The Role of Technostress on Educators' Work Performance at Universities in the Special Capital Region of Jakarta

Dina Syakina, Aulia Rahma, Mohammad Rizal

Abstract


The COVID-19 pandemic forced the education system to adapt a new teaching system from offline to online. However, the ability of lecturers is often unable to keep up with rapid technological developments and the lack of resources provided by institutions, causes lecturers to feel stressed during the teaching and learning process. This study aims to determine the effect of technostress on lecturer performance using the Person-Organization Fit theory approach. The results showed that at the organizational level, the discrepancy between abilities and demands (AD-O) (B= -.39; p<.01) had a significant negative and positive effect on lecturer needs with supplies (NS-O) (B=. 24;p<.05) with performance. At the individual level, the mismatch between needs and supply (NS-T) (B=-.51; p<.01), the absence of social support from colleagues (PPF) (B=-.32; p<.01) had an effect significant negative. The findings of this study indicate that both the organizational level and peer support (AD-O and PPF) as well as the individual level (NS-T) play an important role in predicting a decrease in lecturer performance, while the mismatch between ability demands at the individual level has no effect on performance. The implications of this research will be discussed further in the discussion.

 


Keywords


Higher education; Lecturer; technostress; work performance

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Al-Fudail, M., & Mellar, H. (2008). Investigating teacher stress when using technology. Computers & Education, 51(3), 1103–1110. https://doi.org/10.1016/j.compedu.2007.11.004

Altinay-Gazi, Z., & Altinay-Aksal, F. (2017). Technology as a mediation tool for improving the teaching profession in higher education practices. Eurasia Journal of Mathematics, Science and Technology Education, 13(3), 803–813. https://doi.org/10.12973/eurasia.2017.00 644a

Antonietti, C., Cattaneo, A., & Amenduni, F. (2022). Can teachers’ digital competence influence technology acceptance in vocational education? Computers in Human Behavior, 132, 107266. https://doi.org/https://doi.org/10.1016/ j.chb.2022.107266

Avanzi, L., Fraccaroli, F., Castelli, L., Marcionetti, J., Crescentini, A., Balducci, C., & van Dick, R. (2018). How to mobilize social support against workload and burnout: The role of organizational identification. Teaching and Teacher Education, 69, 154–167. https://doi.org/10.1016/j.tate.2017.10.001

Azwar, S. (2010). Metode Penelitian. Yogyakarta: Pustaka Pelajar.

Bereczki, E. O., & Kárpáti, A. (2021). Technology-enhanced creativity: A multiple case study of digital technology-integration expert teachers’ beliefs and practices. Thinking Skills and Creativity, 39. https://doi.org/10.1016/ j.tsc.2021.100791

Bichler, S., Gerard, L., Bradford, A., & Linn, M. C. (2021). Designing a remote professional development course to support teacher customization in science. Computers in Human Behavior, 123. https://doi.org/10.1016/ j.chb.2021.106814

Carroll, D., Lovallo, W. R., & Phillips, A. C. (2009). Are large physiological reactions to acute psychological stress always bad for health? Social and Personality Psychology Compass, 3(5), 725–743. https://doi.org/10.1111/j.1751-9004.2009.00205.x

Çetin, D., & Bülbül, T. (2017). Okul Yöneticilerinin Teknostres Algıları İle Bireysel Yenilikçilik Özellikleri Arasındaki İlişkinin İncelenmesi. In Abant İzzet Baysal Üniversitesi Eğitim Fakültesi Dergisi, 17(3).

Chen, C.-H. (2008). Chen, C.: Why Do Teachers Not Practice What They Believe Regarding Technology Integration? The Journal of Educational Research 102(1), 65-75. https://doi.org/10.3200/JOER.102.1.65-75

Dahabiyeh, L., Najjar, M. S., & Wang, G. (2022). Online teaching during COVID-19 crisis: the role of technostress and emotional dissonance on online teaching exhaustion and teaching staff productivity. The International Journal of Information and Learning Technology, 39(2), 97–121. https://doi.org/10.1108/IJILT-09-2021-0147

Daniel, S. J. (2020). Education and the COVID-19 pandemic. Prospects, 49(1–2), 91–96. https://doi.org/10.1007/s11125-020-09464-3

Daumiller, M., Rinas, R., Hein, J., Janke, S., Dickhäuser, O., & Dresel, M. (2021). Shifting from face-to-face to online teaching during COVID-19: The role of university faculty achievement goals for attitudes towards this sudden change, and their relevance for burnout/engagement and student evaluations of teaching quality. Computers in Human Behavior, 118. https://doi.org/10.1016/j.chb. 2020.106677

Etikan, I. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1. https://doi.org/10.11648/j.ajtas. 20160501.11

Ferri, F., Grifoni, P., & Guzzo, T. (2020). Online learning and emergency remote teaching: Opportunities and challenges in emergency situations. Societies, 10(4). https://doi.org/10. 3390/soc10040086

Field, A. P. (2018). Discovering statistics using IBM SPSS statistics. Sage Publications.

