Learning programming is difficult, and many students fail or have poor outcomes. To learn to program means to master steps in the complex problem-solving activity. Previous research uncovered a rich set of domain-specific and generic cognitive and metacognitive strategies students use when they learn to program. The processes that problem-solving experts demonstrate are very similar to those studied by self-regulated learning researchers. This study proposes Self-Regulated Learning (SRL) process types derived from the SRL phases indicators developed from log data captured from students' interaction with the instructional scaffold for programming assignments in LMS. The process types were defined from theoretical and pragmatic perspectives, with the aim to indicate concrete interventions for improving problemsolving skills. We have observed and quantified students' use of the SRL processes of distinct types in the series of five problem-solving assignments. We have also observed the progression of SRL processes used by each student in the assignments. Our modelling showed that students with domain knowledge at the same level achieve higher assignment marks when they demonstrate SRL processes at the higher level; importantly, students with the lowest programming skills benefit the most.

学习编程很困难，许多学生失败或成绩不佳。学习编程意味着在复杂的问题解决活动中掌握步骤。先前的研究揭示了学生在学习编程时使用的一组丰富的特定领域和通用认知和元认知策略。问题解决专家展示的过程与自我调节学习研究人员研究的过程非常相似。本研究提出了自调节学习 (SRL) 过程类型，这些过程类型源自 SRL 阶段指标，这些指标是从学生与 LMS 中编程作业的教学支架交互中捕获的日志数据中开发的。过程类型是从理论和实用的角度定义的，旨在指出提高解决问题能力的具体干预措施。我们观察并量化了学生在五个问题解决作业系列中对不同类型的 SRL 过程的使用。我们还观察了每个学生在作业中使用的 SRL 过程的进展。我们的模型表明，具有相同领域知识的学生在展示更高级别的 SRL 过程时会获得更高的作业分数；重要的是，编程技能最低的学生受益最大。