大规模CS1课程中学生讲师偏好的存在与发展研究
Investigating the Presence and Development of Student Instructor Preferences in a Large-Scale CS1 Course
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中文总结 AI 辅助
本研究利用新型学习平台数据，探究大规模CS1课程中学生讲师偏好的动态发展，发现偏好随经历变化，最终偏好与性别、先验编程经验相关，为计算机科学教育提供了相关见解。
中文摘要 AI 辅助
已有研究证实了学生讲师偏好的重要性，并确定了多种影响因素。然而，由于常规课程结构的限制以及依赖单次测量，学生讲师偏好如何发展和变化的动态过程尚未得到充分理解。为了填补这一空白，我们利用了一种新型学习平台的数据，该平台为学生提供了多位讲师创建的教学内容。该平台能够量化整个学期内偏好的出现和演变，因为学生可以反复选择不同讲师的内容。对学生初始和最终讲师偏好的考察表明，偏好是一种动态结构，会不断被经历塑造。此外，我们对偏好与学生特征之间关联的分析揭示了一幅复杂的图景：学生属性与初始偏好无显著关联，但最终偏好在性别和自我报告的先验编程经验方面存在显著差异。该分析通过加深对计算机科学教育中学生讲师偏好以及师生关系的理解，为现有知识体系做出了贡献。我们还提供了实践见解，可供机构和讲师在多位讲师合作开设课程时参考。
英文摘要
Prior research has established the importance of student instructor preferences and identified various influencing factors. However, the dynamics of how student instructor preferences develop and change are less well understood, due to the limitations of common course structures and reliance on one-time measurements. To bridge this gap, we utilize data from a novel learning platform that provides students with access to instructional content created by multiple instructors. This platform enables the quantification of preference emergence and evolution throughout an entire semester, as students repeatedly select content from different instructors. Examining both initial and final student instructor preferences suggests that preference is a dynamic construct continually shaped by experiences. Furthermore, our analysis of the associations between preferences and student characteristics reveals a nuanced picture: while student attributes did not significantly correlate with initial preferences, substantial differences emerged in final preferences across genders and self-reported prior programming experience. This analysis contributes to the existing body of knowledge by expanding our understanding of student instructor preferences and student-instructor relationships in computer science education. We also provide practical insights that institutions and instructors can draw on when multiple instructors collaborate on a course.
