New Perspectives in Science Education

Edition 13

Accepted Abstracts

A Data-Driven Gamification Approach to Monitor and Predict the Students’ Academic Performance

Sherif Abdelhamid, Assistant Professor, Virginia Military Institute (United States)

Kolby Quigg, Virginia Military Institute (United States)

Mona Aly, Independent Researcher (United States)

Abstract

Learning environments can be more stimulating by incorporating game design elements into the curriculum. Several studies have shown that gamification improves student motivation, learning, and academic performance [1]. According to Karl M. Kapp [2], gamification is "the ideal process for creating engaging learning environments." Gamification can be implemented in schools at different grade levels, from kindergarten to 12 years of basic education [3]. Additionally, the use of gamification in education has been demonstrated in several fields, including computer science, mathematics, astronomy, physics, medicine, and law [4, 5]. Current research works have extensively explored how gamification can improve students' engagement and motivation, but few studies have examined how it can track and predict students' academic performance. This study investigates how data collected from gamification activities can help instructors monitor and predict students’ performance in the classroom. We used Quizizz, a web-based tool that delivers quiz questions in a game-like manner. By answering questions interactively, students earn points and rewards. Students can answer at the instructor's or their own pace and earn points based on their answering speed. Additionally, instructors can use team modes to place students in teams for scoring. For this study, we identified two experimental groups representing sophomore students in two computer science courses: Database Management Systems and Data Structures & Applications. We explored the causal relationship between the final course grade of students and their scores, interactions, and timings during the weekly gamified activities. The study employed a data-driven exploratory and correlational methodology that involves regression analysis to forecast and predict patterns in the course grades. 

Keywords:

Gamification, Game-based Learning, Academic Performance, Machine Learning

References:

  1. Liu, T., & Lipowski, M. (2021). Sports gamification: Evaluation of its impact on learning motivation and performance in higher education. International Journal of Environmental Research and Public Health, 18(3), 1267.
  2. Kapp, K. M. (2012). The gamification of learning and instruction: game-based methods and strategies for training and education. John Wiley & Sons.
  3. Varannai, I., Sasvári, P. L., & Urbanovics, A. (2017). The use of gamification in higher education: an empirical study. International Journal of Advanced Computer Science and Applications, 8(10), 1-6.
  4. Kasahara, R., Sakamoto, K., Washizaki, H., & Fukazawa, Y. (2019, July). Applying gamification to motivate students to write high-quality code in programming assignments. 2019 ACM Conference on Innovation and Technology in Computer Science Education (pp. 92-98).
  5. Nevin, C. R., Westfall, A. O., Rodriguez, J. M., Dempsey, D. M., Cherrington, A., Roy, B. & Willig, J. H. (2014). Gamification as a tool for enhancing graduate medical education. Postgraduate medical journal, 90(1070), 685-693.

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