Bayesian Regression Analysis of Junior High School Students' Mathematics Achievement: The Role of Study Duration, Gender, and Task Completion Time - Maria Magdalena; Irvan Irvan (JMEA : Journal of Mathematics Education and Application, 2025)
This study investigates the influence of daily study duration, task completion time, and gender on junior high school students' mathematics achievement using a Bayesian regression approach. The research was conducted at Sutomo Junior High School in Medan with a purposive sample of 19 seventh-grade students. Data were collected through a structured questionnaire and a mathematics achievement test, and analyzed using JASP software. Descriptive statistics were used to summarize student behavior, while Bayesian linear regression assessed the impact of the predictor variables. The results revealed that neither study duration nor task completion time significantly predicted mathematics achievement. Both variables showed a weak negative association with academic performance, suggesting that longer study or test-taking times do not necessarily yield better outcomes. The Bayes Factors indicated anecdotal or weak evidence in favor of the models. These findings highlight the limited predictive power of time-based behavioral indicators and emphasize the importance of study quality, learning strategies, and cognitive efficiency. The study contributes methodologically by demonstrating the utility of Bayesian analysis in small-sample educational research and offers insights for developing more comprehensive models of academic success