Enhancing mathematics retention through seeing-AI: A quasi-experimental study among visually impaired junior secondary students in Ogun State, Nigeria
Akorede Asanre, Johnson Idowu Oguntola, Mamochana Anacletta Ramatea, Abisola Olusola Lawani
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Published: Mar 30, 2026
DOI: 10.20897/ejsteme/18268
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The persistent challenge of poor retention in Mathematics underscores the need for effective, 21st-century instructional strategies that can sustain students’ long-term recall, particularly those students with visual impairment. The study examines the impact of gender and the Seeing AI method on the retention of mathematics among students with visual impairments in junior secondary schools in Ogun State, Nigeria. A quantitative approach to quasi-experimental design was employed. Purposive sampling was used to select two schools, 10 students each assigned to the experimental group and the control group. The Mathematics Retention Test (MRT), with a reliability coefficient of 0.82, was administered over three weeks alongside pre-test and post-test measures. Data were analyzed using Analysis of Covariance (ANCOVA). Findings revealed that Seeing AI had a statistically significant positive effect on students’ Mathematics retention (p < 0.05). Gender did not exert a statistically significant main effect; however, there was a significant interaction effect between strategy and gender, indicating disparities in retention patterns across male and female students. The study concludes that Seeing-AI effectively enhances Mathematics retention among students with visual impairment, irrespective of gender differences. It recommends integrating this strategy into special education practices to ensure fairness and long-term effectiveness in learning.
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