A study on factors hindering online learning acceptance in developing countries

Advents of online learning and its applications have given tertiary-organizations a better operating system to broaden their educational system via internet which offers students with flexibility and ubiquity to embrace online-learning innovation anywhere and at any time. Regrettably, in developing countries, least studies have been conducted to explore the factors conducive to learners' acclaimed versatility regarding online learning. This study employed technology acceptance model as a groundwork in examining objection of online-learning. Partial least squares(PLS) structural equation modeling utilized to analyze the 869 responses of students studying in four tertiary institutions that permitted for this learning mode in Nigeria. Hypotheses tested on power supply, technical resources, perceptive usefulness and ease towards behavioral intents of students to adopt online learning in Smartpls engine supported in this study, expect ease of use on behavioral intents to accept the system failed. All regressed significant at p-value < 0.003, and a variance explained of 75% of factors achieved in this study. However, supported factors in the Nigeria context may not in countries, because of some cultural differences and technology readiness. Thus, recommended the replication of this study to increase the generalizability of this result achieved

[1]  A. I. Gambari,et al.  ACCEPTANCE OF INFORMATION TECHNOLOGY FOR TEACHING IN NIGERIAN VOCATIONAL AND TECHNICAL EDUCATION: A CONFIRMATORY FACTOR ANALYSIS , 2016 .

[3]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[4]  Sowemimo Ronke Adekunmisi,et al.  Use of Multimedia for Teaching in Nigerian University System: A Case Study of University of Ibadan , 2012 .

[5]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[6]  Kevin P. Hwang,et al.  The combined model of influencing on-line consumer behavior , 2010, Expert Syst. Appl..

[7]  H. Kaiser.  An index of factorial simplicity , 1974 .

[8]  Dietmar K. Kennepohl.  Science Online and at a Distance , 2009 .

[9]  M. Bartlett,et al.  A note on the multiplying factors for various chi square approximations , 1954 .

[10]  Sebastian Vogt,et al.  Review of distance education research (2000 to 2008): Analysis of research areas, methods, and authorship patterns , 2009 .

[11]  Richard T. Watson,et al.  WebQual: An Instrument for Consumer Evaluation of Web Sites , 2007, Int. J. Electron. Commer..

[12]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[13]  Joseph Wilson,et al.  The Internet and the Nigerian Woman: A Case of Female Undergraduates , 2015 .

[14]  Khalil Md Nor,et al.  Adoption of Internet Banking by Yemeni Consumers : An Empirical Investigation , 2013 .

[15]  E. Wahab,et al.  Regions of Trust to Technological Know-how Structured for Banking Customers , 2015 .

[16]  M. Bartlett.  A Note on the Multiplying Factors for Various χ2 Approximations , 1954 .

[17]  Solomon Oluyinka Ayodele,et al.  Role of power supply towards e-learning acceptance: VBSEM-AMOS , 2016, 2016 6th International Conference on Information Communication and Management (ICICM).

[18]  Ulf-Daniel Ehlers,et al.  Web 2.0 – e‐learning 2.0 – quality 2.0? Quality for new learning cultures , 2009 .

[19]  A. AdesinaAderonke,et al.  An Empirical Investigation of the Level of Users’ Acceptance of E-Banking in Nigeria , 2010 .

[20]  Charles K. Ayo,et al.  Business-to-consumer e-commerce in Nigeria: Prospects and challenges , 2011 .

[21]  Alina Shamsuddin,et al.  A study of electronic commerce adoption factors in Nigeria , 2013, Int. J. Inf. Syst. Chang. Manag..

[22]  R. Raisamo,et al.  Investigating students' behavioural intention to adopt and use mobile learning in higher education in East Africa , 2014 .

[23]  Sarah Guri-Rosenblit,et al.  Distance Education in the Digital Age: Common Misconceptions and Challenging Tasks , 2009 .

[24]  Marko Sarstedt,et al.  An assessment of the use of partial least squares structural equation modeling in marketing research , 2012 .

[25]  Chia-Chi Chang,et al.  Effects of individuals' locus of control and computer self-efficacy on their e-learning acceptance in high-tech companies , 2014, Behav. Inf. Technol..

[26]  Sung Youl Park,et al.  An Analysis of the Technology Acceptance Model in Understanding University Students' Behavioral Intention to Use e-Learning , 2009, J. Educ. Technol. Soc..

[27]  D. Gerbing,et al.  Viability of exploratory factor analysis as a precursor to confirmatory factor analysis , 1996 .