Towards a Framework for Modelling Engagement Dynamics in Multiple Learning Domains

Autor/inn/en	Käser, Tanja; Baschera, Gian-Marco; Busetto, Alberto Giovanni; Klingler, Severin; Solenthaler, Barbara; Buhmann, Joachim M.; Gross, Markus
Titel	Towards a Framework for Modelling Engagement Dynamics in Multiple Learning Domains
Quelle	In: International Journal of Artificial Intelligence in Education, 22 (2013) 1-2, S.59-83 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1560-4292
DOI	10.3233/JAI-130026
Schlagwörter	Dyslexia; Learning Disabilities; Learner Engagement; Models; Intelligent Tutoring Systems; Spelling Instruction; Mathematics Instruction + Suchen Sie Ihr Suchwort? Dyslexics; Legasthenie; Lese-Rechtschreib-Schwäche; Learning handicap; Lernbehinderung; Analogiemodell; Intelligentes Tutorsystem; Orthographieunterricht; Rechtschreibunterricht; Mathematics lessons; Mathematikunterricht
Abstract	In this paper, we explore the possibility of a general framework for modelling engagement dynamics in software tutoring, focusing on the cases of developmental dyslexia and developmental dyscalculia. This project aims at capturing the similar engagement state patterns for the two learning disabilities. We start by presenting a model of engagement dynamics in spelling learning, which relates input behaviour to learning and explains the dynamics of engagement states. Predictive power of extracted features is increased by incorporating domain knowledge in the pre-processing. The introduced model enables the prediction of focused and receptive states, and of forgetting. In the second part, we extend the model to a more general framework, which takes into account the similarities and dissimilarities of the two studied cases. Finally, we define desirable properties of a general engagement dynamics model, while analysing the reusability of the introduced spelling model. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01