Adaptive Visual Pedagogy and Agro-Nutrition Learning Outcomes in Rural Agricultural Extension: A Quasi-Experimental Study in Southeast Nigeria
Onyebuchi-Igbokwe Grace Chizoma, Ogu Jovita Charles, Egornu Chizoba Anderson, Okwulehie Felicia Chinyere, Uzoegbu, Fiat Mary
Journal of Education, Society and Behavioural Science · pp. 83–99 · Published 12 May 2026
10.9734/jesbs/2026/v39i31488Abstract
Despite advances in digital agriculture and nutrition education, limited empirical evidence exists on the effectiveness of visually mediated digital learning tools in improving agro-nutrition knowledge and dietary behavior among rural farming households in Nigeria. This study investigated the effectiveness of adaptive visual pedagogy in enhancing learning outcomes within rural agricultural extension systems in Southeast Nigeria. Grounded in constructivist learning theory and multimedia learning principles, the study adopted a quasi-experimental design involving 372 valid respondents drawn from Ebonyi and Imo States. Participants were assigned to experimental and control groups, with the experimental group exposed to digitally mediated, visually enriched agro-nutrition learning materials, while the control group received conventional extension messages. Data were collected using structured questionnaires and analyzed using descriptive and inferential statistics, including t-tests, chi-square analysis, ANOVA, and multiple regression. The findings indicate that adaptive visual pedagogy significantly improved agro-nutrition knowledge and learning outcomes, with the experimental group outperforming the control group. The results further reveal a strong effect size, confirming the practical significance of the intervention. In addition, exposure to digital visual learning was significantly associated with improved dietary diversity, while digital exposure and participation intensity emerged as key predictors of knowledge gains. The study concludes that adaptive visual pedagogy is an effective tool for improving agro-nutrition knowledge and bridging the knowledge–behavior gap in rural extension systems. It recommends the integration of visually driven digital learning approaches into agricultural extension policies in developing contexts.
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