Acceptance of an E-learning Module on Climate-smart Horticulture: A Structural Equation Model

Abstract

Background: E-learning is now being used in a variety of industries, including agriculture. The use of information and communication technologies (ICTs) is seen as essential for overcoming the barriers that a developing country faces in all areas and closing the digital divide. Farmers must be prepared with the most recent breakthroughs in ICTs in order to take advantage of new opportunities in the global market. Methods: By designing an e-learning module and providing farmers with a self-learning framework, the study focuses on the use of ICT instruments in climate-smart horticulture. The psychological factors in this study were investigated using the E-Learning Acceptance Model (ELAM), which was derived from the Technology Acceptance Model (TAM). A quantitative survey of 200 farmers were conducted. Structural equation modelling (SEM) was used to test the research hypotheses. Result: ELAM has enough predictive ability to explain farmers’ behavioural intention to utilise an e-learning module in a real world. In total, the result supports five ELAM hypotheses. The SEM findings indicate that ELAM is a valid model. In ELAM, partial mediation was also observed.