In the era of electronic-learning 3.0, existing dimensions related to technologies and learner are not adequately explored while discussing e-learning adoption. In the current study, technology and learner dimensions are converged to overcome this insufficiency in analysing e-learning adoption. Earlier studies have reported less about e-learning adoption in higher education through the users' lens. System parameters and learner attributes were derived from theories of information systems and literature on learning theories. To validate the research model, 704 responses were collected through a questionnaire survey from India, where e-learning is gearing up. The present article utilised Partial Least Square Structural Equation Modeling (PLS-SEM), which describes the relationship between constructs in the research model. The study identifies technology and learner dimension factors that influence e-learning adoption in developing countries like India. The study also put forward implications and policy recommendations from the findings.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Acharya, B., & Lee, J. (2018). Users’ perspective on the adoption of e-learning in developing countries: The case of Nepal with a conjoint-based discrete choice approach. Telematics and Informatics, 35(6), 1733–1743.
Ahmed, H. (2010). Hybrid E-learning acceptance model: Learner perceptions. Decision Sciences Journal of Innovative Education, 8(2), 313–346.
Al Hebaishi, S. (2018). Using the flipped classroom model to enhance problem-based learning in a practicum course. International Journal of Technology Enhanced Learning, 10(4), 329.
Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2019). Evaluating e-learning systems success: An empirical study. Computers in Human Behavior, 102, 67–86.
Alajarmeh, N., & Rashed, A. (2018). Learner in the role of instructor: Promoting student peer-collaboration in learning management systems. International Journal of Technology Enhanced Learning, 1(1), 1.
Aldhafeeri, F., & Khan, B. (2016). Teachers’ and students’ views on e-learning readiness in kuwait’s secondary public schools. Journal of Educational Technology Systems, 45(2), 202–235.
Alfraih, M. M., & Alanezi, F. (2016). Accounting students’ perceptions of effective faculty attributes. Journal of International Education in Business, 9(2), 123–142.
Almutairi, H., & Subramanian, G. H. (2005). An empirical application of the Delone and Mclean model in the Kuwaiti private sector. Journal of Computer Information Systems, 45(3), 113–122.
Alraimi, K. M., Zo, H., & Ciganek, A. P. (2015). Understanding the MOOCs continuance: The role of openness and reputation. Computers & Education, 80, 28–38.
Amasha, M. A., & AbdElrazek, E. E. (2016). An m-learning framework in the podcast form (MPF) using context-aware technology. International Journal of Advanced Computer Science and Applications, 7(12), 226–234.
Andersson, A., & Hatakka, M. (2010). Increasing interactivity in distance educations: Case studies Bangladesh and Sri Lanka. Information Technology for Development, 16(1), 16–33.
Aparicio, M., Bacao, F., & Oliveira, T. (2017). Grit in the path to e-learning success. Computers in Human Behavior, 66, 388–399.
Arbaugh, J. B. (2002). Managing the online classroom: A study of technological and behavioral characteristics of web-based MBA courses. Journal of High Technology Management Research, 13(2), 203–223.
Bagchi, K. (2005). Factors contributing to global digital divide: some empirical results. Journal of Global Information Technology Management, 8(3), 47–65.
Bailey, J. E., & Pearson, S. W. (1983). Development of a tool for measuring and analysing computer user satisfaction. Management Science, 29(5), 530–545.
Bandura, A. (1991). Sociocognitive theory of human adaptation. (p. 247). p: Prentice-Hall.
Barbeite, F. G., & Weiss, E. M. (2004). Computer self-efficacy and anxiety scales for an internet sample: Testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20(1), 1–15.
Barclay, C., Donalds, C., & Osei-Bryson, K. (2018). Investigating critical success factors in online learning environments in higher education systems in the Caribbean. Information Technology for Development, 24(3), 582–611.
Bawack, R., & Kala Kamdjoug, J. (2020). The role of digital information use on student performance and collaboration in marginal universities. International Journal of Information Management, 54, 102179.
Benbya, H., Passiante, G., & Aissa Belbaly, N. (2004). Corporate portal: A tool for knowledge management synchronisation. International Journal of Information Management, 24(3), 201–220.
