The Relationship Between Guided Discovery Method (Gdm) And Knowledge Retention Among Electrical Installation Students in Benue State

Abstract

This study examined the relationships between Guided Discovery Method (GDM) components and knowledge retention among Electrical Installation students in Benue State. The research objectives were to explore the associations between teacher guidance and scaffolding, problem-solving activities, and collaborative learning with students’ knowledge retention. A correlational survey design was employed with 323 valid responses from Electrical Installation students across technical schools in Makurdi Metropolis. Data were collected using a structured questionnaire adapted from validated scales, with Cronbach’s alpha coefficients ranging from 0.91 to 0.94, indicating high internal consistency. Data analysis involved descriptive statistics, Pearson correlation, and multiple regression analyses. The results revealed significant positive correlations between all three GDM components and knowledge retention: teacher guidance and scaffolding (r = .691, p < .01), problem-solving activities (r = .688, p < .01), and collaborative learning (r = .678, p < .01). Multiple regression analysis produced an R value of 0.701 and an adjusted R² of 0.485, indicating that these variables jointly accounted for 48.5% of the variance in students' knowledge retention scores. However, the high inter-correlations among predictors (e.g., r = .989 between teacher guidance and problem-solving) indicate multicollinearity, suggesting that the GDM components likely measure closely related aspects of the same instructional construct. Therefore, the results should be interpreted as the combined influence of GDM rather than distinct effects of each component. The study concludes that GDM components show strong positive relationships with knowledge retention measures. It recommends that technical education teachers adopt GDM as an integrated pedagogical approach. Future research should employ longitudinal or experimental designs with pre-tests and delayed post-tests to establish causation and measure actual long-term knowledge retention.