Persistence of Time Management Behavior of Students and Its Relationship with Performance in Software Projects

J Häkkinen, P Ihantola, M Luukkainen… - Proceedings of the 17th …, 2021 - dl.acm.org
Proceedings of the 17th ACM Conference on International Computing Education …, 2021dl.acm.org
Teachers often preach for their students to start working on assignments early. There is even
a fair amount of scientific evidence that starting early is beneficial for learning. In this work,
we investigate students' time management behavior in a second-year project-based
software engineering course. In the course, students work on a software project in small
groups of four to six students. We study time management from multiple angles. Firstly, we
conduct an exploratory factor analysis and study how different time management related …
Teachers often preach for their students to start working on assignments early. There is even a fair amount of scientific evidence that starting early is beneficial for learning. In this work, we investigate students’ time management behavior in a second-year project-based software engineering course. In the course, students work on a software project in small groups of four to six students. We study time management from multiple angles. Firstly, we conduct an exploratory factor analysis and study how different time management related behavioral metrics are related to one another, for example, whether individual students’ time management practices in the second-year group project-based course are similar to their earlier time management practices in first-year courses where students work on assignments individually. Understanding how students’ previous time management behavior is manifested in later project-based courses would be beneficial when designing project-based education. Secondly, we study whether students’ time management practices affect the peer-review scores they get from their group members. Lastly, we explore how time management affects course performance. Our findings suggest that time management behavior, even from courses taken in the past, can be used to predict how students perform in future courses.
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