Bharucha, J. (2018). Learning and social software: Exploring the realities in India. Journal of Information Communication and Ethics in Society, 16(1), 75–89.
Bhattacharya, I., & Sharma, K. (2007). India in the knowledge economy – an electronic paradigm. International Journal of Educational Management, 21(6), 543–568.
Bisht, R. K., Jasola, S., & Bisht, I. P. (2020). Acceptability and challenges of online higher education in the era of COVID-19: a study of students' perspective. Asian Education and Development Studies, 2046–3162.https://doi.org/10.1108/AEDS-05-2020-0119. Emerald Publishing Limited.
Bliuc, A., Goodyear, P., & Ellis, R. (2007). Research focus and methodological choices in studies into students’ experiences of blended learning in higher education. The Internet and Higher Education, 10(4), 231–244.
Bo, C., Wang, M., Morch, A. I., Chen, N.-S., Kinshuk, K., & Spector, J. M. (2014). Research on e-learningintheworkplace2000–2012:Abibliometricanalysisoftheliterature. Educational Research Review, 11, 56–72.
Boateng, R., Mbrokoh, A., Boateng, L., Senyo, P., & Ansong, E. (2016). Determinants of e-learning adoption among students of developing countries. International Journal of Information and Learning Technology, 33(4), 248–262.
Brahmasrene, T., & Lee, J. (2012). Determinants of intent to continue using online learning: A tale of two universities. Interdisciplinary Journal of Information, Knowledge, and Management, 7, 001–020.
Brandfinance.com. (2019). https://brandfinance.com/images/upload/brand_finance_india_100_2018locked.pdf.
Brown, S. (2010). From VLEs to learning webs: the implications of Web 2.0 for learning and teaching. Interactive Learning Environments, 18(1), 1–10.
Carte, T., Dharmasiri, A., & Perera, T. (2011). Building IT capabilities: Learning by doing. Information Technology for Development, 17(4), 289–305.
Chang, V. (2016). Review and discussion: E-learning for academia and industry. International Journal of Information Management, 36(3), 476–485.
Chang, J., & King, W. (2005). Measuring the performance of information systems: A functional scorecard. Journal of Management Information Systems, 22(1), 85–115.
Chauhan, A. (2014). Massive open online courses (MOOCs): emerging trends in assessment and accreditation. Digital Education Review, 25(7), 17.
Chawla, D., & Joshi, H. (2012). Management education through e-learning in India: An empirical study. Campus-Wide Information Systems, 29(5), 380–393.
Chen, H., & Tseng, H. (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.
Cheng, M. Y. (2012). Effects of quality antecedents on e-learning acceptance. Internet Research, 22(3), 361–390.
Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Computers and Education, 63(1), 160–175.
Chou, H., & Wang, T. (2000). The influence of learning style and training method on self-efficacy and learning performance in WWW homepage design training. International Journal of Information Management, 20(6), 455–472.
Cidral, W., Oliveira, T., Di Felice, M., & Aparicio, M. (2018). E-learning success determinants: Brazilian empirical study. Computers & Education, 122, 273–290.
Davis, F. D. (1998). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Davis, F., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.
Davis, F., Bagozzi, R., & Warshaw, P. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111–1132.
de Vreede, G.-J., & Mgaya, R. J. S. (2006). Technology supported collaborative learning for higher education: Comparative case studies in Tanzania. Information Technology for Development, 12(2), 113–130.
DeLone, W., & McLean, E. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95.
DeLone, W. H., & Mclean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30.
Delone, W. H., & Mclean, E. R. (2014). Journal of management the DeLone and McLean model of information systems success : A ten-year update, 37–41.
Detlor, B. (2000). Corporate portal as an information infrastructure: towards a framework for portal design. International Journal of Information Management, 20(2), 91–101.
Diamond, S., & Irwin, B. (2013). Using e‐learning for student sustainability literacy: Framework and review. International Journal of Sustainability in Higher Education, 14(4), 338–348.
Dominic, M., Francis, S., & Pilomenraj, A. (2014). E-learning in web 3.0. Modern Education and Computer Science, 6(2), 8–14.
