Agricultural education
Seyed Mohammad Javad Sobhani; Omid Jamshidi; Zahra Fozouni Ardekani
Abstract
In recent years, the COVID-19 pandemic has heightened the significance of virtual education in transforming higher education patterns. Consequently, the higher education system in agriculture, which relies on hands-on activities, requires a specific understanding of its audience’s behavior to enhance ...
Read More
In recent years, the COVID-19 pandemic has heightened the significance of virtual education in transforming higher education patterns. Consequently, the higher education system in agriculture, which relies on hands-on activities, requires a specific understanding of its audience’s behavior to enhance learning outcomes. The current research, adopting a quantitative perspective and a causal approach, has analyzed students' behavior towards Learning Management Systems in higher agricultural education during the academic year 2023. The research instrument was a questionnaire based on the amalgamation of the Theory of Planned Behavior and the Technology Acceptance Model, the face validity of which was confirmed by university and industry experts, and its convergent and divergent validity confirmed with an AVE of 0.659to0.881. Additionally, the reliability of all research components was estimated to be satisfactory with an ordinal theta coefficient of 0.715to0.921 and a CR of 0.852 to 0.950. Data required from 385 students currently enrolled in public agricultural universities (N=9819) were collected using stratified random sampling and analyzed using Structural Equation Modeling. Research findings indicated that perceived ease of use has a positive and significant effect on perceived usefulness but does not affect the behavioral intention to use the LMS education system. Furthermore, other model-derived components, such as perceived usefulness, perceived control, and subjective norms, have a significant positive effect on the mediator behavioral intention, ultimately explaining 71 percent of the actual behavior dependent variable. Based on the results, recommendations were put forth to strengthen the effective components and improve accessibility to the Learning Management System.
