Real-time Monitoring of Student Procrastination in a PSI First-year Programming Course

Procrastination is the intentional deferment of a scheduled task and is most often attributed (by the procrastinator) to a lack of available time prior to a deadline. Although the impact of the procrastination on student learning is widely debated, it has been correlated with a lack of external (or self) regulation, motivation, and performance anxiety. These contributors stand in contrast to the commonly asserted issue: lack of time. A lecture-centric course provides limited observations for evaluating actual student procrastination. Evidence is often subjective or anecdotal. In selfpaced Personalized System of Instruction (PSI) courses, observational opportunities can be further limited. Yet PSI can be an effective teaching strategy for course material such as that in a first-year, webbased, introductory programming course. Students (particularly first-year students) have diverse backgrounds and a varied technical literacy. In this particular course, students complete 18 units following a traditional PSI s-curve (reviewed below) in terms of content difficulty over the course of one semester. The content introduces students to two syntaxes and three programming paradigms (compiled, interpreted, and object-oriented languages). The PSI format allows individuals to invest the appropriate amount of time without overwhelming new programmers or underwhelming the more experienced. Most importantly, a well-designed PSI course may instill time management skills (though often as a hard lesson learned), thus countering procrastination habits. In this paper, we present a system developed to monitor and succinctly quantify student procrastination in real-time and evaluate its use for evaluating new course implementations, material, and instructor strategies. The web-based system uses formulated procrastination metrics to succinctly visualize student progress. Real-time monitoring of procrastination in tandem with student profile data (previous programming experience, etc.) are examined to correlate the impact of instructor encouragement, unit difficulty, external events (mid-terms, sporting events, etc.) and other activities. The system can be used to examine the collective procrastination of the class as well as individual students or demographic categories. If effective, real-time procrastination monitoring becomes another tool for objectively evaluating new strategies in a given semester also allowing for immediate adjustments benefitting current instead of just future students.