Duffy, T., & Jonassen, D. (1991). Constructivism: new implications for instructional technology? Educational Technology, 31(5), 3–12.
Elearning market trends and forecast 2017–2021. (2020). https://eclass.teicrete.gr/modules/document/file.php/TP271/Additional%20material/docebo-elearning-trends-report-2017.pdf.
Elkaseh, A., Wong, K., & Fung, C. (2016). Perceived ease of use and perceived usefulness of social media for e-learning in Libyan higher education: A structural equation modeling analysis. International Journal of Information and Education Technology, 6(3), 192–199.
Ellis, R., Ginns, P., & Piggott, L. (2009). E-learning in higher education: Some key aspects and their relationship to approaches to study. Higher Education Research & Development, 28(3), 303–318.
Ertmer, P., & Newby, T. (2013). Behaviorism, cognitivism, constructivism: Comparing critical features from an instructional design perspective. Performance Improvement Quarterly, 26(2), 43–71.
Fakhoury, R., & Aubert, B. (2017). The impact of initial learning experience on digital services usage diffusion: A field study of e-services in Lebanon. International Journal of Information Management, 37(4), 284–296.
Fleming, J., Becker, K., & Newton, C. (2017). Factors for successful e-learning: does age matter? Education + Training, 59(1), 76–89.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Frederickson, N., Reed, P., & Clifford, V. (2005). Evaluating web-supported learning versus lecture-based teaching: Quantitative and qualitative perspectives. Higher Education, 50(4), 645–664.
Fryer, L., & Bovee, H. (2016). Supporting students’ motivation for e-learning: Teachers matter on and off line. The Internet and Higher Education, 30, 21–29.
Fun-mooc.fr. (2020). FUN - Se Former En Liberté. https://www.fun-mooc.fr/.
Gable, G. G., Sedera, D., & Chan, T. (2008). Re-conceptualizing information system success: The IS-impact measurement model. Journal of the Association for Information Systems, 9(7), 377–408.
Garcia-Crespo, A., Gomez-Berbis, J., Colombo-Palacios, R., & Garcia-Sanchez, F. (2011). Digital libraries and Web 3.0. The Callimachus DL approach. Computers in Human Behavior, 27(4), 1424–1430.
García-Peñalvo, F., Fidalgo-Blanco, Á., & Sein-Echaluce, M. (2018). An adaptive hybrid MOOC model: Disrupting the MOOC concept in higher education. Telematics and Informatics, 35(4), 1018–1030.
Geetha, P., Cherukulath, W. K., & Sivakumar, R. (2017). Facilitating e-learning through national knowledge network. DESIDOC Journal of Library & Information Technology, 37(2), 91.
George, P.P., Papachristou, N., Belisario, J. M., Wang, W., Wark, P. A., Cotic, Z., Car, L. T. (2014). Online eLearning for undergraduates in health professions: a systematic review of the impact on knowledge, skills, attitudes and satisfaction. Journal of Global Health, 4(1).
Gong, M., Xu, Y., & Yu, Y. (2004). An enhanced technology acceptance model for web-based learning. Journal of Information Systems Education, 15(4), 365–373.
Gong, X., Liu, Z., & Zheng, X. (2018). Why are experienced users of WeChat likely to continue using the app? Asia Pacific Journal of Marketing and Logistics, 30(4), 013–1039.
Gronlund, A., & Islam, Y. (2010). A mobile e-learning environment for developing countries: The Bangladesh virtual interactive classroom. Information Technology for Development, 16(4), 244–259.
Hafez, M. (2018). Measuring the impact of corporate social responsibility practices on brand equity in the banking industry in Bangladesh. International Journal of Bank Marketing, 36(5), 806–822.
Hair, J. F., Jr., Ringle, C. M., & Sarstedt, M. (2012). Partial least squares: The better approach to structural equation modeling? Long Range Planning, 45(5/6), 312–319.
Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107–123
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24.
Hamidi, H., & Chavoshi, A. (2018). Analysis of the essential factors for the adoption of mobile learning in higher education: a case study of students of the University of Technology. Telematics and Informatics, 35(4), 1053–1070.
