Volume index - Journal index - Article index - Map ---- Back

Comunicar Journal 74: Education for digital citizenship: Algorithms, automation and communication (Vol. 31 - 2023)

Factors determining the use of e-learning and teaching satisfaction

https://doi.org/10.3916/C74-2023-07

Ana-Maria Cazan

Catalin-Ioan Maican

Abstract

Even though in 2021 many universities have decided to resume teaching activities face to face, we believe that the use of online applications will remain a feature of the educational system due to the flexibility offered and the learning possibilities. We aim to analyze the predictive role of personal factors, such as self-efficacy, technostress creators, technostress inhibitors, and tolerance to uncertainty in the use of e-learning tools for teaching and in the use of these applications in the context of the uncertainty generated by the pandemic. The sample consisted of 1,517 academics. The results showed that technostress creators mediate the relationships between technostress inhibitors, technology self-efficacy, use of applications, and satisfaction with the use of e-learning platforms. Although the current context is dominated by uncertainty, the hypotheses regarding the direct and indirect effects of uncertainty in the use of online s in education were partially sustained. The most important finding of our study is that, although the current context is characterized by uncertainty, the negative impact of the resulting higher levels of stress can be counteracted by a high level of technology self-efficacy which, in turn, predicts a greater extent the use of platforms and the satisfaction of using these platforms.

Keywords

Technology self-efficacy, technostress creators, technostress inhibitors, intolerance to uncertainty, e-learning, satisfaction

PDF file in Spanish

PDF file in English

References

Al-Samarraie, H., Teng, B.K., Alzahrani, A.I., & Alalwan, N. (2018). E-learning continuance satisfaction in higher education: A unified perspective from instructors and students. Studies in Higher Education, 43(11), 2003-2019. https://doi.org/10.1080/03075079.2017.1298088

Almuwais, A., Alqabbani, S., Benajiba, N., & Almoayad, F. (2021). An Emergency Shift to e-Learning in Health Professions Education: A Comparative Study of Perspectives between Students and Instructors. International Journal of Learning, Teaching and Educational Research, 20(6), 6. https://doi.org/10.26803/ijlter.20.6.2

Bakar, N.S.A., Maat, S.M., & Rosli, R. (2018). A systematic review of teacher’s self-efficacy and technology integration. International Journal of Academic Research in Business and Social Sciences, 8(8). https://doi.org/10.6007/IJARBSS/V8-I8/4611

Bandura, A. (1997). Self-efficacy: The exercise of control. W H Freeman/Times Books/ Henry Holt & Co. https://bit.ly/2FVgMwH

Bordia, P., Hobman, E., Jones, E., Gallois, C., & Callan, V.J. (2004). Uncertainty during organizational change: Types, consequences, and management strategies. Journal of Business and Psychology, 18(4), 507-532. https://doi.org/10.1023/B:JOBU.0000028449.99127.f7

Caprara, G.V., Barbaranelli, C., Borgogni, L., & Steca, P. (2003). Efficacy beliefs as determinants of teachers’ job satisfaction. Journal of Educational Psychology, 95(4), 821-832. https://doi.org/10.1037/0022-0663.95.4.821

Carleton, R.N., Norton, M.A.P.J., & Asmundson, G.J.G. (2007). Fearing the unknown: A short version of the Intolerance of Uncertainty Scale. Journal of Anxiety Disorders, 21(1), 105-117. https://doi.org/10.1016/j.janxdis.2006.03.014

Casero-Béjar, M.O., & Sánchez-Vera, M.M. (2022). Cambio de modalidad presencial a virtual durante el confinamiento por COVID-19: Percepciones del alumnado universitario. RIED, 25(1), 243-260. https://doi.org/10.5944/ried.25.1.30623

Chan, F.K.Y., Thong, J.Y.L., Venkatesh, V., Brown, S.A., Hu, P.J.H., & Tam, K Y. (2010). Modeling citizen satisfaction with mandatory adoption of an E-Government technology. Journal of the Association for Information Systems, 11(10), 519-549. https://doi.org/10.17705/1jais.00239

Chin, W.W. (2010). How to write up and report PLS analyses. In V. Esposito-Vinzi., W. Chin, J. Henseler, & H. Wang. (eds), Handbook of Partial Least Squares (pp. 655-690). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_29

