Framework to improve e-learner satisfaction and further strengthen e-learning implementation |
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| Affiliation: | 1. English Department, Alzahra University, Tehran, Iran;2. English Department, Iran University of Science and Technology, Tehran, Iran;3. Department of Educational Research, Kharazmi University, Tehran, Iran;1. College of Management and Economics, Tianjin University, No.92, Weijin Road, Tianjin, 300072, China;2. Department of Information Systems, National University of Singapore, 13 Computing Drive, 117417, Singapore;3. School of Economics and Management, Southeast University, No.2, Si Pai Lou Street, Nanjing, Jiangsu, 210096, China;1. University at Buffalo, United States;2. Washington State University Tricities, United States;1. University of Vienna, Faculty of Computer Science, Research Group CSLEARN ‐ Educational Technologies, Währinger Straβe 29, 1090 Vienna, Austria;2. Anima Scan Ltd., Israel;3. Tel Aviv University, Israel;4. Hadassah-Hebrew University Medical Center, Jerusalem, Israel;5. Research Centre for Natural Sciences, Institute of Cognitive Neuroscience and Psychology, Hungary;1. English Department, Alzahra University, Tehran, Iran;2. Department of Foreign Languages, Kharazmi University, Tehran, Iran;3. English Department, Iran University of Science and Technology, Tehran, Iran;1. Complex Service and Training Department, Institute of Computer Science, Masaryk University, Brno, Czech Republic;2. Department of Physics, Faculty of Applied Sciences, University of West Bohemia, Plzen, Czech Republic;3. Department of Czech Language and Literature, Faculty of Education, University of West Bohemia, Plzen, Czech Republic;4. Department of Educational Sciences, Faculty of Arts, Masaryk University, Brno, Czech Republic;1. Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency, Ulsan, Korea;2. Department of Lifelong Education, Korea National Open University, Seoul, Korea |
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| Abstract: | In this study, a framework has been designed to guide institutions to better improve learner satisfaction and further strengthen their e-learning implementation. Undergraduate participants (n = 600) completed an online survey of 132 items. This article will first report on the development and validation of an instrument that attempts to reveal factors that affect user satisfaction, and then a multiple regression analysis and a path analysis help further investigate which factors can significantly predict learner satisfaction. The factor analysis identified 14 different factors. These factors were further categorized by the researchers into 6 dimensions i.e. learner dimension, instructor’s dimension, course dimension, technology dimension, design dimension, and the environment dimension. The multiple regression analysis showed that e-learners satisfaction can mostly be predicted by learner interaction with others. Findings of this research will help institutions by providing them with psychometric properties that add pedagogical value to e-courses. |
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| Keywords: | Learner satisfaction e-Learning environments e-Learning facilitator Learner attitude toward e-courses e-Learning course flexibility |
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