Hao, S., Dennen, V., & Mei, L. (2016). Influential factors for mobile learning acceptance among Chinese users. Educational Technology Research and Development, 65(1), 101–123.
Hargittai, E., & Shafer, S. (2006). Differences in actual and perceived online skills: the role of gender. Social Science Quarterly, 87(2), 432–448.
Henseler, J. (2010). On the convergence of the partial least squares path modeling algorithm. Computational Statistics, 25(1), 107–120.
Hermeking, M. (2006). Culture and internet consumption: Contributions from cross-cultural marketing and advertising research. Journal of Computer-Mediated Communication, 11(1), 192–216.
Huang, H. M. (2002). Student perceptions in an online mediated environment. International Journal of Instructional Media, 29(4), 405e422.
Huber, F., Herrmann, A., Meyer, F., Vogel, J., & Vollhardt, K. (2007). Causal modeling with partial least squares: An application-oriented introduction. Accident, Analysis and Prevention, 68, 57–74.
Hung, D. (2001). Design principles for web-based learning; implications for Vygotskian thought. Educational Technology, 41(3), 33–41.
Hung, M., Chou, C., Chen, C., & Own, Z. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090.
Ifinedo, P. (2017). Students’ perceived impact of learning and satisfaction with blogs. International Journal of Information and Learning Technology, 34(4), 322–337.
Ilin, V. (2020). The Good, the bad and the ugly. A broad look at the adaptation of technology in education. The International Education and Learning Review, 2(1), 31–44.
Internetworldstats.com. (2019). Internet top 20 countries –internet users 2019. https://www.internetworldstats.com/top20.htm.
Islam, A., & Azad, N. (2015). Satisfaction and continuance with a learning management system. International Journal of Information and Learning Technology, 32(2), 109–123.
Jacobsen, D. Y. (2019). Dropping out or dropping in? A connectivist approach to understanding participants’ strategies in an e-learning MOOC pilot. Technology, Knowledge and Learning, 24(1), 1-21.
Jan, S. K. (2015). The relationships between academic self-efficacy, icacy, prior experience, and satisfaction with online learning. American Journal of Distance Education, 29(1), 30–40.
Jeong Kim, H., Pederson, S., & Baldwin, M. (2012). Improving user satisfaction via a case-enhanced e-learning environment. Education + Training, 54(2/3), 204–218.
Johnson, P., & Duberley, J. (2013). Understanding management research – an introduction to epistemology. (p. 53). SAGE Publications.
Jonassen, D. (1991). Objectivism versus constructivism: Do we need a new philosophical paradigm? Educational Technology Research and Development, 39(3), 5–14.
Joo, Y. J., Bong, M., & Choi, H. J. (2000). Self-efficacy for self-regulated learning, academic self-efficacy, and internet self-efficacy in web-based instruction. Educational Technology Research and Development, 48(2), 5–17.
Kapoor, K., Dwivedi, Y., & Williams, M. (2014). Rogers’ Innovation adoption attributes: A systematic review and synthesis of existing research. Information Systems Management, 31(1), 74–91.
Kerr, M., Rynearson, K., & Kerr, M. (2006). Student characteristics for online learning success. The Internet and Higher Education, 9(2), 91–105.
Kim, B., & Park, M. J. (2018). Effect of personal factors to use ICTs on e-learning adoption: Comparison between learner and instructor in developing countries. Information Technology for Development, 24(4), 706–732.
King, W., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43(6), 740–755.
Kodama, M. (2001). Distance learning using video terminals—an empirical study. International Journal of Information Management, 21(3), 227–243.
Kop, R. (2011). The challenges to connectivist learning on open online networks: Learning experiences during a massive open online course. The International Review of Research in Open and Distributed Learning, 12(3), 19.
Kumar, A. (2007). E-learning: A tool for education in rural India. Asia Pacific Business Review, 3(2), 0973–2470.
