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Kaburlasos, Vassilis G.; Marinagi, Catherine C.; Tsoukalas, Vassilis Th. – Computers & Education, 2008
This work presents innovative cybernetics (feedback) techniques based on Bayesian statistics for drawing questions from an Item Bank towards personalized multi-student improvement. A novel software tool, namely "Module for Adaptive Assessment of Students" (or, "MAAS" for short), implements the proposed (feedback) techniques. In conclusion, a pilot…
Descriptors: Feedback (Response), Student Improvement, Computer Science, Bayesian Statistics
Tzouveli, Paraskevi; Mylonas, Phivos; Kollias, Stefanos – Computers & Education, 2008
Taking advantage of the continuously improving, web-based learning systems plays an important role for self-learning, especially in the case of working people. Nevertheless, learning systems do not generally adapt to learners' profiles. Learners have to spend a lot of time before reaching the learning goal that is compatible with their knowledge…
Descriptors: Educational Needs, Distance Education, Knowledge Level, Questionnaires
Dori, Yehudit J.; Dori, Dov – 1994
Recent advances in information technology have made feasible the development of intelligent computer assisted instruction study units. Analysis and design of such systems require the active involvement of a development team consisting of domain experts, educators, and knowledge engineers. Science and technology teaching methods are frequently…
Descriptors: Computer Assisted Instruction, Courseware, Foreign Countries, Intelligent Tutoring Systems
Peer reviewedBouras, Christos; Triantafillou, Vassilis; Tsiatsos, Thrasyvoulos – Educational Technology & Society, 2002
Discusses collaborative virtual learning environments and presents a system architecture to support such environments, defined by user needs and using state-of-the-art technologies. Includes a description of INVITE (Intelligent Distributed Virtual Training Environment), a project funded by the European Commission. (Author/LRW)
Descriptors: Foreign Countries, Information Technology, Intelligent Tutoring Systems, Online Courses
Peer reviewedKhan, Masood Mehmood – Electronic Library, 2002
Describes the implementation of an intelligent tutoring system that employs a game environment and object-oriented user interface for teaching and learning, based on a computer game developed for industrial training. Discusses adventure games, game environments in education, simulation support, and user interface design. (Author/LRW)
Descriptors: Computer Games, Computer Interfaces, Computer Simulation, Educational Games
Peer reviewedPatel, Ashok; Kinshuk; Russell, David – Information Services & Use, 1998
Describes an intelligent assessment system for numeric disciplines that works in conjunction with the intelligent tutoring tools developed by Teaching and Learning Technology (TLTP) Byzantium, a consortium of six U.K. universities. Topics include intelligent tutoring tools based on cognitive apprenticeship framework, a history of computerized…
Descriptors: Evaluation Methods, Foreign Countries, Futures (of Society), Higher Education
Peer reviewedOrey, Michael; Zhao, Ruimin; Fan, Huey-Ling; Keenan, Ron – Computers in Human Behavior, 1998
Describes the results of an effectiveness evaluation of an "intelligently coached simulation," the SINCGARS Tutor, that was developed to train military officers how to operate a SINCGARS radio. Posttests showed officers trained on the computerized tutor performed more accurately than a group trained on the actual equipment. (Author/LRW)
Descriptors: Computer Simulation, Intelligent Tutoring Systems, Military Training, Pretests Posttests
Peer reviewedSheremetov, Leonid; Nunez, Gustavo – Journal of Interactive Learning Research, 1999
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…
Descriptors: Artificial Intelligence, Educational Environment, Intelligent Tutoring Systems, Interaction
Gardner, Howard – TECHNOS, 2000
Explains the relationship between computers and multiple intelligences and explores its potential. Topics include behaviorism and cognitivism; constructivism; multiple representations in the human mind, including various forms of intelligence; individual differences; the challenge of altering early representations; and machine versus human tutors.…
Descriptors: Behaviorism, Cognitive Processes, Constructivism (Learning), Individual Differences
Peer reviewedGilbert, Juan E.; Han, C. Y. – Journal of Computing in Higher Education, 2002
Examined whether there was a significant difference in learner outcomes from the use of Arthur (Gilbert & Han, 1999), a computer-based adaptive instructional system that provides personalized instruction to each learner. Found that Arthur does provide a significant difference in learner outcomes. (EV)
Descriptors: Courseware, Higher Education, Individualized Instruction, Instructional Effectiveness
Vasilakos, Thanos; Devedzic, Vladan; Kinshuk; Pedrycz, Witold – Journal of Interactive Learning Research, 2004
This article discusses some important aspects of Web Intelligence (WI) in the context of educational applications. Some of the key components of WI have already attracted developers of web-based educational systems for quite some time- ontologies, adaptivity and personalization, and agents. The paper focuses on the application of Computational…
Descriptors: Intelligent Tutoring Systems, Internet, Web Based Instruction, Educational Technology
Mowlds, Frances; Roche, Bernard-Joseph; Mangina, Eleni – Campus-Wide Information Systems, 2005
Purpose: One of the greatest challenges facing any intelligent tutoring system is being able to adapt its behaviour based on the student's current knowledge level, ability, needs and wishes within a course. This paper aims to present a framework of BDI agents within an agent-based intelligent tutoring system (ABITS). Design/methodology/approach: A…
Descriptors: Knowledge Level, Intelligent Tutoring Systems, Tutoring, Cognitive Structures
Cetintas, Suleyman; Si, Luo; Xin, Yan Ping; Hord, Casey – International Working Group on Educational Data Mining, 2009
This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…
Descriptors: Programming, Evidence, Intelligent Tutoring Systems, Regression (Statistics)
Mitrovic, Antonija; Martin, Brent; Suraweera, Pramuditha; Zakharov, Konstantin; Milik, Nancy; Holland, Jay; McGuigan, Nicholas – International Journal of Artificial Intelligence in Education, 2009
Over the last decade, the Intelligent Computer Tutoring Group (ICTG) has implemented many successful constraint-based Intelligent Tutoring Systems (ITSs) in a variety of instructional domains. Our tutors have proven their effectiveness not only in controlled lab studies but also in real classrooms, and some of them have been commercialized.…
Descriptors: Foreign Countries, Investment, Intelligent Tutoring Systems, Artificial Intelligence
Botsios, Sotirios; Georgiou, Dimitrios A. – International Journal of Distance Education Technologies, 2009
Adaptation and personalization services in e-learning environments are considered the turning point of recent research efforts, as the "one-size-fits-all" approach has some important drawbacks, from the educational point of view. Adaptive Educational Hypermedia Systems in World Wide Web became a very active research field and the need of…
Descriptors: Electronic Learning, Educational Research, Literature Reviews, Standards

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