Abstract
The study focused on technological readiness and computer self-efficacy as predictors of E-learning adoption by Library and Information Science (LIS) students in Nigeria. While literatures have suggested that E-learning adoption is context based, there is a need to examine the predictors of E-learning adoption within the Nigerian context, given the increasing need for E-learning adoption as a result of the COVID-19 Pandemic. As a result, the study used the descriptive correlational research design to study a group of LIS students in Nigeria. Consequently, LIS students in the Nigeria Library and Information Science Students (NLISS) Facebook group were used for the study. The population of the group was 1,807 at the time the study was conducted and the sample size for the study was 320 randomly selected respondents. The sample size was achieved using the Krejcie, R. V., and D. W. Morgan. 1970. “Determining Sample Size for Research Activities.” Educational and Psychological Measurement 30: 607–10 table for determining sample size. Data was collected from the respondents using a closed-ended questionnaire consisting of adapted scales for all the variables. The 223 responses retrieved within a period of three weeks were analysed using descriptive and inferential statistics. The findings from the investigation showed technological readiness, computer self-efficacy and E-learning adoption of the LIS students is very high. Though technological readiness and computer self-efficacy had relative contribution to E-learning adoption, computer self-efficacy had higher contribution. The study also revealed that significant relationships exist between technological readiness and E-learning adoption, computer self-efficacy and E-learning adoption, technological readiness and computer self-efficacy, while technological readiness and computer self-efficacy had joint prediction on E-learning adoption by LIS students in Nigeria. The study therefore emphasized the need to consider certain individual factors as criteria to the successful adoption of E-learning among LIS students in Nigeria.
References
Abdullah, D., and I. Mustafa. 2019. “The Underlying Factors of Computer Self-efficacy and the Relationship with Students’ Academic Achievement.” International Journal of Research in Education and Science (IJRES) 5 (1): 346–54.Search in Google Scholar
Al-Araibi, A., M. N. bin Mahrin, and R. Yusoff. 2019. “Technological Aspect Factors of E-learning Readiness in Higher Education Institutions: Delphi Technique.” Educational Information Technology 24: 567–90, https://doi.org/10.1007/s10639-018-9780-9.Search in Google Scholar
Al-Rahmi, W., N. Alias, M. S. Othman, A. Alzahrani, O. Alfarraj, A. Saged, and N. S. Rahman. 2018. “Use of E-learning by University Students in Malaysian Higher Educational Institutions: A Case in UniversitiTeknologi Malaysia.” IEEE Access 6, https://doi.org/10.1109/ACCESS.2018.2802325.Search in Google Scholar
Bakirtaş, H., and C. Akkaş. 2017. “Technology Readiness for New Technologies: An Empirical Study.” The Journal of International Social Research 10 (52): 941–9, https://doi.org/10.17719/jisr.2017.1948.Search in Google Scholar
Borrero, J., S. Yousafzai, U. Javed, and K. Page. 2014. “Expressive Participation in Internet Social Movements: Testing the Moderating Effect of Technology Readiness and Sex on Student SNS Use.” Computers in Human Behavior 30: 39–49, https://doi.org/10.1016/j.chb.2013.07.032.Search in Google Scholar
Celik, I., I. Sahin, and M. Aydin. 2014. “Reliability and Validity Study of the Mobile Learning Adoption Scale Developed Based on the Diffusion of Innovations Theory.” International Journal of Education in Mathematics, Science and Technology 2 (4): 300–16, https://doi.org/10.18404/ijemst.65217.Search in Google Scholar