Kuo, Y. C., Walker, A. E., Belland, B. R., Schroder, K. E., & Kuo, Y. T. (2014). A case study of integrating interwise: Interaction, internet self-efficacy, and satisfaction in synchronous online learning environments. The International Review of Research in Open and Distributed Learning, 15(1), 161e181.
Laaziz, E., & Elkhouzai, E. (2018). An analysis of the permeability of Moroccan higher education to e-learning and simulation based e-learning. International Journal of Technology Enhanced Learning, 10(3), 254.
Lassila, O., & Hendler, J. (2007). Embracing ‘Web 3.0. IEEE Internet Computing, 11(3), 90–93.
Lee, Y., & Choi, J. (2010). A review of online course dropout research: Implications for practice and future research. Educational Technology Research and Development, 59(5), 593–618.
Lee, P. M. J., & Quek, C. (2017). Preschool teachers’ perceptions of school learning environment and job satisfaction. Learning Environments Research, 21(3), 369–386.
Liaw, S.-S. (2004). Considerations for developing constructivist web-based learning. International Journal of Instructional Media, 31(3), 309.
Liaw, S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: a case study of the blackboard system. Computers & Education, 51(2), 864–873.
Liaw, S.-S., & Huang, H.-M. (2010). A study of investigating learners attitudes toward e-learning. 5th international conference on distance learning and education (pp. 12).
Liaw, S.-S., Huang, H.-M., & Chen, G.-D. (2007a). Surveying instructor and learner attitudes toward e-learning. Computers & Education, 49(4), 1066–1080.
Liaw, S.-S., Huang, H.-M., & Chen, G.-D. (2007b). An activity-theoretical approach to investigate learners’ factors toward e-learning systems. Computers in Human Behavior, 23(4), 1906–1920.
Lim, H., Lee, S., & Nam, K. (2007). Validating E-learning factors affecting training effectiveness. International Journal of Information Management, 27(1), 22–35.
Lin, H., & Lee, G. (2006). Determinants of success for online communities: An empirical study. Behavior & Information Technology, 25(6), 479–488.
Lin, J. C. C., & Lu, H. (2000). Towards an understanding of the behavioral intention to use a web site. International Journal of Information Management, 20(3), 197–208.
Liu, Y., & Feng, H. (2011). An empirical study on the relationship between metacognitive strategies and online-learning behavior & test achievements. Journal of Language Teaching and Research, 2(1), 990–992.
MacGregor, G., & Turner, J. (2009). Revisiting e-learning effectiveness: Proposing a conceptual model. Interactive Technology and Smart Education, 6(3), 156–172.
Machado-Da-Silva, F., Meirelles, F., Filenga, D., & Filho, M. (2014). Student satisfaction process in virtual learning system: Considerations based in information and service quality from Brazil’s experience. Turkish Online Journal of Distance Education, 15(3), 122–142.
McGill, T., Klobas, J., & Renzi, S. (2014). Critical success factors for the continuation of e-learning initiatives. The Internet and Higher Education, 22, 24–36.
McKinney, V., Yoon, K., & Zahedi, F. (2002). The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Information Systems Research, 13(3), 296–315.
McLester, S. (2002). Virtual learning takes a front row seat. Technology and Learning, 22(8), 24–31.
Merhi, M. (2015). Factors influencing higher education students to adopt podcast: An empirical study. Computers & Education, 83, 32–43.
Mohammed, A., Kumar, S., Maina, B., & Shuaibu, A. (2017). E-learning: A tool for enhancing teaching and learning in educational institutes. International Journal of Computer Science and Information Technologies, 8(2), 217–221.
Moore, J., Dickson-Deane, C., & Galyen, K. (2011). E-learning, online learning, and distance learning environments: Are they the same? The Internet and Higher Education, 14(2), 129–135.
Nam, C. W., & Zellner, R. D. (2011). The relative effects of positive interdependence and group processing on student achievement and attitude in online cooperative learning. Computers & Education, 56(3), 680–688.
Nedungadi, P., Mulki, K., & Raman, R. (2017). Improving educational outcomes & reducing absenteeism at remote villages with mobile technology and WhatsAPP: Findings from rural India. Education and Information Technologies, 23(1), 113–127.
