Science process skills, academic engagement, learning management system utilization, and science academic achievement: A regression analysis

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ABSTRACT

This study sought to explore how academic engagement, science process skills, and the use of learning management systems (LMS) predict science academic achievement among junior high students. A quantitative, correlational design was employed to examine the relationships among three factors (academic engagement, science process skills, and LMS utilization) and the outcome of science academic achievement among Grade 9 students from a private Catholic school in Bacolod City. Data were gathered through random sampling via online surveys, including the Student Engagement in School Four-Dimensional Scale (SES-4DS), a researcher-developed Science Process Skills Test (SPST), and an LMS utilization survey based on Canvas platform use, with first-quarter science grades used to represent academic achievement. Data were analyzed using means, standard deviations, Pearson correlation, and multiple linear regression to evaluate relationships among these factors. The results showed that while the three factors did not have a strong impact on academic achievement, there was a positive link between them and science academic achievement. Specifically, skills such as observing, classifying, and measuring, when combined with LMS utilization and academic engagement, showed positive relationships. However, other science process skills (predicting, inferring, communicating) had negative relationships with science academic achievement. Future studies should include additional variables, such as socioeconomic status, and explore ways to enhance LMS use and address problems. Findings highlight the need for an integrated pedagogy that links engagement, digital tools, and scientific inquiry to improve performance. Longitudinal studies may also be useful for identifying how these factors influence academic performance in science over time.

Keywords: science process skills, academic engagement, learning management system utilization, science academic achievement, regression analysis