Factors Influencing the Design of Electronic learning system in Agricultural Extension

Abstract

Problem statement: Nowadays appropriate training and education are important. Still some organizations make the mistake of not training their employees adequately in the utilization of ICT or in the use of internet information systems, often due to the cost of providing training and the loss in productivity when employees are absent. But many organizations have adopted e-learning as a solution for their corporate training. The Ministry of Agriculture (MoA) also have considered the necessity of e-learning in agricultural extension for training extension agents as human resources that are working in extension centers throughout the country and have direct interaction with farmers, because they understand that traditional education is no longer effective. As a result, understanding factors influencing e-learning system in Iran’s agricultural extension centers is crucial for creating the new opportunities for extension agent to update their information. The purpose of this study was to determine the factors affecting to design an e-learning system. Approach: The research in terms of nature is a kind of quantitative research and in terms of goal is applied research, in terms of controlling the variables is descriptive and correlation kind, which has been carried out in a survey way. Statistical population of the study consisted of 6539 extension expert in extension centers in Iran. Based on the classification of the Ministry of Agriculture which has divided these centers into six regions, sample taking has been conducted using stratified proportionate random sampling technique. Sample size for the students is 400 people using Cochran formula. Considering the entire size of the sample, 379 questionnaires have been returned. Results: With using factor analysis the variables were classified into seven factors, which they are included: financial, policy, support, personal, educational, technical and organizational factors. The confirmatory factor analysis determined that the relationship between observed variables and latent variables in the model. Conclusion: Extension agents will continue to play a crucial role in agricultural extension, therefore to accomplish this role in the best manner there is a need of applying new and effective methods to train extension experts in this field. On the other hand, for access to this goal, finding factors influencing the design of electronic education in agricultural extension is necessary. In this research we found some of factors that should be considered before implementation of any e-learning programs in any extension systems.