Fuglseth, A. M., & Sørebø, Ø. (2014). The effects of technostress within the context of employee use of ICT. Computers in Human Behavior, 40, 161–170. https://doi.org/10.1016/j.chb.2014. 07.040

Giorgi, G., Lecca, L. I., Alessio, F., Finstad, G. L., Bondanini, G., Lulli, L. G., Arcangeli, G., & Mucci, N. (2020). COVID-19-related mental health effects in the workplace: A narrative review. International Journal of Environmental Research and Public Health, 17(21), 1–22. https://doi.org/10.3390/ijerph17217857

Graham, C., Burgoyne, N., Cantrell, P., Smith, L., Clair, L., & Harris, R. (2009). Measuring the TPACK Confidence of In-service Science Teachers. TechTrends, 53(5).

Gros Salvat, B., & Silva Quiroz, J. (2005). La Formación Del Profesorado Como Docent E En Los Espacios Virtuales De Aprendizaje. Revista Iberoamericana De Educación, 36(1), 1-14. https://doi.org/10.35362/rie3612831

Hofer, S. I., Nistor, N., & Scheibenzuber, C. (2021). Online teaching and learning in higher education: Lessons learned in crisis situations. Computers in Human Behavior, 121. https://doi.org/10.1016/j.chb.2021.106789

Hogan, R. L., & McKnight, M. A. (2007). Exploring burnout among university online instructors: An initial investigation. The Internet and Higher Education, 10(2), 117–124. https://doi.org/https://doi.org/10.1016/j.iheduc.2007.03.001

Hsiao, K.-L. (2017). Compulsive mobile application usage and technostress: the role of personality traits. Online Information Review, 41(2), 272–295. https://doi.org/10.1108/OIR-03-2016-0091

Hwang, Y. S., Bartlett, B., Greben, M., & Hand, K. (2017). A systematic review of mindfulness interventions for in-service teachers: A tool to enhance teacher wellbeing and performance. Teaching and Teacher Education, 64, 26–42. https://doi.org/10.1016/J.TATE.2017.01.015

Irawati, D. Y., & Jonatan, J. (2020). Evaluasi Kualitas Pembelajaran Online Selama Pandemi Covid-19: Studi Kasus di Fakultas Teknik, Universitas Katolik Darma Cendika. Jurnal Rekayasa Sistem Industri, 9(2), 135–144. https://doi.org/10.26593/jrsi.v9i2.4014.135-144

Jena, R. K. (2015). Technostress in ICT enabled collaborative learning environment: An empirical study among Indian academician. Computers in Human Behavior, 51, 1116–1123. https://doi.org/https://doi.org/10.1016/j.chb.2015.03.020

Jung, I., Kudo, M., & Choi, S.-K. (2012). Stress in Japanese learners engaged in online collaborative learning in English. British Journal of Educational Technology, 43(6), 1016–1029. https://doi.org/10.1111/j.1467-8535.2011.01271.x

Kinyita, P. (2015). Relationship Between Work Stress And Perfomance Of Employees: A Case Study Of Transit Hotel In Nairobi City County. Archives of Business Research, 3(6). https://doi.org/10.14738/abr.36.1538

Ko, E.-J., Kim, A.-H., & Kim, S.-S. (2021). Toward the understanding of the appropriation of ICT-based Smart-work and its impact on performance in organizations. Technological Forecasting and Social Change, 171, 120994. https://doi.org/https://doi.org/10.1016/j.techfore.2021.120994

Koh, J. H. L., Chai, C. S., & Lim, W. Y. (2016). Teacher Professional Development for TPACK-21CL: Effects on Teacher ICT Integration and Student Outcomes. Journal of Educational Computing Research, 55(2), 172–196. https://doi.org/10.1177/0735633116656848

la Torre, G., de Leonardis, V., & Chiappetta, M. (2020). Technostress: how does it affect the productivity and life of an individual? Results of an observational study. Public Health, 189, 60–65. https://doi.org/10.1016/j.puhe.2020.09.013

Lee, S. B., Lee, S. C., & Suh, Y. H. (2016). Technostress from mobile communication and its impact on quality of life and productivity. Total Quality Management and Business Excellence, 27(7–8), 775–790. https://doi.org/10.1080/14783363.2016.1187998

Lemay, D. J., Bazelais, P., & Doleck, T. (2021). Transition to online learning during the COVID-19 pandemic. Computers in Human Behavior Reports, 4. https://doi.org/10.1016/j.chbr. 2021.100130

Luchman, J. N., & González-Morales, M. G. (2013). Demands, control, and support: A meta-analytic review of work characteristics interrelationships. Journal of Occupational Health Psychology, 18(1), 37–52. https://doi.org/10.1037/a0030541