Ngampornchai, A., & Adams, J. (2016). Students’ acceptance and readiness for e-learning in Northeastern Thailand. International Journal of Educational Technology in Higher Education, 13(1), 34.
Nneka Eke, H. (2010). The perspective of e-learning and libraries in Africa: challenges and opportunities. Library Review, 59(4), 274–290.
Offir, B., Lev, Y., Lev, Y., Barth, I., & Shteinbek, A. (2004). An integrated analysis of verbal and nonverbal interaction in conventional and distance learning environment. Journal of Educational Computing Research, 31(2), 101e118.
Oliver, R., & Omari, A. (2001). Student responses to collaborating and learning in a web-based environment. Journal of Computer Assisted Learning, 17(1), 34–47.
Ong, C.-S., Lai, J.-Y., & Wang, Y.-S. (2004). Factors affecting engineers’ acceptance of asynchronous e-learning systems in high-tech companies. Information & Management, 41(6), 795–804.
Ozkan, S., Koseler, R., & Baykal, N. (2009). Evaluating learning management systems. Transforming Government: People, Process and Policy, 3(2), 111–130.
Paechter, M., & Maier, B. (2010). Online or face-to-face? Students’ experiences and preferences in e-learning. Internet and Higher Education, 13(4), 292–297.
Paliwoda-Pekoszand, G., & Stal, J. (2015). ICT in supporting content and language integrated learning: Experience from Poland. Information Technology for Development, 21(3), 403–425.
Parikh, M., & Verma, S. (2002). Utilizing Internet technologies to support learning: An empirical analysis. International Journal of Information Management, 22(1), 27–46.
Park, Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use e-learning. Education Technology Society, 3(150), 162.
Park, J. H., & Wentling, T. (2007). Factors associated with transfer of training in workplace e-learning. Journal of Workplace Learning, 19(5), 311–329.
Parkes, M., Stein, S., & Reading, C. (2015). Student preparedness for university e-learning environments. The Internet and Higher Education, 25, 1–10.
Passerini, K., & Granger, M. J. (2000). A developmental model for distance learning using the internet. Computers & Education, 34(1), 0360–1315.
Pellas, N. (2014). The influence of computer self-efficacy, metacognitive self-regulation and self-esteem on student engagement in online learning programs: Evidence from the virtual world of second life. Computers in Human Behavior, 35, 157–170.
Peng, H., Tsai, C., & Wu, Y. (2006). University students’ self-efficacy and their attitudes toward the internet: the role of students’ perceptions of the internet. Educational Studies, 32(1), 73–86.
Peter, J. (1979). Reliability: A review of psychometric basics and recent marketing practices. Journal of Marketing Research, 16(1), 6.
Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-based virtual learning environments: A research framework and a preliminary assessment of effectiveness in basic IT skills training. MIS Quarterly, 401-426.
Pituch, K., & Lee, Y. (2006). The influence of system characteristics on e-learning use. Computers & Education, 47(2), 222–244.
Pritchard, A., & Woollard, J. (2010). Psychology for the classroom: Constructivism and social learning. . Routledge.
Qu, L., & Johnson, W.L. (2005). Detecting the learner’s motivational states in an interactive learning environment. In Proceedings of the 2005 conference on artificial intelligence in education: Supporting learning through intelligent and socially informed technology (pp. 547–554). IOS Press.
Ramaha, N. T., Mohd, W., & Ismail, F. W. (2012). Assessment of learner’s motivation in web based e-learning. International Journal of Scientific & Engineering Research, 3(8), 1–5.
Ray, A., Bala, P., & Dasgupta, S. (2019). Role of authenticity and perceived benefits of online courses on technology based career choice in India: A modified technology adoption model based on career theory. International Journal of Information Management, 47, 140–151.
Reeves, T. (2000). Alternative assessment approaches for online learning environments in higher education. Journal of Educational Computing Research, 23(1), 101–111.
Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012). Editor’s comments: a critical look at the use of PLS-SEM. MIS Quarterly, 36(1), 3.
Rovai, A. P., & Barnum, K. (2003). On-line course effectiveness: an analysis of student interactions and perceptions of learning. Journal of Distance Education, 18(1), 57–73.
