What question did this study set out to answer?

This research aims to evaluate the effectiveness of webinars in agricultural education, focusing on how various factors influence outcomes.

March 31, 2026Open Access

Evaluating webinar effectiveness in post COVID digital learning: a multi-stakeholder assessment using Fuzzy-AHP and clustering analysis

Key Points

This research aims to evaluate the effectiveness of webinars in agricultural education, focusing on how various factors influence outcomes.
Data collected through an online survey of 415 participants in India.
Webinar effectiveness assessed using the first two levels of Kirkpatrick's evaluation model.
Webinar Effectiveness Index developed using Fuzzy-AHP based on factors like usefulness and satisfaction.
Fuzzy C-Means clustering used to identify learner patterns and correlate satisfaction with learning outcomes.
Costs and time efficiency of webinars compared to in-person seminars.
Eight distinct learner types identified, each with varying engagement and effectiveness levels.
Clusters showed strong correlations between satisfaction, knowledge gain, and overall learning impact.
Webinars found to be more economical and time-efficient than traditional seminars.

Abstract

Introduction As digital technologies continue to impact our education system, webinars have become an essential way to deliver timely, scalable training, especially in the post-COVID era. Despite widespread use, we still know relatively little about how effective webinars are especially in the field of agricultural education and extension. This study aims to fill that gap by exploring how socio-economic, personal, and learning-related factors shape participants' webinar experiences and outcomes. Methods Data was collected from 415 participants across India through a structured online survey. The impact of webinar was assessed using the first two levels of Kirkpatrick's evaluation model, focusing on participants' reactions and learning. To measure overall effectiveness, Webinar Effectiveness Index (WEI) was developed using the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) based on five key components like usefulness, lecture quality, knowledge gain, satisfaction, and learning impact. Fuzzy C-Means clustering was applied to identify patterns among learners, supported by correlation analysis to understand how satisfaction and learning outcomes relate. Costs and time requirements of webinars were also taken into account. Results Our analysis revealed eight distinct types of learners, each showing different levels of engagement and effectiveness. Some clusters performed consistently well, reporting strong knowledge gains and high satisfaction, while others displayed more varied and less favorable outcomes. We also found clear, positive Correlation between participants' satisfaction, their knowledge gain, and the overall impact of the learning experience. Additionally, webinars proved to be more economical and time-efficient than in-person seminars. Discussion/Conclusion The study offers a practical, multi-dimensional approach to evaluating webinar effectiveness using soft computing tools. The findings highlight how learner diversity shapes digital learning outcomes and demonstrate the strong connections among satisfaction, learning, and perceived impact. Overall, the study provides useful guidance for designing webinars that are more engaging, inclusive, and cost-effective especially for large-scale capacity-building programs in agriculture and other fields where accessibility and scalability matter most.

Ask AI

Helpful

Bookmark

View Full Paper