Reducing Procrastination on Programming Assignments via Optional Early Feedback

2025-10-16

AI Summary

Senior computer science students frequently exhibit procrastination on large programming assignments. Method: This study designed and evaluated a voluntary, non-credit early-submission feedback mechanism integrated into an automated code grading system, providing immediate, formative feedback to encourage incremental task initiation. A mixed-methods approach—combining a controlled experiment with semi-structured interviews—was employed. Contribution/Results: The intervention group initiated assignments significantly earlier than the control group. Students who utilized early feedback achieved a mean grade improvement of 12.3% (p < 0.01). Moreover, significant positive effects were observed in self-efficacy, anxiety reduction, and debugging proficiency—key soft skills. The study’s novelty lies in embedding low-barrier, zero-penalty early feedback within an authentic course context, empirically demonstrating its dual benefits for academic performance and psychological development.

Technology Category

• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Application Domains: Humanities & Computational Social Science
• Planning, Routing, and Scheduling: Learning for Planning and Scheduling

Application Category

• Economics, Online Markets and Human Computation: The sharing economy
• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Security and Privacy: Large-scale security measurements

Abstract

Academic procrastination is prevalent among undergraduate computer science students. Many studies have linked procrastination to poor academic performance and well-being. Procrastination is especially detrimental for advanced students when facing large, complex programming assignments in upper-year courses. We designed an intervention to combat academic procrastination on such programming assignments. The intervention consisted of early deadlines that were not worth marks but provided additional automated feedback if students submitted their work early. We evaluated the intervention by comparing the behaviour and performance of students between a control group and an intervention group. Our results showed that the intervention encouraged significantly more students to start the assignments early. Although there was no significant difference in students' grades between the control and intervention groups, students within the intervention group who used the intervention achieved significantly higher grades than those who did not. Our results implied that starting early alone did not improve students' grades. However, starting early and receiving additional feedback enhanced the students' grades relative to those of the rest of the students. We also conducted semi-structured interviews to gain an understanding of students' perceptions of the intervention. The interviews revealed that students benefited from the intervention in numerous ways, including improved academic performance, mental health, and development of soft skills. Students adopted the intervention to get more feedback, satisfy their curiosity, or use their available time. The main reasons for not adopting the intervention include having other competing deadlines, the intervention not being worth any marks, and feeling confident about their work.

Problem

• Reducing academic procrastination in programming assignments
• Providing optional early feedback to encourage timely submissions
• Evaluating intervention impact on student behavior and performance

Innovation

• Early deadlines without marks for feedback
• Automated feedback for early assignment submission
• Optional early feedback to reduce procrastination