Document Type : Original Article


1 Ph.D condidate in Education Management, Islamic Azad University, Marand Branch,Iran

2 Assistant Professor, Department of Education Management, Islamic Azad University, Marand Branch, Iran

3 Assistant Professor, Department of Governmental management, Islamic Azad University, Khoy Branch,Iran


The purpose of this study is to provide a conceptual framework for the e-learning system of higher education institutions in the Iran, based on the views of experts related to the field of e-learning at the level of higher education institutions and prioritizing factors over each other. The present study is applied in terms of purpose; It is descriptive-exploratory in terms of how data is collected and qualitative in terms of the nature of the data. Accordingly, in order to collect qualitative data, after reviewing the literature related to the research topic, a framework was developed to ask questions of interviews with experts. Then, using purposive sampling method (snowball), the opinions of 15 experts up to the theoretical saturation stage were used. The interviews were coded using Clark and Brown six-step inductive theme analysis. Accordingly, the identified speech evidence from the interview text was labeled in the form of 53 initial codes. Then, the initial codes were drawn in the form of 12 sub-themes and then, three main themes including specialized requirements of e-education system, general requirements of e-education system, results and consequences of e-education system, classification and conceptual conceptual framework of e-education system of higher education institutions. Then, in order to validate the results of the interviews and confirm the components of the research conceptual framework, the fuzzy Delphi questionnaire and method were used and in order to prioritize the components of the research conceptual framework, the fuzzy hierarchy questionnaire and process (FAHP) were used. Based on the results of the research in the Delphi section, all 12 sub-themes or questions of the Delphi questionnaire were approved by the research experts. The results of fuzzy hierarchical analysis also showed that the technical requirements of e-learning have the highest priority among the specialized requirements, followed by the quality requirements of the education system, support requirements, requirements related to professors, requirements for educational quality and related requirements. With students, they are in the next ranks. Also, achieving effectiveness is the highest priority among the general requirements of the e-learning system, followed by satisfaction, optimal use and utilization, in the next ranks. In addition, saving time and money is the highest priority. Among the factors and then the development of learning and integration of education, are in the next ranks.