Chan, C.-L., and C.-L. Lin. 2009. “Determinants of Satisfaction and Intention to Use Self-service Technology – Technology Readiness and Computer Self-efficacy.” In Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing. Kyoto: IEEE, https://doi.org/10.1109/IIH-MSP.2009.115 (accessed March 12, 2021).10.1109/IIH-MSP.2009.115Search in Google Scholar
Chao, C.-M. 2019. “Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTUAT Model.” Frontiers in Psychology 10, https://doi.org/10.3389/fpsyg.2019.01652.Search in Google Scholar
Chien, T.-C. 2012. “Computer Self-efficacy and Factors Influencing E-learning Effectiveness.” European Journal of Training and Development 36 (7): 670–86, https://doi.org/10.1108/03090591211255539.Search in Google Scholar
Chokri, B. 2013. “Factors Influencing the Adoption of the Elearning Technology in Teaching and Learning by Students of a University Class.” European Scientific Journal 8 (28): 165–90, https://doi.org/10.1177/0266666918765907.Search in Google Scholar
Dwivedi, Y., N. Rana, H. Chen, and M. Williams. 2011. “A Meta-analysis of the Unified Theory of Acceptance and Use of Technology (UTAUT).” In Governance and Sustainability in Information Systems. Managing the Transfer and Diffusion of IT. TDIT 2011. IFIP Advances in Information and Communication Technology, Vol. 366, edited by M. Nüttgens, A. Gadatsch, K. Kautz, I. Schirmer, and N. Blinn, 155–70. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-24148-2_10.Search in Google Scholar
Dwivedi, Y., N. Rana, A. Jeyaraj, M. Clement, and M. D. Williams. 2019. “Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model.” Information Systems Frontiers 21: 719–34, https://doi.org/10.1007/s10796-017-9774-y.Search in Google Scholar
Elgort, I. 2005. E-learning Adoption: Bridging the Chasm. ASCILITE, https://www.researchgate.net/publication/252655816_E-learning_adoption_Bridging_the_chasm (accessed March 12, 2021, March 30, 2021).Search in Google Scholar
Geng, S., K. Law, and B. Niu. 2019. “Investigating Self-directed Learning and Technology Readiness in Blending Learning Environment.” International Journal of Educational Technology in Higher Education 16: 17, https://doi.org/10.1186/s41239-019-0147-0.Search in Google Scholar
Howard, M. 2014. “Creation of a Computer Self-efficacy Measure: Analysis of Internal Consistency, Psychometric Properties, and Validity.” Cyberpsychology, Behavior, and Social Networking 17 (10): 677–81, https://doi.org/10.1089/cyber.2014.0255.Search in Google Scholar
Igbinovia, M., and N. Osuchukwu. 2018. “Predictors of Knowledge Sharing Behaviour on Sustainable Development Goals among Library Personnel in Nigeria.” IFLA Journal 44 (2): 119–31, https://doi.org/10.1177/0340035218763445.Search in Google Scholar
Jan, S. 2015. “The Relationships between Academic Self-efficacy, Computer Self-efficacy, Prior Experience, and Satisfaction with Online Learning.” American Journal of Distance Education 29 (1): 30–40, https://doi.org/10.1080/08923647.2015.994366.Search in Google Scholar
Jawadi, N., and A. Akremi. 2006. “Articles in French - II: E-learning Adoption Determinants: A Modified Technology Acceptance Model.” Communications of the Association for Information Systems 18, https://doi.org/10.17705/1CAIS.01802.Search in Google Scholar
Kanwal, F., and M. Rehman. 2017. “Factors Affecting E-learning Adoption in Developing Countries–Empirical Evidence from Pakistan’s Higher Education Sector.” IEEE Access 5 (2017): 10968–78, https://doi.org/10.1109/access.2017.2714379.Search in Google Scholar
Kaushik, K., and D. Agrawal. 2021. “Influence of Technology Readiness in Adoption of E-learning.” International Journal of Educational Management, https://doi.org/10.1108/IJEM-04-2020-0216 (Epub ahead of print).Search in Google Scholar
