DOES ANXIETY IMPEDE VLE ADOPTION INTENTIONS OF STATE UNIVERSITY LECTURERS? - A STUDY BASED ON MODIFIED UTAUT FRAMEWORK

Asanka Gunasinghe, Junainah Abd Hamid, Ali Khatibi, S. M. Ferdous Azam

Abstract


Purpose of this study is to gain a deeper understanding of technology adoption in higher educational contexts. More precisely, this study would examine the significance of technology anxiety within the UTAUT framework in determining VLE adoption intentions of non-users from the perspective of Sri Lankan state university lecturers. A developing country like Sri Lanka can potentially expand higher education sector potentials through ICT integration in the state universities. Thus, a better understanding of university staff attitudes and perceptions about educational technologies such as VLEs is essential for effective use of these technologies which intern offer prolific payoffs. Quantitative methodology was used for primary data collection. QuestionPro online survey tool was employed to send out questionnaires of which returned with 219 valid responses. A unit of the sample was a university lecturer who fit to survey criteria of Non-VLE usage. SPSS and AMOS software was used to analyze data in terms of descriptive and hypotheses testing using structured equation modelling. By adding the technology anxiety as an external component (i.e., affection) to UTAUT factors (mainly cognitive and behavioral), this study enhanced the response power of the framework in determining adoption intention of non-users in the study context. Further, the theorized relationships between UTAUT factors and technology anxiety would fulfil the gap in the lack of literature that connects affective, cognitive components to predict technology adoption in the presence of demographics such as lecturer’s age and gender. Results of the study reveal that performance expectancy, facilitating conditions, has a positive correlation with VLE adoption intention, while technology anxiety confirms its significant negative effect on the same. Further, it was found that technology anxiety has positive effects on both performance expectancy and effort expectancy although one variable (PE) indicate a mediation effect. However, the effect of technology anxiety on all hypothesized relationships was moderated by lecturer’s age and gender.

 

Article visualizations:

Hit counter

DOI

Keywords


Unified Theory of Acceptance and Use of Technology (UTAUT), Virtual Learning Environment (VLE), anxiety, blended learning, teacher technology acceptance, Structured Equation Modelling (SEM), mediation, moderation, Sri Lanka

Full Text:

PDF

References


Abdullah, F., Ward, R., & Ahmed, E. (2016). Investigating the influence of the most commonly used external variables of TAM on students’ Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios. Computers in Human Behavior, 63, 75-90.

Althuizen, N. (2018). Using structural technology acceptance models to segment intended users of a new technology: Propositions and an empirical illustration. Information Systems Journal, 28(5), 879-904.

Aslan, A., & Zhu, C. (2018). Starting Teachers' Integration of ICT into Their Teaching Practices in the Lower Secondary Schools in Turkey. Educational Sciences: Theory and Practice, 18(1), 23-45.

Bandura, A. (1986). The explanatory and predictive scope of self-efficacy theory. Journal of social and clinical psychology, 4(3), 359-373.

Barnett, T., Pearson, A. W., Pearson, R., & Kellermanns, F. W. (2015). Five-factor model personality traits as predictors of perceived and actual usage of technology. European Journal of Information Systems, 24(4), 374-390.

Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of personality and social psychology, 51(6), 1173.

Baruch, Y., & Holtom, B. C. (2008). Survey response rate levels and trends in organizational research. Human relations, 61(8), 1139-1160.

BECTA. (2003). BECTA (British Educational Communications and Technology Agency). Virtual and managed learning environments. British Educational Communications and Technology Agency. Retrieved from http://homepages.shu.ac.uk/~edsjlc/ict/becta/technical_papers/pdf/v_&_mle.pdf

Celik, H. (2016). Customer online shopping anxiety within the Unified Theory of Acceptance and Use Technology (UTAUT) framework. Asia Pacific Journal of Marketing and Logistics, 28, 278-307. doi:10.1108/apjml-05-2015-0077

Colis, B., & Moonen, J. (2001). Flexible Learning in a Digital World: Experiences and Expectations. Open & Distance Learning Series. In: Sterling, VA: Stylus Publishing.

Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS quarterly, 145-158.

Dedeoglu, B. B., Bilgihan, A., Ye, B. H., Buonincontri, P., & Okumus, F. (2018). The impact of servicescape on hedonic value and behavioral intentions: The importance of previous experience. International Journal of Hospitality Management, 72, 10-20.

Demissie, D. H. (2011). Investigating users' acceptance of a Learning Community Management System (LCMS) in the Commonwealth of The Bahamas: The Unified Theory of Acceptance and Use of Technology (UTAUT) framework approach: State University of New York at Albany.

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2017). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 1-16.

El-Masri, M., & Tarhini, A. (2017). Factors affecting the adoption of e-learning systems in Qatar and USA: Extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Educational Technology Research and Development, 65, 743-763. doi:10.1007/s11423-016-9508-8

Farooq, M. S., Salam, M., Jaafar, N., Fayolle, A., Ayupp, K., Radovic-Markovic, M., & Sajid, A. (2017). Acceptance and use of lecture capture system (LCS) in executive business studies: Extending UTAUT2. Interactive Technology and Smart Education, 14(4), 329-348.

Field, A. (2013). Discovering statistics using IBM SPSS statistics: sage.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.

Gamage, D., & Fernando, S. (2012, 2012). Engaging interactivity in elearning: review of practices and challenges in Sri Lanka. Paper presented at the 30th National Information Technology Conference.

Hair Jr, J. F., Babin, B. J., & Krey, N. (2017). Covariance-based structural equation modeling in the Journal of Advertising: Review and recommendations. In (Vol. 46, pp. 163-177). Journal of Advertising.

Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM): Sage Publications.

Harris, M. E., Mills, R. J., Fawson, C., & Johnson, J. J. (2018). Examining the Impact of Training in the Unified Theory of Acceptance and Use of Technology. Journal of Computer Information Systems, 58(3), 221-233.

He, J., & Freeman, L. A. (2010). Understanding the formation of general computer self-efficacy. Communications of the Association for Information Systems, 26(1), 12.

Holzmann, P., Schwarz, E. J., & Audretsch, D. B. (2018). Understanding the determinants of novel technology adoption among teachers: the case of 3D printing. The Journal of Technology Transfer, 1-17.

Huang, L. (2017). Acceptance of Mobile Learning in Classroom Instruction among College English Teachers in China Using an Extended TAM. Paper presented at the 2017 International Conference of Educational Innovation through Technology (EITT).

Igbaria, M., & Chakrabarti, A. (1990). Computer anxiety and attitudes towards microcomputer use. Behaviour & Information Technology, 9(3), 229-241.

Joint Information Systems Committee. (2009). Technology and tools for online learning. Retrieved from https://www.jisc.ac.uk/full-guide/technology-and-tools-for-online-learning

Juric, J., & Lindenmeier, J. (2018). An empirical analysis of consumer resistance to smart-lighting products. Lighting Research & Technology, 1477153518774080.

Khechine, H., & Lakhal, S. (2018). Technology as a Double-Edged Sword: From Behavior Prediction with UTAUT to Students’ Outcomes Considering Personal Characteristics. JOURNAL OF INFORMATION TECHNOLOGY EDUCATION-RESEARCH, 17, 63-102.

Koohang, A. A. (1989). A Study of Attitudes Toward Computers - Anxiety, Confidence, Liking, and Perception of Usefulness. Journal of Research on Computing in Education, 22(2), 137-150. doi:10.1080/08886504.1989.10781909

Lawton, J., & Gerschner, V. T. (1982). A review of the literature on attitudes towards computers and computerized instruction. Journal of Research & Development in Education.

