Real-time monitoring of student procrastination in a PSI first-year programming course

Abstract

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 self- paced 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. © 2012 American Society for Engineering Education.