Optimal Self-Explanation Prompt Design in Dynamic Multi-Representational Learning Environments

Autor/inn/en	Yeh, Yu-Fang; Chen, Mei-Chi; Hung, Pi-Hsia; Hwang, Gwo-Jen
Titel	Optimal Self-Explanation Prompt Design in Dynamic Multi-Representational Learning Environments
Quelle	In: Computers & Education, 54 (2010) 4, S.1089-1100 (12 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0360-1315
DOI	10.1016/j.compedu.2009.10.013
Schlagwörter	Animation; Undergraduate Students; Educational Environment; Outcomes of Education; Higher Education; Multimedia Materials; Scaffolding (Teaching Technique) + Suchen Sie Ihr Suchwort? Lernumgebung; Pädagogische Umwelt; Schulumwelt; Lernleistung; Schulerfolg; Hochschulbildung; Hochschulsystem; Hochschulwesen
Abstract	Self-explanation prompts are considered to be an important form of scaffolding in the comprehension of complex multimedia materials. However, there is little theoretical understanding to date of self-explaining prompt formats tailored to different expertise levels of learners to help them fully exploit the advantages of dynamic multi-representational materials. To address this issue, this study designed two types of self-explaining prompts: the reasoning-based prompts asked the learners to reason the action run of the animation; the predicting-based prompts asked the learners to predict the upcoming action of the animation, and then asked for reasoning if they made a wrong prediction. Furthermore, multiple indicators including learning outcome, cognitive load demand, learning time, and learning efficiency were used to interpret the prompts' effects on different expertise levels of learners. A total of 244 undergraduate students were randomly assigned to one of the three conditions: a control and two different self-explaining prompt conditions. The results indicate that the learning effects of self-explaining prompts depend on levels of learner expertise. Based on the results, this study makes recommendations for adaptive self-explaining prompt design. (Contains 1 table and 8 figures.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10