Journal of Health And Care
Volume 27, Issue 1 (spring 2025)
JHC 2025, 27(1): 31-41 |
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Ethics code: R.IAU.ARDABIL.REC.1401.172
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Nezhadsafar R, Rastgoo A, pourasghar N, Namvar Y. Evaluating the Quality of E-Learning Systems Using the
Hadullo Model. JHC 2025; 27 (1) :31-41
URL: http://hcjournal.arums.ac.ir/article-1-1610-en.html
URL: http://hcjournal.arums.ac.ir/article-1-1610-en.html
Department of Educational Sciences, Ardabil Branch, Islamic Azad University, Ardabil, Iran
Abstract: (29 Views)
Background: With the increasing acceleration of digital transformations in the present era and the facilitation of access to new technologies, e-learning is being widely developed, as a leading educational approach. In this regard, ensuring the quality of this new educational system requires the use of systematic and reliable evaluation frameworks. The aim of this research was evaluating the quality of the e-learning systems, using the Hadullo evaluating model.
Methods: This quantitative descriptive-correlational study was conducted based on structural equation modeling. The study population included all students of Islamic Azad and Payame Noor universities in Ardabil in the academic year 2023-2024, (11,488 people). A total of 372 were selected using stratified random sampling. The data collection tool was the Hadullo e-learning quality assessment questionnaire (2018). Data analysis was performed using t-tests and Pearson correlation coefficient using SPSS-27, and structural equation modeling analysis using Amos-26.
Results: The results showed that the goodness of fit index was 0.98, the adjusted goodness of fit index was 0.96, and the normalized fit index was 0.92, which indicates that the final model had a very good fit. Furthermore, the results of examining the relationship between variables showed that the learner support dimension, with a path coefficient of 0.81 and T = 145.31, had a greater impact on the quality of e-learning than the other 4 dimensions. All components had a significant impact on the quality of e-learning.
Conclusion: Based on the findings of the research, the quality of e-learning in Islamic Azad and Payame Noor Universities of Ardabil has been evaluated at a desirable level in five areas based on the Hadullo model. Therefore, evaluating the quality of the e-learning system based on this model can determine the level of performance in universities and accurately identify strengths and weaknesses in this area, so their quality can be modified and improved
Methods: This quantitative descriptive-correlational study was conducted based on structural equation modeling. The study population included all students of Islamic Azad and Payame Noor universities in Ardabil in the academic year 2023-2024, (11,488 people). A total of 372 were selected using stratified random sampling. The data collection tool was the Hadullo e-learning quality assessment questionnaire (2018). Data analysis was performed using t-tests and Pearson correlation coefficient using SPSS-27, and structural equation modeling analysis using Amos-26.
Results: The results showed that the goodness of fit index was 0.98, the adjusted goodness of fit index was 0.96, and the normalized fit index was 0.92, which indicates that the final model had a very good fit. Furthermore, the results of examining the relationship between variables showed that the learner support dimension, with a path coefficient of 0.81 and T = 145.31, had a greater impact on the quality of e-learning than the other 4 dimensions. All components had a significant impact on the quality of e-learning.
Conclusion: Based on the findings of the research, the quality of e-learning in Islamic Azad and Payame Noor Universities of Ardabil has been evaluated at a desirable level in five areas based on the Hadullo model. Therefore, evaluating the quality of the e-learning system based on this model can determine the level of performance in universities and accurately identify strengths and weaknesses in this area, so their quality can be modified and improved
Type of Study: correlation design |
Subject:
Nursing education
Received: 2024/12/20 | Accepted: 2025/05/16 | Published: 2025/03/30
Received: 2024/12/20 | Accepted: 2025/05/16 | Published: 2025/03/30
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