The Impact of Group Discussion and Formation on Student Performance: An Experience Report in a Large CS1 Course

Tong Wu, Xiaohang Tang, Sam Wong, Xi Chen, Clifford A. Shaffer, Yan Chen
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Abstract

Programming instructors often conduct collaborative learning activities, such as Peer Instruction (PI), to enhance student motivation, engagement, and learning gains. However, the impact of group discussion and formation mechanisms on student performance remains unclear. To investigate this, we conducted an 11-session experiment in a large, in-person CS1 course. We employed both random and expertise-balanced grouping methods to examine the efficacy of different group mechanisms and the impact of expert students' presence on collaborative learning. Our observations revealed complex dynamics within the collaborative learning environment. Among 255 groups, 146 actively engaged in discussions, with 96 of these groups demonstrating improvement for poor-performing students. Interestingly, our analysis revealed that different grouping methods (expertise-balanced or random) did not significantly influence discussion engagement or poor-performing students' improvement. In our deeper qualitative analysis, we found that struggling students often derived benefits from interactions with expert peers, but this positive effect was not consistent across all groups. We identified challenges that expert students face in peer instruction interactions, highlighting the complexity of leveraging expertise within group discussions.
小组讨论和组建对学生成绩的影响:大型 CS1 课程的经验报告
程序设计教师经常开展协作学习活动,如同伴指导(PI),以提高学生的学习积极性、参与度和学习效果。然而,小组讨论和形成机制对学生成绩的影响仍不清楚。为了研究这个问题,我们在一门大型面授 CS1 课程中进行了一次为期 11 课时的实验。我们采用随机分组和专家平衡分组两种方法,考察了不同小组机制的有效性以及专家学生的存在对协作学习的影响。我们的观察揭示了协作学习环境中的复杂动态。在 255 个小组中,有 146 个小组积极参与讨论,其中 96 个小组的成绩较差学生的表现有所改善。有趣的是,我们的分析表明,不同的分组方法(专业平衡或随机分组)对讨论参与度或成绩差的学生的进步没有显著影响。在更深入的定性分析中,我们发现学困生往往能从与专家同学的互动中获益,但这种积极影响在所有小组中并不一致。我们发现了专家学生在同伴指导互动中面临的挑战,突出了在小组讨论中利用专业知识的复杂性。
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