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Comparative review reveals structural barriers depressing standardized exam scores in secondary students, highlighting the potential of offline-first AI frameworks for personalized remediation.
This comprehensive academic review investigates the long-standing disparity between Nigerian secondary school students' true classroom potential and their final output in external standardized examinations, such as those conducted by the West African Examinations Council (WAEC), the National Examinations Council (NECO), and the Unified Tertiary Matriculation Examination (UTME). Utilizing primary quantitative and qualitative field survey data (N=30) gathered from secondary school learners, this paper establishes that severe structural impediments including massive student-to-teacher ratios, inadequate supplementary learning resources, rigid assessment methodologies, and lack of personalized remediation artificially depress student academic outcomes. To formulate a viable solution, this review explores international benchmark models, specifically examining South Korea’s post-war educational transformation and current AI digital textbook initiative, as well as Finland’s personalized diagnostic model. Based on these global insights and localized survey findings, an offline-first, AI-integrated educational framework tailored to the infrastructural realities of Nigerian secondary schools is detailed.
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MICHAEL OLUWADAMILARE ASAOLU (2026) studied this question.
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