Dugas, M.J., Buhr, K., & Ladouceur, R. (2004). The role of intolerance of uncertainty in etiology and maintenance. In R.G. Heimberg, C.L. Turk, & D.S. Mennin (Eds.), Generalized anxiety disorder: Advances in research and practice (pp. 143-163). The Guilford Press. https://bit.ly/3cXDWFt

Fida, R., Paciello, M., Tramontano, C., Barbaranelli, C., & Farnese, M.L. (2015). “Yes, I can”: The protective role of personal self-efficacy in hindering counterproductive work behavior under stressful conditions. Anxiety, Stress, & Coping, 28(5), 479-499. https://doi.org/10.1080/10615806.2014.969718

Grupe, D.W., & Nitschke, J.B. (2013). Uncertainty and anticipation in anxiety: An integrated neurobiological and psychological perspective. Nature Reviews Neuroscience, 14(7), 488-501. https://doi.org/10.1038/nrn3524

Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020). The difference between emergency remote teaching and online learning. EDUCAUSE Review. https://bit.ly/3bk6MPI

Jena, R.K. (2015). Impact of technostress on job satisfaction: An empirical study among Indian academician. The International Technology Management Review, 5(3), 117-124. https://doi.org/10.2991/itmr.2015.5.3.1

Jerrim, J., & Sims, S. (2021). When is high workload bad for teacher wellbeing? Accounting for the non-linear contribution of specific teaching tasks. Teaching and Teacher Education, 105, 103395. https://doi.org/10.1016/j.tate.2021.103395

Li, L., & Wang, X. (2021). Technostress inhibitors and creators and their impacts on university teachers’ work performance in higher education. Cognition, Technology and Work, 23, 315-330. https://doi.org/10.1007/s10111-020-00625-0

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 and Education, 128, 113-131. https://doi.org/10.1016/j.compedu.2018.09.010

Maier, C., Laumer, S., Eckhardt, A., & Weitzel, T. (2017). Giving too much social support: Social overload on social networking sites. European Journal of Information Systems, 24(5), 447-464. https://doi.org/10.1057/ejis.2014.3

Marasi, S., Jones, B., & Parker, J.M. (2022). Faculty satisfaction with online teaching: A comprehensive study with American faculty. Studies in Higher Education, 47(3), 513-525. https://doi.org/10.1080/03075079.2020.1767050

Marchiori, D.M., Mainardes, E.W., & Rodrigues, R.G. (2019). Do Individual characteristics influence the types of technostress reported by workers? International Journal of Human-Computer Interaction, 35(3), 218-230. https://doi.org/10.1080/10447318.2018.1449713

Mertens, G., Duijndam, S., Smeets, T., & Lodder, P. (2021). The latent and item structure of COVID-19 fear: A comparison of four COVID-19 fear questionnaires using SEM and network analyses. Journal of Anxiety Disorders, 81, 102415. https://doi.org/10.1016/j.janxdis.2021.102415

Mouakket, S., & Bettayeb, A.M. (2015). Investigating the factors influencing continuance usage intention of Learning management systems by university instructors: The Blackboard system case. International Journal of Web Information Systems, 11(4), 491-509. https://doi.org/10.1108/IJWIS-03-2015-0008

Pan, X. (2020). Technology acceptance, technological self-efficacy, and attitude toward technology-based self-directed learning: Learning motivation as a mediator. Frontiers in Psychology, 11, 2791. https://doi.org/10.3389/fpsyg.2020.564294

Pflügner, K., Maier, C., Mattke, J., & Weitzel, T. (2021). Personality Profiles that put users at risk of perceiving technostress: A qualitative comparative analysis with the big five personality traits. Business and Information Systems Engineering, 63(4), 389-402. https://doi.org/10.1007/s12599-020-00668-7

Polly, D., Martin, F., & Guilbaud, T.C. (2021). Examining barriers and desired supports to increase faculty members’ use of digital technologies: Perspectives of faculty, staff and administrators. Journal of Computing in Higher Education, 33(1), 135-156. https://doi.org/10.1007/s12528-020-09259-7

Pressley, T., & Ha, C. (2021). Teaching during a pandemic: United States teachers’ self-efficacy during COVID-19. Teaching and Teacher Education, 106, 103465. https://doi.org/10.1016/j.tate.2021.103465