Khalifeh, G., O. Noroozi, M. Farrokhnia, and E. Talaee. 2020. “Higher Education Students’ Perceived Readiness for Computer-supported Collaborative Learning.” Multimodal Technologies and Interact 4 (11): 1–14, https://doi.org/10.3390/mti4020011.Search in Google Scholar
Krejcie, R. V., and D. W. Morgan. 1970. “Determining Sample Size for Research Activities.” Educational and Psychological Measurement 30: 607–10, https://doi.org/10.1177/001316447003000308.Search in Google Scholar
Lagos Business School. 2020. Accelerated Digital Transformation and the Post-COVID Reality. https://www.lbs.edu.ng/lbsinsight/accelerated-digital-transformation-and-the-post-covid-reality/ (accessed March 12, 2021).Search in Google Scholar
Larasati, N., J. Widyawan, and P. Santosa. 2017. “Technology Readiness and Technology Acceptance Model in New Technology Implementation Process in Low Technology SMEs.” International Journal of Innovation, Management and Technology 8 (2): 113–7, https://www.ijimt.org/vol8/713-IE005.pdf.10.18178/ijimt.2017.8.2.713Search in Google Scholar
Merhi, M. 2015. “Factors Influencing Higher Education Students to Adopt Podcast: An Empirical Study.” Computers and Education 83: 32–43, https://doi.org/10.1016/j.compedu.2014.12.014.Search in Google Scholar
Muries, B., and J. Masele. 2017. “Explaining Electronic Learning Management Systems (ELMS) Continued Usage Intentions among Facilitators in Higher Education Institutions (HEIs) in Tanzania.” International Journal of Education and Development using Information and Communication Technology 13 (1): 123–41.Search in Google Scholar
Murugan, A., G. Sai, and A. Lin. 2017. “Technological Readiness of UiTM Students in Using Mobile Phones in the English Language Classroom.” Malaysian Online Journal of Educational Technology 5 (2): 34–50, https://files.eric.ed.gov/fulltext/EJ1142394.pdf.Search in Google Scholar
Ngampornchai, A., and J. Adams. 2016. “Students’ Acceptance and Readiness for E-learning in Northeastern Thailand.” International Journal of Educational Technology in Higher Education 13: 34, https://doi.org/10.1186/s41239-016-0034-x.Search in Google Scholar
Nugroho, M., and A. Fajar. 2017. “Effects of Technology Readiness towards Acceptance of Mandatory Web-based Attendance System.” Procedia Computer Science 124: 319–28, https://doi.org/10.1016/j.procs.2017.12.161.Search in Google Scholar
Nwobu, B., O. Oyewole, and J. Apotiade. 2016. “Computer Self-efficacy as Correlate of On-line Public Access Catalogue Use: A Case Study.” Information Impact: Journal of Information and Knowledge Management 7 (2): 15–26.10.4314/iijikm.v7i2.2Search in Google Scholar
Olatubosun, O., F. Olusoga, and O. Samuel. 2015. “Adoption of Elearning Technology in Nigerian Tertiary Institution of Learning.” British Journal of Applied Science & Technology 10 (2): 1–15, https://doi.org/10.9734/bjast/2015/18434.Search in Google Scholar
Palau-Saumell, R., S. Forgas-Coll, J. Sánchez-García, and E. Robres. 2019. “User Acceptance of Mobile Apps for Restaurants: An Expanded and Extended UTAUT-2.” Sustainability 11: 1210, https://doi.org/10.3390/su11041210.Search in Google Scholar
Parasuraman, A. 2000. “Technology Readiness Index (TRI): A Multiple-item Scale to Measure Readiness to Embrace New Technologies.” Journal of Service Research 2 (4): 307–20, https://journals.sagepub.com/doi/abs/10.1177/109467050024001.10.1177/109467050024001Search in Google Scholar
Parasuraman, A., and C. Colby. 2014. “An Updated and Streamlined Technology Readiness Index: TRI 2.0.” Journal of Service Research 18 (1): 59–74, https://doi.org/10.1177/1094670514539730.Search in Google Scholar
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: 157–70, https://doi.org/10.1016/j.chb.2014.02.048.Search in Google Scholar
Qteishat, M., and J. Alqatawna. 2013. “Factors Influencing the Adoption of E-learning in Jordan: An Extended TAM Model.” European Journal of Business and Management 5 (18): 84–100.Search in Google Scholar
