Investigating Factors Affecting the Acceptance of E-Learning among Faculty Members and Students of Macro Medical Universities in Region Three Based on the Davis Model: A Cross-Sectional Study

Background: The integration of information technology into educational systems represents a dynamic educational paradigm that delineates modern education for effective engagement in the third millennium. However, prior to its implementation, efforts should be directed towards identifying the factors influencing its acceptance and utilization. Objectives: The present study aimed to investigate the factors influencing the acceptance of e-learning among professors and students of macro medical sciences universities in the third region based on the Davis model in the year 2023. Methods: This study employed a cross-sectional design. The research instrument consisted of a 25-item Davis questionnaire utilizing a 5-point Likert scale, which was distributed to the samples both in person and virtually following validation and reliability confirmation by experts and a pre-test. The study population comprised 308 professors and 400 students from macro medical sciences universities in Macro Region 3. Data analysis utilized descriptive statistics (frequency, percentage, mean, and standard deviation) and inferential statistics (correlation, analysis of variance, and related tests), using SPSS software version 19 and LISREL software for Structural Equation Modeling.Modeling. Results: Data analysis revealed that the structural model of acceptance of electronic learning technology among the students of the University of Medical Sciences in Macro Region 3 is appropriate and applicable in the academic community. The variable of ease of use on attitude towards use demonstrated a coefficient of 0.41 and a T score of 7.16, while the variable of usefulness on decision to use showed a coefficient of 0.46 and a T-score of 6.31. Additionally, usefulness on attitude towards use displayed a coefficient of 0.49 and a T score of 5.92. Moreover, the variable of attitude towards use on decision to use had a coefficient of 0.47 and a T score of 5.65. Finally, the variable of decision to use on use exhibited a coefficient of 0.49 and a T score of 6.42. Conclusions: Conducting preliminary studies to comprehend the current landscape and elucidate the influencing factors in this regard can facilitate the implementation of related programs and pave the way for their efficacy. Moreover, it is advisable for officials and policymakers to employ technology acceptance theories to deploy new systems and technologies, thereby understanding the factors contributing to their acceptance and application, mitigating the risk of failure and resource wastage, and enhancing the quality of education and service delivery.