Self-Explanation Prompts on Problem-Solving Performance in an Interactive Learning Environment.
Self-Explanation Prompts on Problem-Solving Performance in an Interactive Learning Environment.
复制标题
自我解释提示交互式学习环境中解决问题的表现。
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Jane Howland
中科院分区：
文献类型：
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作者：
Kyungbin Kwon;Christiana Kumalasari;Jane Howland
本研究考察了自我解释提示对解决问题表现的影响。总共招募了47名学生，并对他们进行了在线学习环境中调试网络程序代码的培训。开放式自我解释组的学生被要求对自己的问题进行解释，而完全其他解释组的学生被提供了部分解释，并要求选择正确的关键词来完成它们。结果表明，学生在开放的自我解释条件下（a）优于调试任务，（B）感知更高的信心，他们的解释和他们的表现之间的质量表现出很强的正相关关系。这些结果证明了开放式自我解释提示的好处。探讨了自我解释的认知负荷和解释质量。
This study examined the effects of self-explanation prompts on problem-solving performance. In total, 47 students were recruited and trained to debug web-program code in an online learning environment. Students in an open self-explanation group were asked to explain the problem cases to themselves, whereas a complete other-explanation group was provided with partial explanations and asked to complete them by choosing correct key-words. The results indicate that students in the open self-explanation condition (a) outperformed in a debugging task, (b) perceived higher confidence for their explanations, and (c) showed a strong positive relationship between the quality of their explanation and their performance. These results demonstrate the benefits of the open self-explanation prompts. Cognitive load of self-explanation and quality of explanation are discussed.