Contrasting Fundamental Assumptions in Adaptive Learning and Modeling Human Tutors with TutorIT

Autor/in	Scandura, Joseph M.
Titel	Contrasting Fundamental Assumptions in Adaptive Learning and Modeling Human Tutors with TutorIT
Quelle	In: Technology, Instruction, Cognition and Learning, 10 (2017) 4, S.259-265 (7 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1540-0182
Schlagwörter	Intelligent Tutoring Systems; Tutors; Tutorial Programs; Delivery Systems; Knowledge Representation + Suchen Sie Ihr Suchwort? Intelligentes Tutorsystem; Förderlehrer; Lehrender; Tutor; Tutorial programmes; Förderprogramm; Lernprogramm; Tutorensystem; Auslieferung; Wissensrepräsentation
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01