AI 中文总结
该研究探讨执行者效应是否适用于计算机科学教学，分析334名学生的日志数据发现主动实践学习成果是被动活动的3.2倍，其中代码编写对成绩提升的关联度最强。
AI 中文摘要
“执行者效应”表明，主动开展实践活动与学习成果的关联度远高于被动观看内容。在执行者效应的相关研究中，“做”特指主动实践，但这种分类将不同形式的主动实践视为等同，未明确是否存在某些类型的主动实践比其他类型更有效。本文研究执行者效应是否适用于计算机科学教学，以及是否存在某些实践形式相较于其他形式更为突出。我们分析了11个学期共334名学生的日志数据，这些学生使用包含五种内容类型的交互式实践系统学习入门和中级Java，内容类型包括Code Writing、Code Tracing、Code Completion、Code Visualizations和Code Explanations。与先前执行者效应研究一致，我们发现主动实践活动与学习成果的关联度是被动活动的3.2倍。有趣的是，在主动实践中，Code Writing与后测成绩提升的关联度最强，其他活动类型均未表现出可比的关联。这些结果凸显了具有挑战性、反馈支持的实践活动（如Code Writing问题）的重要性。
英文摘要
The "doer effect" suggests that actively doing practice activities is more strongly associated with learning outcomes than passively viewing content. In the doer effect literature, "doing" refers specifically to active practice. However, this categorization treats different forms of active practice as equivalent, leaving open whether some types of active practice are more effective than others. In this paper, we investigate whether the doer effect extends to computer science instruction and whether some forms of doing stand out compared to other forms. We analyze log data from 334 students across 11 semesters of introductory and intermediate Java who used an interactive practice system with five content types: Code Writing, Code Tracing, Code Completion, Code Visualizations, and Code Explanations. Consistent with prior doer effect work, we find that active practice activities were associated with 3.2 times better learning outcomes than passive activities. Interestingly, among the active practice, code writing was the most strongly associated with improved posttest performance, while no other activity type showed a comparable association. These results highlight the importance of challenging, feedback-supported practice activities, such as code writing problems.