Saade, R., He, X., & Kira, D. (2007). Exploring dimensions to online learning. Computers in Human Behavior, 23(4), 1721–1739.
Salaberry, M. (2000). Pedagogical design of computer mediated communication tasks: Learning objectives and technological capabilities. The Modern Language Journal, 84(1), 28–37.
Samsudeen, S. N., & Mohamed, R. (2019). University students’ intention to use e-learning systems. Interactive Technology and Smart Education, 3, 219–238,1741–5659
Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., & Hair, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM): a useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105–115.
Scott, S., Plotnikoff, R., Karunamuni, N., Bize, R., & Rodgers, W. (2008). Factors influencing the adoption of an innovation: An examination of the uptake of the Canadian Heart Health Kit (HHK). Implementation Science, 3(1).
Segers, M. S. R. (1997). An alternative for assessing problem-solving skills: the overall test. Studies in Educational Evaluation, 23(4), 373–398.
Selim, H. (2003). An empirical investigation of student acceptance of course websites. Computers & Education, 40(4), 343–360.
Selim, H. M. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. International Journal of Technology Marketing, 2(2), 157–182.
Sharma, M. (2020). India’S burgeoning youth are the world’s future. mint. https://www.livemint.com/Opinion/2WSy5ZGR9ZO3KLDMGiJq2J/Indias-burgeoning-youth-are-the-worlds-future.html.
Shim, S., Lee, B., & Kim, S. (2018). Rival precedence and open platform adoption: An empirical analysis. International Journal of Information Management, 38(1), 217–231.
Shraim, K., & Khlaif, Z. (2010). An e-learning approach to secondary education in Palestine: Opportunities and challenges. Information Technology for Development, 16(3), 159–173.
Shroff, R., Deneen, C., & Ng, E. (2011). Analysis of the technology acceptance model in examining students’ behavioral intention to use an e-portfolio system. Australasian Journal of Educational Technology, 27(4), 8–10.
Shyu, S., & Huang, J. (2011). Elucidating usage of e-government learning: A perspective of the extended technology acceptance model. Government Information Quarterly, 28(4), 491–502.
Shehzadi, S., Nisar, Q. A., Hussain, M. S., Basheer, M. F., Ul Hameed, W., & Chaudhry, N. I. (2020). The role of digital learning toward students' satisfaction and university brand image at educational institutes of Pakistan: A post-effect of COVID-19. Asian Education and Development Studies, 2046–3162. Emerald Publishing Limited.
Simmering, M., Posey, C., & Piccoli, G. (2009). Computer self-efficacy and motivation to learn in a self-directed online course. Decision Sciences Journal of Innovative Education, 7(1), 99–121.
Sosik, J. J., Kahai, S. S., & Piovoso, M. J. (2009). Silver bullet or voodoo statistics?: A primer for using the partial least squares data analytic technique in group and organisation research. Group and Organization Management, 34(1), 5–36.
Stern, H. H. (1983). Fundamental concepts of language teaching. . Oxford University Press.
Stricker, D., Weibel, D., & Wissmath, B. (2011). Efficient learning using a virtual learning environment in a university class. Computers & Education, 56(2), 495–504.
Sukserm, T., & Takahashi, Y. (2012). Self-efficacy as a mediator of the relationships between learning and ethical behavior from human resource development in corporate social responsibility activity. Asia-Pacific Journal of Business Administration, 4(1), 8–22.
Sun, P., Tsai, R., 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.
Susskind, J. E. (2005). PowerPoint’s power in the classroom: Enhancing students’ self-efficacy and attitudes. Computers & Education, 45(2), 203–215.
Tang, Y., & Hew, K. (2017). Is mobile instant messaging (MIM) useful in education? Examining its technological, pedagogical, and social affordances. Educational Research Review, 21(2), 85–104.
Tarhini, A., Hone, K., & Liu, X. (2014). The effects of individual differences on e-learning users’ behavior in developing countries: A structural equation model. Computers in Human Behavior, 41, 153–163.