Alam, M. M.; Ahmad, N.; Naveed, Q. N.; Patel, A.; Abohashrh, M.; & Khaleel, M. A. (2021). E-learning services to achieve sustainable learning and academic performance: An empirical study. Sustainability, 13(5), 26-53.
AL-Sabawy, A. Y. (2011). "Measuring e-learning systems success".In PACIS Proceedings,Paper 15
Arbaugh, J. (2000). Virtual classroom characteristics and student satisfaction with internet-based MBA courses. Journal of management education, 24(1), 32-54.
Arbaugh, J; & Duray, R. (2002). Technological and structural characteristics, student learning and satisfaction with web-based courses: An exploratory study of two on-line MBA programs. Management learning, 33(3), 331-347.
Balaban, I.; Mu, E.; & Divjak, B. (2013). Development of an electronic Portfolio system success conceptual framework: An information systems approach. Computers & Education, 60(1), 396-411.
Batara, C. (2021). Monitoring of the Virtual Learning Process during the Covid-19 pandemic. In IOP Conference Series: Materials Science and Engineering (Vol. 1088, p. 12044). IOP Publishing.
Bates, T. (2020). Crashing into online learning: a report from five continents–and some conclusions. Online Learning and Distance Education Resources
Chen, H-R. & Tseng, H-F. (2012). Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan. Evaluation and program planning, 35(3), 398-406.
Chiu, C.; Chiu, C. & Chang, H. (2007). Examining the integrated influence of fairness and quality on learners’ satisfaction and Web‐based learning continuance intention. Information systems journal, 17(3), 271-287.
Cidral, W. A; Oliveira, T.; Di Felice, M.; & Aparicio, M. (2018). E-learning success determinants: Brazilian empirical study. Computers & Education, 122, 273-290.
DeLone, W. H; & McLean, E. R. (2003). The DeLone and McLean conceptual framework of information systems success: a ten-year update. Journal of management information systems, 19(4): 9-30
Effendy, F.; Kurniawati, O. & Priambada, G. (2021). Factor Affecting E-Learning User Acceptance: A Case Study of AULA. Journal of Physics: Conference Series, 1783, 12122.
Ejdys, J. (2021). Factors Affecting the Adoption of e-Learning at University Level. WSEAS Transactions on Business and Economics, 18, 313-323.
Eom, S.; Ashill, N. J; Arbaugh, JB; & Stapleton, J. L. (2012). The role of information technology in e-learning systems success. Human Systems Management, 31(3-4): 147-163.
Garcia-Smith, D.; & Effken, J. A. (2013). Development and initial evaluation of the clinical information systems success conceptual framework (CISSM). International Journal of Medical Informatics, 82(6), 539-552.
Ghanbari, S.; Ziaee, M. S.; Mosleh, M. and Razzaqi Shirsavar, H. (۱۳۹۸). Presenting an evaluation conceptual framework of e-learning in the electronic unit of Islamic Azad University. Educational Management Research, 41 (11), 75-100.( in Persian)
Halawi, L. A; McCarthy, R. V; & Aronson, J. E. (2008). An empirical investigation of knowledge management systems’ success. Journal of computer information systems, 48(2), 121-135.
Hasan, M.l; Maarop, N.; Samy, G N.; Baharum, H; Abidin, WZ; & Hassan, N H. (2017). Developing a success conceptual framework of Research Information Management System for research affiliated institutions (pp. 1-6). Presented at the 2017 international conference on research and innovation in information systems (ICRIIS), IEEE.
Hassanzadeh, A.; Kanaani, F.; & Elahi, S. (2012). A conceptual framework for measuring e-learning systems success in universities. Expert systems with Applications, 39(12), 10959-10966.
Hou, C. (2012). Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: An empirical study of Taiwan’s electronics industry. International Journal of Information Management, 32(6), 560-573.
Hwang, H.; Chang, IC.; Chen, F. & Wu, SY. (2008). Investigation of the application of KMS for diseases classifications: A study in a Taiwanese hospital. Expert Systems with Applications, 34(1), 725-733.
Islam, A.N. (2013). Investigating e-learning system usage outcomes in the university context. Computers & Education, 69, 387-399.
Kim, K.; Trimi, S.; Park, H.; & Rhee, S. (2012). The impact of CMS quality on the outcomes of e‐learning systems in higher education: an empirical study. Decision Sciences Journal of Innovative Education, 10(4), 575-587.
Klobas, J. E; & McGill, T. J. (2010). The role of involvement in learning management system success. Journal of Computing in Higher Education, 22(2), 114-134.
Kuliya, M.; & Usman, S. (2021). Perceptions of E-learning among undergraduates and academic staff of higher educational institutions in north-eastern Nigeria. Education and Information Technologies, 26(2), 1787-1811.
Leclercq, A. (2007). The perceptual evaluation of information systems using the construct of user satisfaction: case study of a large French group. ACM SIGMIS Database: The Database for Advances in Information Systems, 38(2), 27-60.
Lee, B.; Yoon, J; & Lee, I. (2009). Learners’ acceptance of e-learning in South Korea: Theories and results. Computers & education, 53(4), 1320-1329.
Lin, H. (2007). Measuring online learning systems success: Applying the updated DeLone and McLean conceptual framework. Cyberpsychology & behavior, 10(6), 817-820.
Lwoga, E. (2014). Critical success factors for adoption of web-based learning management systems in Tanzania. International Journal of Education and Development using ICT, 10(1):98-120.
