ERIC Number: EJ1257782
Record Type: Journal
Publication Date: 2017
Pages: 7
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1540-0182
EISSN: N/A
Contrasting Fundamental Assumptions in Adaptive Learning and Modeling Human Tutors with TutorIT
Scandura, Joseph M.
Technology, Instruction, Cognition and Learning, v10 n4 p259-265 2017
Adaptive learning has become a dominant theme in settings ranging from academic laboratories to commercial education. Despite tens of millions of dollars invested by governments, universities, the private sector and companies, however, progress has been both costly and limited. No established initiative has attempted to model the processes human teachers and tutors use in interacting with students. This article is an attempt to explain why. It also outlines a potential solution to the problem: Highly efficient authoring and delivering platforms that make it possible to both efficiently create and deliver human like tutorials.
Descriptors: Intelligent Tutoring Systems, Tutors, Tutorial Programs, Delivery Systems, Knowledge Representation
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A