Long, T., Cummins, J., & Waugh, M. (2018). Investigating the factors that influence higher education instructors' decisions to adopt a flipped classroom instructional model. British Journal of Educational Technology.

Maican, C. I., Cazan, A.-M., Lixandroiu, R. C., & Dovleac, L. (2019). A study on academic staff personality and technology acceptance: The case of communication and collaboration applications. Computers & Education, 128, 113-131.

Mallinckrodt, B., Abraham, W. T., Wei, M., & Russell, D. W. (2006). Advances in testing the statistical significance of mediation effects. Journal of Counseling Psychology, 53(3), 372.

McKenna, B., Tuunanen, T., & Gardner, L. (2013). Consumers’ adoption of information services. Information & Management, 50(5), 248-257.

Nair, P. K., Ali, F., & Leong, L. C. (2015). Factors affecting acceptance & use of ReWIND: Validating the extended unified theory of acceptance and use of technology. Interactive Technology and Smart Education, 12(3), 183-201.

Nanayakkara, S. (2017). Impact of Free and Open-source Software Paradigm for Environmental Sustainability-Case Study in Higher Education Sector. International Journal of Research in Electronics and Computer Engineering, 5(4), 174-188.

Nanayakkara, S., & Kusumsiri, N. (2013). Barriers to Successful Implementation of E-Learning in Design Education. International Journal of Computer Science & Technology, 7(1), 25-30.

Nandwani, S., & Khan, S. (2016). Teachers’ Intention towards the Usage of Technology: An Investigation Using UTAUT Model. Journal of Education & Social Sciences, 4(2), 95-111.

Oshlyansky, L., Cairns, P., & Thimbleby, H. (2007, 2007/09/03/). Validating the Unified Theory of Acceptance and Use of Technology (UTAUT) Tool Cross-culturally. Paper presented at the 21st BCS HCI Group Conference.

Palvia, S., Aeron, P., Gupta, P., Mahapatra, D., Parida, R., Rosner, R., & Sindhi, S. (2018). Online Education: Worldwide Status, Challenges, Trends, and Implications. In: Taylor & Francis.

Parsons, A. (2017). Accessibility and use of VLEs by students in further education. Research in Post-Compulsory Education, 22(2), 271-288.

Peng, D. (2019). Mobile-Based Teacher Professional Training: Influence Factor of Technology Acceptance. In Foundations and Trends in Smart Learning (pp. 161-170): Springer.

Powell, A. L. (2013). Computer anxiety: Comparison of research from the 1990s and 2000s. Computers in Human Behavior, 29(6), 2337-2381.

Raman, A., Don, Y., Khalid, R., Hussin, F., Omar, M. S., & Ghani, M. (2014). Technology acceptance on smart board among teachers in Terengganu using UTAUT model. Asian Social Science, 10(11), 84.

Russell, G., & Bradley, G. (1997). Teachers' computer anxiety: implications for professional development. Education and Information Technologies, 2(1), 17-30. doi:10.1023/A:1018680322904

Saadé, R. G., & Kira, D. (2006). The emotional state of technology acceptance. Issues in Informing Science & Information Technology, 3.

Saadé, R. G., & Kira, D. (2009). Computer anxiety in e-learning: The effect of computer self-efficacy. Journal of Information Technology Education: Research, 8, 177-191.

Samaradiwakara, G., & Gunawardena, C. (2014). Comparison of existing technology acceptance theories and models to suggest a well improved theory/model. International technical sciences journal, 1(1), 21-36.

Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach: John Wiley & Sons.

Skoumpopoulou, D., Wong, A. K., Ng, P. M., & Lo, M. F. (2018). Factors that affect the acceptance of new technologies in the workplace: a cross case analysis between UK and Hong Kong.

Smith, B., & Caputi, P. (2001). Cognitive interference in computer anxiety. Behaviour & Information Technology, 20(4), 265-273.

