Analysis of the Factors for the Successful E-Learning Services Adoption from Education Providers’ and Students’ Perspectives: A case study of Private Universities in Northern Iraq
More details
Hide details
Department of Management Information Systems, Cyprus International University, Nicosia, N. CYPRUS
Online publish date: 2017-12-23
Publish date: 2017-12-23
EURASIA J. Math., Sci Tech. Ed 2018;14(3):1097–1109
Electronic learning (e-learning) adoption has always been a challenge for developing countries which is often stunted by the facilitating conditions as well as the resistance of both the professionals and students. Two-step research methodology is applied in private Universities of Northern Iraq by utilizing a hypothesized model of technology acceptance model (TAM). First, the readiness factors were investigated through University staff by analysing 516 participants. As the second research objective, the intention of students is explored with 256 valid respondents in these Universities. Data were obtained from seven private Universities’ staff and students via a paper based quantitative survey. Respondents were selected based on the convenience sampling method, where researchers visited Universities during the semester with permission of their administration bodies. The findings reveal that the lowest value was for human resource readiness factor. Cultural acceptance, both from education providers’ and students’ perspective, is quite crucial in order to have a sustainable e-learning applications. From a technical point of view, our findings also confirm the importance of the technological readiness and the main TAM constructs of perceived ease of use (PEOU) and perceived usefulness (PU). Therefore, management of the Universities need to ensure that selected systems adequately address these issues.
Abbad, M. M., Morris, D., & De Nahlik, C. (2009). Looking under the bonnet: Factors affecting student adoption of e-learning systems in Jordan. The International Review of Research in Open and Distance Learning, 10(2), 10–35.
AbuSneineh, W., & Zairi, M. (2010). An evaluation Framework for E-learning Effectiveness in The Arab World. International Encyclopedia of Education, 521-535.
Al-Adwan, A., & Smedley, J. (2013). Exploring students’ acceptance of e-learning using Technology Acceptance Model in Jordanian universities. International Journal of Education and Development Using Information and Communication Technology, 9(2), 4-18.
Alharbi, S., & Drew, S. (2014). Using the Technology Acceptance Model in understanding academics’ behavioural intention to use learning management systems. International Journal of Advanced Computer Science and Applications, 5(1), 143-155.
Alshare, K. A., Freeze, R. D., Lane, P. L., & Wen, H. J. (2011). The impacts of system and human factors on online learning systems use and learner satisfaction. Decision Sciences Journal of Innovative Education, 9, 437–461.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modelling in practice. A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
Aydin, C. H., & Tasci, D. (2005). Measuring readiness for E-Learning: reflections from an emerging country. Educational Technology & society, 8(4), 244-257.
Baris, M. F. (2015). Future of e-learning: Perspective of European Teachers. Eurasia Journal of Mathematics, science & technology education, 11(2), 421–429.
Baroud, F., & Abouchedid, k. (2010). eLearning in Lebanon: Patterns of E-learning development in Lebanon’s Mosaic educational context. In U. Demiray (Ed.), E-learning practices: Cases on challenges facing e-learning and national development, institutional studies and practices (pp. 409–424). Eskisehir, Turkey: Anadolu University.
Borotis, S., & Poulymenakou, A. (2004). e-Learning readiness components: Key issues to consider before adopting e-Learning interventions. In J. Nall, & R. Robson (Eds.), Proceedings of world conference on e-Learning in corporate, government, healthcare, and higher education (pp. 1622-1629). Chesapeake, VA: AACE.
Chang, C., Yan, C., & Tseng, J. (2012). Perceived convenience in an extended technology acceptance model: Mobile technology and English learning for college students. Australasian Journal of Educational Technology, 28(5), 809-826.
Chen, S., Hanli, S., & Yi Li, C. (2011). Recent related research in Technology Acceptance Model: a literature review. Australian Journal of Business and Management Research, 1(9), 124-127.
Clark, R. C., & Mayer, R. E. (2016). E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. New Jersey, NJ: John Wiley & Sons.
Dagher, Z. R., & BouJaoude, S. (2011). Science education in Arab states: Bright future or status quo? Studies in Science Education, 47(1), 73–101.
Davis, D. F. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. Management Information Journal, 13(3), 319-340.
DeVellis, R. F. (2003). Scale development: Theory and applications. Newbury Park, CA: Sage.
Hair, J. F. J., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis. Upper Saddle River, NJ: Pearson Prentice Hall, Pearson Education.
Hu, P. J.-H., & Hui, W. (2012). Examining the role of learning engagement in technology-mediated learning and its effects on learning effectiveness and satisfaction. Decision Support Systems, 53(2), 782–792.
