Time management is crucial for college students' academic success and learning of computer programming. Yet the changes of time management behaviors and their associations with learning outcomes are underexplored in online learning of programming. To address the gap, this study employed an intensive longitudinal approach to examine undergraduates’ time management behaviors in an online programming problem system. Specifically, we analyzed weekly indicators of academic procrastination and spaced practice derived from programming traces. We applied dynamic structural equation modeling to examine the changes in these behaviors over time and their correlations with weekly quiz performance. Academic procrastination and self-selected spaced practice showed a significant upward trend over time, while incentivized spaced practice exhibited a significant downward trend. Moreover, students with prior programming experience showed a greater growth rate in spacing behaviors. At both within- and between-person levels, procrastination predicted quiz performance significantly and negatively, while self-selected spaced practice predicted quiz performance significantly and positively. In contrast, incentivized spaced practice predicted quiz performance positively at the within-person level but negatively at the between-person level. Additionally, quiz performance in the current week predicted subsequent time management behaviors significantly. These findings contribute to the understanding of procrastination and spaced practice in online programming learning and have implications for the design of scaffolding on time management. Furthermore, this study demonstrates the significance of combining intensive longitudinal approaches and action logs in examining the temporality of learning in online environments.

中文翻译：

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在线编程问题系统中的学业拖延、激励和自我选择的间隔练习以及测验表现：深入的纵向调查

时间管理对于大学生的学业成功和计算机编程的学习至关重要。然而，在在线编程学习中，时间管理行为的变化及其与学习成果的关联尚未得到充分探索。为了解决这一差距，本研究采用了密集的纵向方法来检查本科生在在线编程问题系统中的时间管理行为。具体来说，我们分析了来自编程痕迹的学术拖延和间隔实践的每周指标。我们应用动态结构方程模型来检查这些行为随时间的变化及其与每周测验表现的相关性。随着时间的推移，学业拖延和自我选择的间隔练习呈现出显着的上升趋势，而激励间隔练习则呈现出显着的下降趋势。此外，具有编程经验的学生在间隔行为方面表现出更大的增长率。在人内和人与人之间的水平上，拖延对测验表现有显着的负面影响，而自我选择的间隔练习则对测验表现有显着的正面预测。相比之下，激励间隔练习对人内水平的测验表现有积极的预测作用，但在人与人之间的水平上有消极的预测作用。此外，本周的测验表现可以显着预测随后的时间管理行为。这些发现有助于理解在线编程学习中的拖延和间隔实践，并对时间管理支架的设计具有影响。此外，这项研究证明了结合强化纵向方法和行动日志在检查在线环境中学习的时间性方面的重要性。