Investigating Students’ Performance and Motivation in Computer Programming through a Gamified Recommender System

Abstract

Abstract In this study, a personalized gamified recommender system was developed to help secondary-school students in Saudi Arabia learn computer programming. This recommender system supports those students by providing personalized recommendations to address their weaknesses and increase their motivation toward computer programming. A total of 60 female secondary-school students participated in this empirical study and were divided in to an intervention and comparison group. Due to the distance learning directives imposed by the COVID-19 pandemic, the whole study was conducted online. Data were collected through a post-test to measure student performance. In addition, a learning motivation questionnaire was distributed to all the study participants to measure their motivation toward learning programming. The Instructional Materials Motivation Survey questionnaire was distributed to the experimental group to measure their level of motivation after using the recommender system. The results showed that the personalized gamified recommender system positively affected the students’ performance in the intervention group and enhanced their motivation toward learning computer programming.