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A Deterministic AI Foundation for Modeling Human Tutors: Fundamental Assumptions in Structural Learning Theory
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Scandura, Joseph M. – Technology, Instruction, Cognition and Learning, 2018
This paper summarizes key stages in development of the Structural Learning Theory (SLT) and explains how and why it is now possible to model human tutors in a highly efficient manner. The paper focuses on evolution of the SLT, a deterministic theory of teaching and learning, on which AuthorIT authoring and TutorIT delivery systems have been built.…
Descriptors: Artificial Intelligence, Models, Tutors, Learning Theories
Widening the Knowledge Acquisition Bottleneck for Constraint-Based Tutors
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Suraweera, Pramuditha; Mitrovic, Antonija; Martin, Brent – International Journal of Artificial Intelligence in Education, 2010
Intelligent Tutoring Systems (ITS) are effective tools for education. However, developing them is a labour-intensive and time-consuming process. A major share of the effort is devoted to acquiring the domain knowledge that underlies the system's intelligence. The goal of this research is to reduce this knowledge acquisition bottleneck and better…
Descriptors: Intelligent Tutoring Systems, Programming, Engineering, Tutoring
Of Hubert Dreyfus and Dead Horses: Some Thoughts on Dreyfus'"What Computers Still Can't Do."
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Koschmann, Timothy – Artificial Intelligence, 1996
Reviews Dreyfus's writings about human cognition and artificial intelligence (AI), and explains some of the implications of his position, particularly in education. Topics include Dreyfus' critique of AI, representationlaism and expertise, technology and its role in instruction, computer-assisted instruction, and intelligent tutoring systems. (JKP)
Descriptors: Artificial Intelligence, Cognitive Development, Cognitive Processes, Cognitive Psychology
Artificial Tutoring Systems: What Computers Can and Can't Know.
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Frick, Theodore W. – Journal of Educational Computing Research, 1997
Maccia's epistemology of intelligent natural systems implies that computer systems must develop qualitative intelligence before knowledge representation and natural language understanding can be achieved. Emotion and sensation--capabilities which computers do not currently possess are vital to the growth of the mind (Stanley I. Greenspan).…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer System Design, Computer Uses in Education
ED-Media 94--World Conference on Educational Multimedia and Hypermedia (Vancouver, British Columbia, Canada, June 25-30, 1994). Short Papers.
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Abbanat, Rob; And Others – 1994
The 49 short (one- or two-page) conference papers presented here document concern for the use of hypermedia and multimedia technology in education. Discussion includes the use of multimedia technology in various subject areas, programming languages, electronic books, intelligent tutoring systems, distance education, knowledge representation,…
Descriptors: Computer Assisted Instruction, Computer Games, Computer Software Development, Computer Uses in Education
Modelling Teaching Strategies.
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Major, Nigel – Journal of Artificial Intelligence in Education, 1995
Describes a modelling language for representing teaching strategies, based in the context of the COCA intelligent tutoring system. Examines work on meta-reasoning in knowledge-based systems and describes COCA's architecture, giving details of the language used for representing teaching knowledge. Discusses implications for future work. (AEF)
Descriptors: Computer Assisted Instruction, Computer System Design, Computer Uses in Education, Educational Strategies