Perceived Digital Game Instructional Strategies and Self-Regulated Learning as Predictors of Biology Students' Academic Engagement in Awka South LGA

Esther Ebele Akachukwu

doi:10.61227/r2drzt77

Authors

Esther Ebele Akachukwu Department of Science Education, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria

DOI:

https://doi.org/10.61227/r2drzt77

Keywords:

Academic engagement, Biology students, Digital game strategies, Goal setting, Self regulated learning

Abstract

Traditional biology instruction in secondary schools often relies on conventional teaching methods that struggle to sustain student attention, leading to declining interest and low academic engagement with complex biological concepts. This ongoing pedagogical challenge requires investigating innovative, student-centered predictors that can enhance classroom participation and active learning. The purpose of this study was to assess perceived digital game instructional strategies as well as goal setting self-regulated learning as predictors of academic engagement among biology students, Awka South Local Government Area. For this investigation, a correlational research design was chosen. The population of the study was all the senior secondary school biology students in the educational zone with a sample of one hundred and ten students obtained by convenient sampling technique. The three rating instruments adapted on a four point scale were used for data collection. High reliability indices were obtained with the Cronbach alpha method for the internal consistency of the items. Analyses of the collected data involved linear and multiple hierarchical regression analysis procedures at 5% significance level. The results showed that perceived digital game instructional strategies significantly predicted the academic engagement scores of the biology students when moderated by school type, accounting for more than two-thirds of the variance. In the same way, goal setting self regulated learning was significant predictors of academic engagement in terms of genders. Finally, the joint predictive model showed that the combination of digital game strategies and SRL explained 61.8% of the total variance in academic engagement. It is concluded that a pedagogical path towards maximizing student engagement is offered when modern technological framework is combined with structured self regulation habits.

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