Ji Shi
ABSTRACT
Collaborative learning is widely used in higher education and much research has been conducted to find how group discussion contributes to students' learning performance. This study was aimed at 62 undergraduate students who participated in college physics courses. For four collaborative learning activities containing 12 discussion questions, data such as pre-test, post-test and group score were collected. The questions are divided into two categories: conceptual analysis questions and computational application questions according to the skills needed to solve the problems. Singular value decomposition (SVD) is used to decompose and reduce the dimension of the group collaborative learning score matrix. The decomposition results show that the student attributes influencing group discussion results are knowledge mastery and learning style while the governing question attributes include item difficulty and question type. The research methods provide a tool for quantifying collaborative learning and designing the attributes of group discussion questions in college physics.
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Index Terms
- Group Discussion in College Physics: A Case Study of Collaborative Learning Based on Data Mining
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