Saadé, R., and D. Kira. 2009. “Computer Anxiety in E-learning: The Effect of Computer Self Efficacy.” Journal of Information Technology Education 8: 177–91, https://www.jite.org/documents/Vol8/JITEv8p177-191Saade724.pdf.10.28945/3386Search in Google Scholar
Salloum, S., A. Alhamad, M. Al-Emran, A. Monem, and K. Shaalan. 2019. “Exploring Students’ Acceptance of E-learning through the Development of a Comprehensive Technology Acceptance Model.” IEEE Access 7, https://doi.org/10.1109/ACCESS.2019.2939467.Search in Google Scholar
Smit, C., M. Roberts-Lombard, and M. Mpinganjira. 2018. “Technology Readiness and Mobile Self-service Technology Adoption in the Airline Industry: An Emerging Market Perspective.” Acta Commercii 18 (1): a580, https://doi.org/10.4102/ac.v18i1.580.Search in Google Scholar
Tarhini, A., R. Masa’deh, K. Al-Busaidi, A. Mohammed, and M. Maqableh. 2017. “Factors Influencing Students’ Adoption of E-learning: A Structural Equation Modeling Approach.” Journal of International Education in Business 10 (2): 164–82, https://doi.org/10.1108/JIEB-09-2016-0032.Search in Google Scholar
Teo, T. 2009. “Modelling Technology Acceptance in Education: A Study of Pre-service Teachers.” Computers & Education 52 (2): 302–12, https://doi.org/10.1016/j.compedu.2008.08.006.Search in Google Scholar
Thongsri, N., L. Shen, and Y. Bao. 2019. “Investigating Academic Major Differences in Perception of Computer Self-efficacy and Intention toward E-learning Adoption in China.” Innovations in Education & Teaching International, https://doi.org/10.1080/14703297.2019.1585904.Search in Google Scholar
Venkatesh, V., M. Morris, G. Davis, and F. Davis. 2003. “User Acceptance of Information Technology: Toward a Unified View, MIS Q.” International Journal of Computer Science and Applications 27 (3): 425–78, https://doi.org/10.2307/30036540.Search in Google Scholar
Venkatesh, V., J. Thong, and X. Xu. 2016. “Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead.” Journal of the Association for Information Systems 17 (5): 328–76, https://doi.org/10.17705/1jais.00428.Search in Google Scholar
Yakubu, N., and S. Dasuki. 2018. “Factors Affecting the Adoption of E-learning Technologies among Higher Education Students in Nigeria: A Structural Equation Modelling Approach.” Information Development 35 (3): 1–11, https://doi.org/10.1177/0266666918765907.Search in Google Scholar
© 2021 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Articles
- Cognitive Authority as an Instance of Informational and Expert Power
- Technological Readiness and Computer Self-efficacy as Predictors of E-learning Adoption by LIS Students in Nigeria
- Information Inequality among Entrepreneurs in Rural China
- Fostering Knowledge Sharing Behavior Among Pakistani Engineering Students: Role of Individual and Classroom Related Factors
- Digital Literacy of EFL Students: An Empirical Study in Vietnamese Universities
- Desired Affordances of Scholarly E-Articles: Views from Scholars Based on Open-Ended Answers
- Dostoevsky and the Word “Jew”: A Quantitative Analysis of F.M. Dostoevsky’s Greatest Novels
Articles in the same Issue
- Frontmatter
- Articles
- Cognitive Authority as an Instance of Informational and Expert Power
- Technological Readiness and Computer Self-efficacy as Predictors of E-learning Adoption by LIS Students in Nigeria
- Information Inequality among Entrepreneurs in Rural China
- Fostering Knowledge Sharing Behavior Among Pakistani Engineering Students: Role of Individual and Classroom Related Factors
- Digital Literacy of EFL Students: An Empirical Study in Vietnamese Universities
- Desired Affordances of Scholarly E-Articles: Views from Scholars Based on Open-Ended Answers
- Dostoevsky and the Word “Jew”: A Quantitative Analysis of F.M. Dostoevsky’s Greatest Novels