Modeling instructional strategies and their transformative role in enhancing engagement and equity in computer studies: a quasi-experimental study

Innovative instructional strategies are critical for fostering engagement and inclusivity in education, especially in technology-driven fields such as computer studies. Despite their potential, the broader impacts of modeling instructional approaches on student interest remain underexplored, particularly in secondary education. This study investigates the effects of a modeling instructional strategy on junior secondary school students’ interest in computer studies in Ebonyi State, Nigeria, using a quasi-experimental pre-test, post-test, non-equivalent control group design. A total of 260 Junior Secondary School 2 (JSS2) students participated, divided into treatment and control groups. The Computer Studies Interest Inventory (CSII), a validated 25-item Likert scale, measured dimensions of academic, vocational, leisure, and general interest. Over eight weeks, the treatment group experienced a modeling-based instructional approach emphasizing hands-on, collaborative learning, while the control group received conventional teaching. Statistical analysis, conducted using Python’s data analysis libraries, revealed a significant improvement in student interest within the treatment group (mean post-test score = 69.36) compared to the control group (mean = 49.46), with a large effect size (Cohen’s d = 2.49). ANCOVA results confirmed the modeling approach’s effectiveness and revealed no significant gender differences, underscoring its inclusivity. By bridging abstract concepts with practical applications, this approach promotes engagement and equitable learning outcomes. We recommend incorporating modeling strategies into curricula and professional development programs to enhance teaching quality and student interest. This study contributes valuable insights for educators and policymakers seeking to improve STEM education through evidence-based, student-centered methodologies.