Ed. – InTech, 2010
E-Learning is a vast and complex research topic that poses many challenges in every aspect: educational and pedagogical strategies and techniques and the tools for achieving them; usability, accessibility and user interface design; knowledge sharing and collaborative environments; technologies, architectures, and protocols; user activity…
Descriptors: Cartoons, Foreign Countries, Electronic Learning, Distance Education
Ben-Naim, Dror; Bain, Michael; Marcus, Nadine – International Working Group on Educational Data Mining, 2009
It has been recognized that in order to drive Intelligent Tutoring Systems (ITSs) into mainstream use by the teaching community, it is essential to support teachers through the entire ITS process: Design, Development, Deployment, Reflection and Adaptation. Although research has been done on supporting teachers through design to deployment of ITSs,…
Descriptors: Foreign Countries, Intelligent Tutoring Systems, Computer System Design, Computer Managed Instruction
Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2009
The Cognitive Tutor Authoring Tools (CTAT) support creation of a novel type of tutors called example-tracing tutors. Unlike other types of ITSs (e.g., model-tracing tutors, constraint-based tutors), example-tracing tutors evaluate student behavior by flexibly comparing it against generalized examples of problem-solving behavior. Example-tracing…
Descriptors: Feedback (Response), Student Behavior, Intelligent Tutoring Systems, Problem Solving
Kazi, Hameedullah; Haddawy, Peter; Suebnukarn, Siriwan – International Journal of Artificial Intelligence in Education, 2009
In well-defined domains such as Physics, Mathematics, and Chemistry, solutions to a posed problem can objectively be classified as correct or incorrect. In ill-defined domains such as medicine, the classification of solutions to a patient problem as correct or incorrect is much more complex. Typical tutoring systems accept only a small set of…
Descriptors: Foreign Countries, Problem Based Learning, Problem Solving, Correlation
Shuqun, Yang; Shuliang, Ding; Zhiqiang, Yao – International Journal of Distance Education Technologies, 2009
Cognitive diagnosis (CD) plays an important role in intelligent tutoring system. Computerized adaptive testing (CAT) is adaptive, fair, and efficient, which is suitable to large-scale examination. Traditional cognitive diagnostic test needs quite large number of items, the efficient and tailored CAT could be a remedy for it, so the CAT with…
Descriptors: Monte Carlo Methods, Distance Education, Adaptive Testing, Intelligent Tutoring Systems
Peer reviewedPatel, Ashok; Russell, David; Kinshuk; Oppermann, Reinhard; Rashev, Rossen – Information Services & Use, 1998
Discussion of context focuses on the various contexts surrounding the design and use of intelligent tutoring systems and proposes an initial framework of contexts by classifying them into three major groupings: interactional; environmental, including classifications of knowledge and social environment; and objectival contexts. (Author/LRW)
Descriptors: Classification, Computer System Design, Context Effect, Intelligent Tutoring Systems
Blessing, Stephen B.; Gilbert, Stephen B.; Ourada, Stephen; Ritter, Steven – International Journal of Artificial Intelligence in Education, 2009
Intelligent Tutoring Systems (ITSs) that employ a model-tracing methodology have consistently shown their effectiveness. However, what evidently makes these tutors effective, the cognitive model embedded within them, has traditionally been difficult to create, requiring great expertise and time, both of which come at a cost. Furthermore, an…
Descriptors: Intelligent Tutoring Systems, Cognitive Processes, Models, Expertise
The Social Semantic Web in Intelligent Learning Environments: State of the Art and Future Challenges
Jovanovic, Jelena; Gasevic, Dragan; Torniai, Carlo; Bateman, Scott; Hatala, Marek – Interactive Learning Environments, 2009
Today's technology-enhanced learning practices cater to students and teachers who use many different learning tools and environments and are used to a paradigm of interaction derived from open, ubiquitous, and socially oriented services. In this context, a crucial issue for education systems in general, and for Intelligent Learning Environments…
Descriptors: Models, Interaction, Educational Technology, Design Requirements
Stankov, Slavomir; Rosic, Marko; Zitko, Branko; Grubisic, Ani – Computers & Education, 2008
Special classes of asynchronous e-learning systems are the intelligent tutoring systems which represent an advanced learning and teaching environment adaptable to individual student's characteristics. Authoring shells have an environment that enables development of the intelligent tutoring systems. In this paper we present, in entirety, for the…
Descriptors: Elementary Secondary Education, Intelligent Tutoring Systems, Artificial Intelligence, Tutoring
Curilem, S. Gloria; Barbosa, Andrea R.; de Azevedo, Fernando M. – Computers & Education, 2007
This article proposes a mathematical model of Intelligent Tutoring Systems (ITS), based on observations of the behaviour of these systems. One of the most important problems of pedagogical software is to establish a common language between the knowledge areas involved in their development, basically pedagogical, computing and domain areas. A…
Descriptors: Student Characteristics, Mathematical Models, Intelligent Tutoring Systems, Computer Software
Liao, Ching-Jung; Chou, Chien-Chih; Yang, Jin-Tan David – International Journal of Distance Education Technologies, 2009
The purpose of this study is to incorporate adaptive ontology into ubiquitous learning grid to achieve seamless learning environment. Ubiquitous learning grid uses ubiquitous computing environment to infer and determine the most adaptive learning contents and procedures in anytime, any place and with any device. To achieve the goal, an…
Descriptors: Individualized Instruction, Simulation, Educational Environment, College Freshmen
Hayashi, Yusuke; Bourdeau, Jacqueline; Mizoguchi, Riichiro – International Journal of Artificial Intelligence in Education, 2009
This paper describes the achievements of an innovative eight-year research program first introduced in Mizoguchi and Bourdeau (2000), which was aimed at building a theory-aware authoring system by using ontological engineering. To date, we have proposed OMNIBUS, an ontology that comprehensively covers different learning/instructional theories and…
Descriptors: Foreign Countries, Theory Practice Relationship, Engineering, Teaching Methods
Huang, Yueh-Min; Huang, Tien-Chi; Wang, Kun-Te; Hwang, Wu-Yuin – Educational Technology & Society, 2009
The ability to apply existing knowledge in new situations and settings is clearly a vital skill that all students need to develop. Nowhere is this truer than in the rapidly developing world of Web-based learning, which is characterized by non-sequential courses and the absence of an effective cross-subject guidance system. As a result, questions…
Descriptors: Markov Processes, Transfer of Training, Probability, Internet

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