Munyengabe, S., Yiyi, Z., Haiyan, H., & Hitimana, S. (2017). Primary teachers’ perceptions on ICT integration for enhancing teaching and learning through the implementation of one Laptop Per Child program in primary schools of Rwanda. Eurasia Journal of Mathematics, Science and Technology Education, 13(11), 7193–7204. https://doi.org/10.12973/ejmste/79044

Özgür, H. (2020). Relationships between teachers’ technostress, technological pedagogical content knowledge (TPACK), school support and demographic variables: A structural equation modeling. Computers in Human Behavior, 112. https://doi.org/10.1016/j.chb.2020.106468

Penado Abilleira, M., Rodicio-García, M. L., Ríos-de Deus, M. P., & Mosquera-González, M. J. (2021). Technostress in Spanish University Teachers During the COVID-19 Pandemic. Frontiers in Psychology, 12. https://doi.org/10. 3389/fpsyg.2021.617650

Penado Abilleira, M., Rodicio-García, M. L., Ríos-de-Deus, M. P., & Mosquera-González, M. J. (2020). Technostress in Spanish University Students: Validation of a Measurement Scale. Frontiers in Psychology, 11. https://doi.org/ 10.3389/fpsyg.2020.582317

Pullins, E., Tarafdar, M., & Pham, P. (2020). The dark side of sales technologies: how technostress affects sales professionals. Journal of Organizational Effectiveness, 7(3), 297–320. https://doi.org/10.1108/JOEPP-04-2020-0045

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

Rahayu, R. P., & Wirza, Y. (2020). Teachers’ Perception of Online Learning during Pandemic Covid-19. Jurnal Penelitian Pendidikan, 20, 392–406.

Salanova, M., Llorens, S., & Cifre, E. (2013). The dark side of technologies: Technostress among users of information and communication technologies. International Journal of Psychology, 48(3), 422–436. https://doi.org/10.1080/00207594.2012.680460

Scherer, R., Howard, S. K., Tondeur, J., & Siddiq, F. (2021). Profiling teachers’ readiness for online teaching and learning in higher education: Who’s ready? Computers in Human Behavior, 118. https://doi.org/10.1016/j.chb.2020.106675

Schildkamp, K., van der Kleij, F. M., Heitink, M. C., Kippers, W. B., & Veldkamp, B. P. (2020). Formative assessment: A systematic review of critical teacher prerequisites for classroom practice. International Journal of Educational Research, 103. https://doi.org/10.1016/j.ijer. 2020.101602

Skaalvik, E. M., & Skaalvik, S. (2015). Job satisfaction, stress and coping strategies in the teaching profession-what do teachers say? International Education Studies, 8(3), 181–192. https://doi.org/10.5539/ies.v8n3p181.

Shadiev, R., & Yang, M. (2020). Review of studies on technology-enhanced language learning and teaching. Sustainability, 12(2), 524.

Stošić, L., & Stošić, I. (2015). Perceptions of teachers regarding the implementation of the internet in education. Computers in Human Behavior, 53, 462–468. https://doi.org/10.1016/ j.chb.2015.07.027

Tang, Y. M., Chen, P. C., Law, K. M. Y., Wu, C. H., Lau, Y.-Y., Guan, J., He, D., & Ho, G. T. S. (2021). Comparative analysis of Student’s live online learning readiness during the coronavirus (COVID-19) pandemic in the higher education sector. Computers & Education, 168, 104211. https://doi.org/10.1016/j.compedu.2021.104211

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., Tu, Q., Ragu-Nathan, B. S., & Ragu-Nathan, T. S. (2007). The impact of technostress on role stress and productivity. Journal of Management Information Systems, 24(1), 301–328. https://doi.org/10.2753/MIS0742-1222240109

Tiwari, V. (2021). Countering effects of technostress on productivity: moderating role of proactive personality. Benchmarking, 28(2), 636–651. https://doi.org/10.1108/BIJ-06-2020-0313.

Voet, M., & de Wever, B. (2017). Towards a differentiated and domain-specific view of educational technology: An exploratory study of history teachers’ technology use. British Journal of Educational Technology, 48(6), 1402–1413. https://doi.org/https://doi.org/10.1111/bjet.12493

Wang, X., & Li, B. (2019). Technostress among teachers in higher education: An investigation from multidimensional person-environment misfit. Frontiers in Psychology, 10(JULY). https://doi.org/10.3389/fpsyg.2019.01791

Yunita, P. I., & Saputra, I. G. N. W. H. (2019). Millennial generation in accepting mutations: Impact on work stress and employee performance. International Journal of Social Sciences and Humanities, 3(1), 102–114. https://doi.org/10.29332/ijssh.v3n1.268.

Zheng, F., Khan, N. A., & Hussain, S. (2020). The COVID 19 pandemic and digital higher education: Exploring the impact of proactive personality on social capital through internet self-efficacy and online interaction quality. Children and Youth Services Review, 119, 105694. https://doi.org/10.1016/j.childyouth. 2020.105694




DOI: https://doi.org/10.24167/psidim.v22i1.4935

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