The Economic Times. (2019). 2019: Latest news & videos, photos about 2019. The Economic Times [online] https://economictimes.indiatimes.com/topic/2019.
Thompson, L., Meriac, J., & Cope, J. (2002). Motivating online performance. Social Science Computer Review, 20(2), 149–160.
Tripathi, M., & Jeevan, V. (2010). E-learning library and information science: A pragmatic view for India. DESIDOC Journal of Library & Information Technology, 30(5), 83–90.
Tudge, J., & Winterhoff, P. (1993). Vygotsky, Piaget, and Bandura: Perspectives on the relations between the social world and cognitive development. Human Development, 36(2), 61–81.
Urbach, N., & Ahlemann, F. (2010a). Partial least squares structural equation modeling (PLS-SEM): An application in customer satisfaction research. Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application, 11(2), 5–40.
Urbach, N., & Ahlemann, F. (2010b). Structural equation modeling in information systems research using partial least squares. Journal of Information Technology Theory and Application, 11, 5–40.
Urbach, N., Smolnik, S., & Riempp, G. (2010). Journal of strategic information systems an empirical investigation of employee portal success. Journal of Strategic Information Systems, 19(3), 184–206. Elsevier B.V.
Uppal, M., Ali, S., & Gulliver, S. (2017). Factors determining e-learning service quality. British Journal of Educational Technology, 49(3), 412–426.
Urbach, N., Smolnik, S., & Riempp, G. (2010). An empirical investigation of employee portal success. The Journal of Strategic Information Systems, 19(3), 184–206.
Venkatesh, V. (1999). Creation of favorable user perceptions: Exploring the role of intrinsic motivation. MIS Quarterly, 23(2), 239.
Venkatesh, V., & Davis, F. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451–481.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425–478.
Wang, Y. (2003). Assessment of learner satisfaction with asynchronous electronic learning systems. Information & Management, 41(1), 75–86.
Wang, H., & Chiu, Y. (2011). Assessing e-learning 2.0 system success. Computers & Education, 57(2), 1790–1800.
Wang, A., & Newlin, M. (2002). Predictors of web-student performance: The role of self-efficacy and reasons for taking an on-line class. Computers in Human Behavior, 18(2), 151–163.
Weiser, O., Blau, I., & Eshet-Alkalai, Y. (2018). How do medium naturalness, teaching-learning interactions and students’ personality traits affect participation in synchronous e-learning? The Internet and Higher Education, 37, 40.
Wu, Y., & Tsai, C. (2006). University students’ internet attitudes and internet self-efficacy: A study at three universities in Taiwan. Cyber Psychology & Behavior, 9(4), 441–450.
Yilmaz, R. (2017). Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom. Computers in Human Behavior, 70, 251–260.
Yudko, E., Hirokawa, R., & Chi, R. (2008). Attitudes, beliefs, and attendance in a hybrid course. Computers & Education, 50(4), 1217–1227.
Yuen, A. H. K., & Ma, W. (2008). Exploring teacher acceptance of e-earning technology. Asia Pacific Journal of Teacher Education, 36(3), 229–243.
Zaranis, N., & Exarchakos, G. (2018). Does ICT affect the understanding of ellipsoids, cylinders and cones among students from University of Applied Sciences? International Journal of Technology Enhanced Learning, 10(4), 269.
Zhang, D., & Nunamaker, J. (2003). Powering e-Learning in the new millennium: An overview of e-learning and enabling technology. Information Systems Frontiers, 5(2), 207–218.
Zhang, L., Wen, H., Li, D., Fu, Z., & Cui, S. (2010). E-learning adoption intention and its key influence factors based on innovation adoption theory. Mathematical and Computer Modelling, 51(11–12), 1428–1432.
Zhao, L. (2015). The influence of learners’ motivation and attitudes on second language teaching. Theory and Practice in Language Studies, 5(11), 2333–2339.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Vanitha, P., Alathur, S. Factors influencing E-learning adoption in India: Learners' perspective. Educ Inf Technol (2021). https://doi.org/10.1007/s10639-021-10504-4
- Information and Communication Technologies
- Perceived usefulness
- Perceived satisfaction