Enhancing Self-Regulated Learning in CS Education Through Comment Analysis

This summer, my research focused on analyzing code comments to enhance our understanding of self-regulated learning (SRL) in computer science education. Recognizing that comments within code provide insight into a student's thought process, this project aimed to explore how, what, and why students comment while coding. My work involved extracting and organizing comments from code written by students in an undergraduate classroom setting, distinguishing between student-written comments and those provided by instructors. This distinction is crucial for accurately analyzing how students reflect on their problem-solving approaches and self-regulate their learning. By preparing the data for in-depth analysis, I have set the stage for future research to examine the relationship between comment use and successful SRL strategies in programming. The outcomes of this work have the potential to contribute significantly to educational models in computer science, providing educators with valuable insights into how to foster effective learning environments that support diverse learners.