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Modeling Instructional Strategies and Their Transformative Role in Enhancing Engagement and Equity in Computer Studies: A Quasi-Experimental Study

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Title: Modeling Instructional Strategies and Their Transformative Role in Enhancing Engagement and Equity in Computer Studies: A Quasi-Experimental Study
Language: English
Authors: Chukwudum Collins Umoke, Musa Adekunle Ayanwale (ORCID 0000-0001-7640-9898), Sunday Odo Nwangbo (ORCID 0000-0002-1752-835X), Ngele Cletus Ezeoke, Sunday Okechukwu Abonyi, Stella Oluwakemi Olatunbosun (ORCID 0000-0002-3103-9544)
Source: Discover Education. 2025 4.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 23
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Junior High Schools
Middle Schools
Secondary Education
Descriptors: Educational Strategies, Teaching Methods, Models, Junior High School Students, Student Interests, Computer Science Education, Interest Inventories, Experiential Learning, Cooperative Learning, Conventional Instruction, Instructional Effectiveness, Gender Differences, Inclusion, Learner Engagement, Equal Education, STEM Education, Evidence Based Practice, Student Centered Learning, Outcomes of Education, Foreign Countries
Geographic Terms: Nigeria
DOI: 10.1007/s44217-025-00648-7
ISSN: 2731-5525
Abstract: 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.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1476100
Database: ERIC
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  Data: Modeling Instructional Strategies and Their Transformative Role in Enhancing Engagement and Equity in Computer Studies: A Quasi-Experimental Study
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  Data: <searchLink fieldCode="AR" term="%22Chukwudum+Collins+Umoke%22">Chukwudum Collins Umoke</searchLink><br /><searchLink fieldCode="AR" term="%22Musa+Adekunle+Ayanwale%22">Musa Adekunle Ayanwale</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-7640-9898">0000-0001-7640-9898</externalLink>)<br /><searchLink fieldCode="AR" term="%22Sunday+Odo+Nwangbo%22">Sunday Odo Nwangbo</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-1752-835X">0000-0002-1752-835X</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ngele+Cletus+Ezeoke%22">Ngele Cletus Ezeoke</searchLink><br /><searchLink fieldCode="AR" term="%22Sunday+Okechukwu+Abonyi%22">Sunday Okechukwu Abonyi</searchLink><br /><searchLink fieldCode="AR" term="%22Stella+Oluwakemi+Olatunbosun%22">Stella Oluwakemi Olatunbosun</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-3103-9544">0000-0002-3103-9544</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Discover+Education%22"><i>Discover Education</i></searchLink>. 2025 4.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: <searchLink fieldCode="DE" term="%22Nigeria%22">Nigeria</searchLink>
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  Data: 10.1007/s44217-025-00648-7
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  Data: 2731-5525
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  Data: 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.
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