Huang, M., & Liaw, S. (2005). Exploring user’s attitudes and intentions toward the web as survey tool. Computers in Human Behavior, 21(5), 729-743.
Johnston, D., Berg, S., Pillon, K., & Williams, M. (2015). Ease of use and usefulness as measures of student experience in a multi-platform e-textbook pilot. Journal of Emerald Library Hi Tech, 33(1), 65-82.
Kaur, K., & Abas, Z. (2004). An Assessment of e-Learning Readiness at the Open University Malaysia. International Conference on Computers in Education (ICCE2004), Melbourne, Australia.
Lašáková, A., Bajzíková, L., & Dedze I. (2017). Barriers and drivers of innovation in higher education: Case study-based evidence across ten European Universities. International Journal of Educational Development, 55, 69–79.
Lee, Y.-H., Hsieh, Y.-C. & Hsu., C.-N. (2011). Adding Innovation Diffusion Theory to Technology Acceptance Model: Supporting Employees’ Intentions to use E-learning Systems. Educational Technology & Society, 14 (4), 124-137.
Marchewka, J., & Liu, C. (2007). An application of the UTAUT model for understanding student perceptions using course management software. Communications of the IIMA, 7(2), 93-104.
Nunnally, J. C. (1970). Introduction to psychological measurement. New York, NY: McGraw-Hill.
Nyoro, M., Kamau, W. J., Wanyembi, W. G., Titus, S. W., & Dinda, A. W. (2015). Review of Technology Acceptance Model usage in predicting e-commerce adoption. International Journal of Application or Innovation in Engineering and Management, 4(1), 46-49.
Oketch, H., Njihia, J., & Wausi, A. (2014). E-learning Readiness Assessment Model in Kenyas’ Higher Education Institutions: A Case Study of University of Nairobi. International Journal of Scientific Knowledge, 5(6), 29-41.
Park, S. Y. (2009). An analysis of the Technology Acceptance Model in understanding university students’ behavioural intention to use e-learning. Educational Technology and Society, 12(3), 150–162.
Robinson, J. P., Wrightsman, L. S., & Andrews, F. M. (1991). Measures of personality and social psychological attitudes. San Diego, CA: Academic Press.
Rohayani, A., & Kurniabudi, Sh. (2015). A Literature Review: Readiness Factors to Measuring e-Learning Readiness in Higher Education. Procedia Computer Science, 59, 230-234.
Sadik, A. (2007). The readiness of faculty members to develop and implement e-learning: The case of an Egyptian university. International journal on e-learning, 6(3), 433-453.
Saekow A., & Samson D. (2011). E-learning Readiness of Thailand’s Universities Comparing to the USA’s Cases. International Journal of e-Education, e-business, e-Management and e-Learning, 1(2), 126-131.
Sek, Y., Lau, S., Teoh, K., & Law, C. (2010). Prediction of User Acceptance and Adoption of Smart Phone for Learning with Technology Acceptance Model. Journal of Applied Sciences, 10(20), 2395-2402.
Shareef, A. M., Kumar, V., Kumar, U., & Dwivedi, Y.K. (2011). E-learning adoption model (GAM): differing service maturity levels. Government Information Quarterly, 28, 17–35.
Sharma, K. S., & Chandel, K. (2013). Technology Acceptance Model for the use of learning through websites among students in Oman. International Arab Journal of e-Technology, 3(1), 44-49.
Sharma, S. K., Chandel, J. K., Govindaluri, S. M., & FakhrElDin, H. (2014). Students’ acceptance and satisfaction of learning through course websites. Education, Business and Society: Contemporary Middle Eastern, 7(2), 152–166.
Shroff, H. R., Deneed, C. C., & Ng, E. M. (2011). Analysis of the technology acceptance model in examining students’ behavioural intention to use an eportfolio system. Australasian Journal of Educational Technology, 27(4), 600-618.
Sulčič, V., & Lesjak, D. (2009). E-learning and study effectiveness. Journal of Computer Information Systems, 49(3), 40–47.
Tarhini, A., Hone, K., & Liu, X. (2015). A cross-cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between British and Lebanese university students. British Journal of Educational Technology, 46(4), 739–755.
Teo, T., & Noyes, J. (2014). Explaining the intention to use technology among pre-service teachers: A multi-group analysis of the Unified Theory of Acceptance and Use of Technology. Interactive Learning Environments, 22(1), 51–66.
Venkatesh V., & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204.
Wong, K.-T., Teo, T., & Goh, P. S. C. (2015). Understanding the intention to use interactive whiteboards: Model development and testing. Interactive Learning Environments, 23(6), 731–747.