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ERIC Number: EJ875196
Record Type: Journal
Publication Date: 2010-May
Pages: 12
Abstractor: As Provided
Reference Count: 0
ISBN: N/A
ISSN: ISSN-0360-1315
Optimal Self-Explanation Prompt Design in Dynamic Multi-Representational Learning Environments
Yeh, Yu-Fang; Chen, Mei-Chi; Hung, Pi-Hsia; Hwang, Gwo-Jen
Computers & Education, v54 n4 p1089-1100 May 2010
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.)
Elsevier. 6277 Sea Harbor Drive, Orlando, FL 32887-4800. Tel: 877-839-7126; Tel: 407-345-4020; Fax: 407-363-1354; e-mail: usjcs@elsevier.com; Web site: http://www.elsevier.com
Publication Type: Journal Articles; Reports - Evaluative
Education Level: Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A