Sumak, B., Polancic, G., & Hericko, M. (2010, 2010/02//). An Empirical Study of Virtual Learning Environment Adoption Using UTAUT. Paper presented at the Second International Conference on Mobile, Hybrid, and On-Line Learning.

Tacken, M., Marcellini, F., Mollenkopf, H., Ruoppila, I., & Szeman, Z. (2005). Use and acceptance of new technology by older people. Findings of the international MOBILATE survey: ‘Enhancing mobility in later life’. Gerontechnology, 3(3), 126-137.

Teo, T., Milutinović, V., & Zhou, M. (2016). Modelling Serbian pre-service teachers' attitudes towards computer use: A SEM and MIMIC approach. Computers & Education, 94, 77-88.

Tibenderana, P. K., & Ogao, P. J. (2008). Acceptance and use of electronic library services in Ugandan universities. Paper presented at the Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries.

Uğur, N. G., & Turan, A. H. (2018). E-learning adoption of academicians: a proposal for an extended model. Behaviour & Information Technology, 37(4), 393-405.

University Grants Commission Sri Lanka. (2017). Sri Lanka University Statistics 2017. Retrieved from Colombo:

Van Raaij, E. M., & Schepers, J. J. L. (2008). The acceptance and use of a virtual learning environment in China. Computers & Education, 50(3), 838-852.

Venkatesh, V., & Davis, F. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204. doi:10.1287/mnsc.46.2.186.11926

Venkatesh, V., Morris, M. G., & Ackerman, P. L. (2000). A longitudinal field investigation of gender differences in individual technology adoption decision-making processes. Organizational behavior and human decision processes, 83(1), 33-60.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.

Venkatesh, V., Thong, J. Y., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328-376.

Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS quarterly, 12(1), 157-178.

Wickramasinghe, V. (2018). Higher education in state universities in Sri Lanka: Review of higher education since colonial past through international funding for development. International Journal of Educational Management, 32(3), 463-478.

Wong, K.-T., Russo, S., & McDowall, J. (2012). Understanding early childhood student teachers’ acceptance and use of interactive whiteboard. Campus-Wide Information Systems, 30(1), 4-16.

Wong, K.-T., Teo, T., & Russo, S. (2013). Interactive whiteboard acceptance: Applicability of the UTAUT model to student teachers. The Asia-Pacific Education Researcher, 22(1), 1-10.

Zainudin, A. (2012). A handbook on SEM: Structural equation modelling using amos graphics. In: Kelantan: University Technology MARA Press.




Copyright (c) 2019 Asanka Gunasinghe, Junainah Abd Hamid, Ali Khatibi, S. M. Ferdous Azam

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

The research works published in this journal are free to be accessed. They can be shared (copied and redistributed in any medium or format) and\or adapted (remixed, transformed, and built upon the material for any purpose, commercially and\or not commercially) under the following terms: attribution (appropriate credit must be given indicating original authors, research work name and publication name mentioning if changes were made) and without adding additional restrictions (without restricting others from doing anything the actual license permits). Authors retain the full copyright of their published research works and cannot revoke these freedoms as long as the license terms are followed.

Copyright © 2015 - 2018. European Journal Of Social Sciences Studies (ISSN 2501-8590) is a registered trademark of Open Access Publishing Group. All rights reserved.

This journal is a serial publication uniquely identified by an International Standard Serial Number (ISSN) serial number certificate issued by Romanian National Library. All the research works are uniquely identified by a CrossRef DOI digital object identifier supplied by indexing and repository platforms. All the research works published on this journal are meeting the Open Access Publishing requirements and standards formulated by Budapest Open Access Initiative (2002), the Bethesda Statement on Open Access Publishing (2003) and  Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities (2003) and can be freely accessed, shared, modified, distributed and used in educational, commercial and non-commercial purposes under a Creative Commons Attribution 4.0 International License. Copyrights of the published research works are retained by authors.


 

Hit counter