Dynamics of Adaptive Learning Algorithms and Community-Based Interventions

Students’ Preparedness in CBT in Southwest Nigeria

Abstract

This study investigates the impact of Adaptive Learning Algorithms and Community-Based Interventions on students' preparedness and anxiety toward the proposed Computer-Based Testing (CBT) for the West African Senior School Certificate Examination (WASSCE) in Southwest Nigeria. The research was based on a mixed-research design comprising a quasi-experimental design and Focus Group Discussions (FGDs). A multistage sampling method selected 200 students into four groups: Control, Adaptive Learning, Community-Based, and Combined Interventions. Quantitative data were analyzed with mixed-model ANOVA, while FGDs underwent thematic analysis using NVivo 14. The results indicated significant post-test improvements across all groups, with Community-Based and Combined Interventions showing the most significant impact. Thematic analysis identified five key themes: preparedness, confidence in CBT, peer support, reduced anxiety, and enhanced understanding of CBT requirements. Notably, participants in the Community-Based Group experienced collaborative peer interactions, freedom of expression, and a supportive community, which alleviated anxiety and boosted confidence in CBT. The study recommends that the West African Examination Council (WAEC) adopt preparatory measures across government levels and consider utilizing a TetFund-sponsored web-based CBT simulator to enhance students' readiness and reduce digital phobia. These steps could ensure a smoother transition to CBT for WASSCE in Nigeria.