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Autors principals:	Kyausu, Cynthia Shidoo, Torkula, Paul Terkura
Format:	Recurso digital
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Publicat:	Zenodo 2026
Accés en línia:	https://doi.org/10.5281/zenodo.20177916
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This study examined the effect of Artificial Intelligence-Based Instruction (AIBI) on secondary school students’ achievement in Integrated Science in Benue State, Nigeria, addressing persistent underachievement linked to conventional, teacher-centred methods. A quasi-experimental pre-test post-test design was employed with a multistage sample of 60 students drawn from a population of 2,450 across 30 public schools. Data were collected using a researcher-developed Integrated Science Achievement Test (ISAT; reliability coefficient = 0.87, KR-20) and analysed with mean, standard deviation, and Analysis of Covariance (ANCOVA). Students taught with AIBI significantly outperformed those taught via the conventional lecture method, F (1, 57) = 48.325, p < 0.05, with a large effect size (η² = 0.46), indicating that AIBI accounts for approximately 46% of the variance in achievement outcomes. A significant gender difference also emerged, F (1, 28) = 5.612, p < 0.05 (η² = 0.17), favouring female students. These findings demonstrate that AIBI is a powerful, adaptive instructional tool capable of improving science learning outcomes and reducing gender gaps in resource-constrained classroom settings. The study recommends the systematic integration of AIBI into Integrated Science teaching in Benue State secondary schools, supported by targeted teacher training and technology infrastructure investment, as a practical strategy for improving academic achievement and advancing gender equity in science education.   Keywords: Artificial Intelligence Based Instruction, Achievement, Integrated Science.

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