AuthorIT & TutorIT: Attacking Bloom's 2-Sigma Problem from a Different Perspective

Autor/inn/en	Scandura, Joseph M.; Novak, Elena
Titel	AuthorIT & TutorIT: Attacking Bloom's 2-Sigma Problem from a Different Perspective
Quelle	In: Technology, Instruction, Cognition and Learning, 10 (2017) 4, S.267-288 (22 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1540-0182
Schlagwörter	Bibliografie; Intelligent Tutoring Systems; Decision Making; Knowledge Representation; Learning Theories; Artificial Intelligence; Instructional Design + Suchen Sie Ihr Suchwort? Intelligentes Tutorsystem; Decision-making; Entscheidungsfindung; Wissensrepräsentation; Learning theory; Lerntheorie; Künstliche Intelligenz; Lesson concept; Lessonplan; Unterrichtsentwurf
Abstract	AuthorIT and TutorIT represent a fundamentally different approach to building and delivering adaptive learning systems. Intelligent Tutoring Systems (ITS) guide students as they solve problems. BIG DATA systems make pedagogical decisions based on average student performance. Decision making in AuthorIT and TutorIT is designed to model the human tutoring process as a whole. Just as good human tutors need to know the subject matter, AuthorIT is used to systematically identify what students need to learn for success. TutorIT takes this information as input and makes all pedagogical decisions automatically. This dramatically reduces the time and expense of building adaptive learning systems, while simultaneously having the potential of ensuring predetermined levels of mastery. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01