Enhancing the Automatic Generation of Hints with Expert Seeding

Autor/inn/en	Stamper, John; Barnes, Tiffany; Croy, Marvin
Titel	Enhancing the Automatic Generation of Hints with Expert Seeding
Quelle	In: International Journal of Artificial Intelligence in Education, 21 (2011) 1-2, S.153-167 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1560-4292
DOI	10.3233/JAI-2011-021
Schlagwörter	Cues; Prompting; Learning Strategies; Teaching Methods; Data Collection; Data Processing; Program Implementation; Formative Evaluation; Feedback (Response); Tutoring; Models; Markov Processes; Decision Making; Program Descriptions; Automation; Computer System Design; Artificial Intelligence; Problem Solving + Suchen Sie Ihr Suchwort? Stichwort; Benutzerführung; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Teaching method; Lehrmethode; Unterrichtsmethode; Data capture; Datensammlung; Datenverarbeitung; Förderkonzept; Nachhilfeunterricht; Analogiemodell; Markowscher Prozess; Decision-making; Entscheidungsfindung; Künstliche Intelligenz; Problemlösen
Abstract	The Hint Factory is an implementation of our novel method to automatically generate hints using past student data for a logic tutor. One disadvantage of the Hint Factory is the time needed to gather enough data on new problems in order to provide hints. In this paper we describe the use of expert sample solutions to "seed" the hint generation process. We show that just a few expert solutions give significant coverage (over 50%) for hints. This seeding method greatly speeds up the time needed to reliably generate hints. We discuss how this feature can be integrated into the Hint Factory and some potential pedagogical issues that the expert solutions introduce. (Contains 9 tables and 5 figures.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10