Prifti, R. (2022). Self–efficacy and student satisfaction in the context of blended learning courses. Open Learning: The Journal of Open, Distance and e-Learning, 37(2), 111-125. https://doi.org/10.1080/02680513.2020.1755642

Ragu-Nathan, T.S., Tarafdar, M., Ragu-Nathan, B.S., & Tu, Q. (2008). The consequences of technostress for end users in organizations: Conceptual development and validation. Information Systems Research, 19(4), 417-433. https://doi.org/10.1287/isre.1070.0165

Ringle, C., Wende, S., & Becker, J. (2015). SmartPLS 3. SmartPLS GmbH. https://bit.ly/3vxn0w2

Rokhimah, S., & Sirait, A. (2021). Educator satisfaction using LMS with ICT infrastructure as a mediation variable. RSF Conference Series: Business, Management and Social Sciences, 1(3), 81-87. https://doi.org/10.31098/bmss.v1i3.291

Salah-Eddine, M., & Belaissaoui, M. (2017). Technostress, coping and job satisfaction model of information systems. In Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016 (pp. 139-142). IEEE. https://doi.org/10.1109/CSCI.2016.0033

Shu, Q., Tu, Q., & Wang, K. (2011). The impact of computer self-efficacy and technology dependence on computer-related technostress: A social cognitive theory perspective. International Journal of Human-Computer Interaction, 27(10), 923-939. https://doi.org/10.1080/10447318.2011.555313

Skaalvik, E.M., & Skaalvik, S. (2017). Still motivated to teach? A study of school context variables, stress and job satisfaction among teachers in senior high school. Social Psychology of Education, 20(1), 15-37. https://doi.org/10.1007/s11218-016-9363-9

Stickney, L.T., Bento, R.F., Aggarwal, A., & Adlakha, V. (2019). Online Higher Education: Faculty Satisfaction and Its Antecedents. Journal of Management Education, 43(5), 509-542. https://doi.org/10.1177/1052562919845022

Syvänen, A., Mäkiniemi, J.P., Syrjä, S., Heikkilä-Tammi, K., & Viteli, J. (2016). When does the educational use of ICT become a source of technostress for Finnish teachers? Seminar.Net, 12(2), 95-109. https://doi.org/10.7577/seminar.2281

Tarafdar, M., Maier, C., Laumer, S., & Weitzel, T. (2020). Explaining the link between technostress and technology addiction for social networking sites: A study of distraction as a coping behavior. Information Systems Journal, 30(1), 96–124. https://doi.org/10.1111/isj.12253

Tarafdar, M., Pullins, E. Bolman., & Ragu-Nathan, T.S. (2015). Technostress: Negative effect on performance and possible mitigations. Information Systems Journal, 25(2), 103-132. https://doi.org/10.1111/isj.12042

Tinaztepe, C. (2012). The effect of desire for change on the relationship between perceived uncertainty and job related affective well being. International Journal of Social Sciences and Humanity Studies, 4(2), 127-136. https://bit.ly/3OPV1yv

UNESCO (Ed.) (2020). COVID-19 response–remote learning strategy. Remote learning strategy as a key element in ensuring continued learning. UNESCO. https://bit.ly/3JmFIfn

Upadhyaya, P., & Vrinda. (2021). Impact of technostress on academic productivity of university students. Education and Information Technologies, 26(2), 1647-1664. https://doi.org/10.1007/s10639-020-10319-9

Uzun, K., & Karata?, Z. (2020). Predictors of academic self efficacy: Intolerance of uncertainty, positive beliefs about worry and academic locus of control. International Education Studies, 13(6), 104-116. https://doi.org/10.5539/ies.v13n6p104

Venkatesh, V., Thong, J.Y.L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use technology. MIS Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412

Ünal, E., Yamaç, A., & Uzun, A.M. (2017). The Effect of the teaching practice course on pre-service elementary teachers’ technology integration self-efficacy. Malaysian Online Journal of Educational Technology, 5(3), 39-53. https://bit.ly/3zWwcg9

Yoo, S.J., Huang, W.H., & Lee, D.Y. (2012). The impact of employee’s perception of organizational climate on their technology acceptance toward e-learning in South Korea. Knowledge Management & E-Learning: An International Journal, 4(3), 359-378. https://doi.org/10.34105/j.kmel.2012.04.028