Developing an E-learning Platform to Enhance Agricultural Science Education Engagement

Thesis Abstract

The persistent decline in student engagement and practical understanding in agricultural science education necessitates innovative approaches to enhance learning outcomes through technology integration. This study aims to develop an interactive e-learning platform tailored specifically for agricultural science students and to evaluate its effectiveness in increasing engagement, knowledge acquisition, and practical skills development. The primary objectives include designing a user-centered digital platform featuring multimedia resources, virtual laboratories, and collaborative tools; assessing its usability, engagement levels, and learning outcomes among students; and identifying factors influencing adoption and sustained use of the platform within agricultural educational settings. Employing a mixed-methods research design, the study combines quantitative surveys and experimental validation with qualitative interviews to provide a comprehensive evaluation. The quantitative component involves a quasi-experimental design with a sample of 300 undergraduate agricultural science students randomly assigned to either the intervention group, which uses the e-learning platform, or a control group relying on traditional instructional methods. Data collection instruments include validated questionnaires measuring engagement, self-efficacy, and perceived usefulness, alongside pre- and post-test assessments of academic knowledge and practical skills. The qualitative component incorporates semi-structured interviews with 20 students and 10 instructors to explore usability issues, motivational factors, and contextual challenges. Descriptive statistics, paired t-tests, regression analysis, and thematic analysis of interview data will be employed to analyze quantitative and qualitative findings respectively. It is anticipated that the e-learning platform will significantly improve student engagement, motivation, and comprehension of complex agricultural concepts, as evidenced through higher scores in post-intervention assessments compared to the control group. Regression analysis is expected to reveal positive correlations between platform usability factors and engagement metrics, providing insights into critical features that influence adoption. The qualitative analysis aims to identify barriers to engagement, technical challenges, and user perceptions, enriching understanding of contextual factors affecting implementation. The expected contribution of this study lies in filling existing gaps by providing empirical evidence on the efficacy of tailored digital platforms in agricultural education, guided by the Cognitive Load Theory and the Technology Acceptance Model, which underpin the design and adoption processes. Findings will inform policymakers, educators, and developers on best practices for integrating ICT solutions to foster active learning and practical skill development among agricultural students. The study concludes that well-designed e-learning environments can significantly enhance agricultural science education by promoting active participation, contextual learning, and resource accessibility, especially in resource-constrained settings. Based on these results, recommendations include scaling up platform deployment, continuous platform enhancement based on user feedback, and integrating such tools into curriculum frameworks to support lifelong learning and professional development in agriculture. The study also advocates further research on long-term impacts, cross-disciplinary adaptations, and the role of artificial intelligence in personalizing agricultural education experiences. Ultimately, this research contributes a robust model for leveraging digital innovation to transform agricultural education into a more engaging, accessible, and practical discipline aligned with 21st-century skills development.