The Desirability of Quality Components of E-learning Payam Noor University; Student’s Perspective of ISFAHAN LMS

The conditions of the corona virus forced online education with LMS (learning management system). The main purpose of this research is to investigate the desirability of the quality of electronic education of Payam Noor University from the students' point of view of ISFAHAN LMS. The current research is a survey. The research tool was the USELEARN questionnaire and the checklist of the National Learning Association website. The statistical population includes all students who were studying at the Bachelor's degree and Master's degree (LMS) in the 2023 at Payam Noor University through electronic education. The simple random sampling method was used. The sample size was 384 students.Benson et al.'s and Salmon's models have been used to evaluate the quality indicators and components of Payam Noor University's electronic education. The average values of the ratings showed that the indices of "Professor", Information Technology" and "University Support" had the highest average and the most importance, and the index of "Contextual Factors" had the least importance. Based on the ratio test, the factors "teacher ", "electronic interaction” and “Access to facilities” are desirable factors.”University support and support" has been evaluated as a low desirability. There is a significant difference between the evaluations of the desirability of the quality of e-learning indicators and gender.Multivariate regression analysis showed that among the independent variables entered into the equation, the variables of the “Electronic lesson score”, “The teacher's interest and friendly behavior toward all students”, “Inviting students to use electronic education”, “Evaluation of face-to-face training” and” Ease of use of electronic education system” have the greatest impact on evaluating the desirability of electronic education that could explain 73% of the variance of the changes related to the dependent variable. The variables have been able to explain 73% of the variance of changes related to the dependent variable.