Marjanovic, U.; Delić, M.; & Lalic, B. (2016). Developing a conceptual framework to assess the success of e-learning systems: evidence from a manufacturing company in transitional economy. Information Systems and e-Business Management, 14(2), 253-272.
Mohammadi, H. (2015a). Investigating users’ perspectives on e-learning: An integration of TAM and IS success conceptual framework. Computers in Human Behavior, 45, 359-374.
Mohammadi, H. (2015b). Investigating users’ perspectives on e-learning: An integration of TAM and IS success conceptual framework. Computers in human behavior, 45:pp 359-374(Inpersian).
Mtebe, J. S.; & Raphael, C. (2018a). Key factors in learners’ satisfaction with the e-learning system at the University of Dar es Salaam, Tanzania. Australasian Journal of Educational Technology, 34(4):246-311
Mtebe, J. S; & Raphael, C. (2018b). Key factors in learners’ satisfaction with the e-learning system at the University of Dar es Salaam, Tanzania. Australasian Journal of Educational Technology, 34(4):96-102
Muhammad, A. H.and (2020a). A hierarchical conceptual framework to evaluate the quality of web-based e-learning systems. Sustainability, 12(10), 4071. .(in Persian)
Naveed, Q.N. and (2020). Evaluating critical success factors in implementing E-learning system using multi-criteria decision-making. Plos one, 15(5), e0231465.(in Persian)
Navimipour, N. & Zareie, B. (2015). A conceptual framework for assessing the impact of e-learning systems on employees’ satisfaction. Computers in Human Behavior, 53, 475-485.
Niazi, D; Barakat, G.H. and Bahmaei, L. (1400). Factors affecting the quality of e-learning in Farhangian University of Khuzestan Province based on the field theory approach. Ahwaz Jundishapur Education Development Quarterly, 12 (1), 236-247.(In persian)
Ong, C.; Lai, J.; & Wang, Y. (2004). Factors affecting engineers’ acceptance of asynchronous e-learning systems in high-tech companies. Information & management, 41(6), 795-804.
Ouajdouni, A.; Chafik, K.; & Boubker, O. (2021). Measuring e-learning systems success: Data from students of higher education institutions in Morocco. Data in Brief, 35, 106807.
Ozkan, S.; & Koseler, R. (2009a). Multi-dimensional students’ evaluation of e-learning systems in the higher education context: An empirical investigation. Computers & Education, 53(4), 1285-1296.
Palacios, L. ; & Evans, C. (2014). The effect of interactivity in e-Learning systems.england: Cambridge Scholars Publishing.
Park, S. (2009). An analysis of the technology acceptance conceptual framework in understanding university students’ behavioral intention to use e-learning. Journal of Educational Technology & Society, 12(3), 150-162
Park, S.; Zo, H.; C., Andrew P; & Lim, G G. (2011). Examining success factors in the adoption of digital object identifier systems. Electronic commerce research and applications, 10(6), 626-636.
Petter, S.; DeLone, W.; & McLean, E. (2008). Measuring information systems success: conceptual frameworks, dimensions, measures, and interrelationships. European journal of information systems, 17(3), 236-263.
Pituch, K. A; & Lee, Y. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222-244.
Po-An Hsieh, J.J; & Wang, W. (2007). Explaining employees’ extended use of complex information systems.European Journal of Information systems,16(3):216-227;
Priatna, T.; Maylawati, D.; Sugilar, H.; & Ramdhani, M. (2020). Key success factors of e-learning implementation in higher education. International Journal of Emerging Technologies in Learning (iJET), 15(17), 101-114.
Rai, A.; Lang, S.S; & Welker, R. B. (2002). Assessing the validity of IS success conceptual frameworks: An empirical test and theoretical analysis. Information systems research, 13(1), 50-69.
Sandjojo, N. & Wahyuningrum, T. (2015). Measuring e-learning systems success: Implementing D & M is success conceptual framework (pp. 1-6). Presented at the 2015 4th International Conference on Interactive Digital Media (ICIDM), IEEE
Sarmast, N and Golbazi ,S. (۱۳۹۹). Explaining the conceptual framework of factors affecting the effectiveness of e-learning in master's courses of Urmia University of Technology (Master's thesis). Faculty of Payame Noor University of West Azerbaijan Province, Payame Noor Center, Urmia.(In Persian).
Šumak, B.; Heričko, M.; & Pušnik, M. (2011). A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types. Computers in human behavior, 27(6), 2067-2077.
Sun, P.; Tsai, R. J; Finger, G.; Chen, Y. & Yeh, D. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & education, 50(4), 1183-1202.
Van Raaij, E. M; & Schepers, JL. (2008). The acceptance and use of a virtual learning environment in China. Computers & education, 50(3), 838-852.
Wu, J. & Wang, Y. (2006). Measuring KMS success: A respecification of the DeLone and McLean’s conceptual framework. Information & management, 43(6), 728-739.
Xing, W.; Kim, S. & Goggins, S. (2015). Conceptual frameworking performance in asynchronous CSCL: an exploration of social ability, collective efficacy and social interaction. International Society of the Learning Sciences, Inc.
Yawson, D. E.; & Yamoah, F. A. (2020). Understanding satisfaction essentials of E-learning in higher education: A multi-generational cohort perspective. Heliyon, 6(11), 55-79.
Zhu, K.; & Kraemer, K. L. (2005). Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry. Information systems research, 16(1), 61-84.