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FACTORS CONTRIBUTING TO VIETNAMESE UNIVERSITY LECTURERS’ BURNOUT IN ONLINE EMERGENCY CLASSROOMS AMIDST THE COVID-19 PANDEMIC

Yıl 2023, Cilt: 24 Sayı: 2, 64 - 92, 01.04.2023
https://doi.org/10.17718/tojde.1020442

Öz

This large-scale study aimed to investigate the impacts of underlying factors on lecturers’ burnout in emergency online classrooms during the outbreak of the Covid-19 pandemic. The study attracted the participation of 399 lecturers who are conducting online emergency classrooms from 30 universities and colleges across Vietnam. Data analyses with EFA, CFA, and SEM indicated that such factors as support resources, anxiety towards emergency online teaching and Coronavirus, lecturer’s technological and pedagogical content, and knowledge significantly impacted their burnout levels. In contrast, no significant difference in burnout states was found between lecturers with different demographic features, including different genders and their residence. The results from this study also suggested critical pedagogical implications for higher education leaders and administrators to prepare emergency online classes for sustained education in times of crisis.

Teşekkür

The authors would like to express our gratitude towards Ms. Linh N. Pham, HQT Education, Ltd., Ho Chi Minh City, Vietnam for her efforts to assist us in the proofreading process of this article.

Kaynakça

  • Ainur, A. K., Sayang, M. D., Jannoo, Z., & Yap, B. W. (2017). Sample size and non-normality effects on goodness of fit measures in structural equation models. Pertanika Journal of Science and Technology, 25(2), 575–586.
  • Al-Fudail, M., & Mellar, H. (2008). Investigating teacher stress when using technology. Computers and Education, 51(3), 1103–1110. https://doi.org/10.1016/j.compedu.2007.11.004
  • Altinay-Gazi, Z., & Altinay-Aksal, F. (2017). Technology as mediation tool for improving teaching profession in higher education practices. Eurasia Journal of Mathematics, Science and Technology Education, 13(3), 803–813. https://doi.org/10.12973/eurasia.2017.00644a
  • Antoniou, A.-S., Ploumpi, A., & Ntalla, M. (2013). Occupational stress and professional burnout in teachers of primary and secondary education: The role of coping strategies. Psychology, 04(03), 349–355. https://doi.org/10.4236/psych.2013.43a051
  • Austin, V., Shah, S., & Muncer, S. (2005). Teacher stress and coping strategies used to reduce stress. Occupational Therapy International, 12(2), 63–80. https://doi.org/10.1002/oti.16
  • Behr, D. (2017). Assessing the use of back translation: the shortcomings of back translation as a quality testing method. International Journal of Social Research Methodology, 20(6), 573–584. https://doi.org/10.1080/13645579.2016.1252188
  • Chen, H., Liu, F., Pang, L., Liu, F., Fang, T., Wen, Y., Chen, S., Xie, Z., Zhang, X., Zhao, Y., & Gu, X. (2020). Are you tired of working amid the pandemic? The role of professional identity and job satisfaction against job burnout. International Journal of Environmental Research and Public Health, 17(24), 1–14. https://doi.org/10.3390/ijerph17249188
  • Cordaro, M. (2020). Pouring from an Empty Cup: The case for compassion fatigue in higher education. Building Healthy Academic Communities Journal, 4(2), 17. https://doi.org/10.18061/bhac.v4i2.7618
  • Cooper, L., Laster-Loftus, A., & Mandernach, B. J. (2019). Efficient online instruction: Maximum impact in minimal time. Online Journal of Distance Learning Administration, 22(3).
  • Cross, T., & Polk, L. (2018). Burn bright, not out: Tips for managing online teaching. Journal of Educators Online, 15(3). https://doi.org/10.9743/jeo.2018.15.3.1
  • Dong, Y., Xu, C., Chai, C. S., & Zhai, X. (2020). Exploring the structural relationship among teachers’ technostress, technological pedagogical content knowledge (TPACK), computer self-efficacy and school support. Asia-Pacific Education Researcher, 29(2), 147–157. https://doi.org/10.1007/s40299-019-00461-5
  • Estrada-Muñoz, C., Castillo, D., Vega-Muñoz, A., & Boada-Grau, J. (2020). Teacher technostress in the chilean school system. International Journal of Environmental Research and Public Health, 17(15), 1–17. https://doi.org/10.3390/ijerph17155280
  • Fagan, M. H., Neill, S., & Wooldridge, B. R. (2003). An empirical investigation into the relationship between computer self-efficacy, anxiety, experience, support and usage. Journal of Computer Information Systems, 44(2), 95–104. https://doi.org/10.1080/08874417.2004.11647572
  • Fernández-Castillo, A. (2021). State-anxiety and academic burnout regarding university access selective examinations in Spain during and after the COVID-19 lockdown. Frontiers in Psychology, 12, 17. https://doi.org/10.3389/fpsyg.2021.621863
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/10.1177/002224378101800313
  • García-González, M. A., Torrano, F., & García-González, G. (2020). Analysis of stress factors for female professors at online universities. International Journal of Environmental Research and Public Health, 17(8). https://doi.org/10.3390/ijerph17082958
  • Hammond, H., Coplan, M., & Mandernach, B. J. (2018). Administrative considerations impacting the quality of online teaching. Online Journal of Distance Learning Administration, 21(4), 1–18.
  • Hidalgo-Andrade, P., Hermosa-Bosano, C., & Paz, C. (2021). Teachers’ mental health and self-reported coping strategies during the covid-19 pandemic in ecuador: A mixed-methods study. Psychology Research and Behavior Management, 14, 933–944. https://doi.org/10.2147/PRBM.S314844
  • Hogan, R. L., & McKnight, M. A. (2007). Exploring burnout among university online instructors: An initial investigation. Internet and Higher Education, 10(2), 117–124. https://doi.org/10.1016/j.iheduc.2007.03.001
  • Joo, Y. J., Lim, K. Y., & Kim, N. H. (2016). The effects of secondary teachers’ technostress on the intention to use technology in South Korea. Computers and Education, 95, 114–122. https://doi.org/10.1016/j.compedu.2015.12.004
  • Kelly, N., & Antonio, A. (2016). Teacher peer support in social network sites. Teaching and Teacher Education, 56, 138–149. https://doi.org/10.1016/j.tate.2016.02.007
  • Lackritz, J. R. (2004). Exploring burnout among university faculty: Incidence, performance, and demographic issues. Teaching and Teacher Education, 20(7), 713–729. https://doi.org/10.1016/j.tate.2004.07.002
  • Lee, S. A. (2020). Coronavirus anxiety scale: A brief mental health screener for COVID-19 related anxiety. Death Studies, 44(7), 393–401. https://doi.org/10.1080/07481187.2020.1748481
  • Maatuk, A. M., Elberkawi, E. K., Aljawarneh, S., Rashaideh, H., & Alharbi, H. (2021). The COVID-19 pandemic and E-learning: Challenges and opportunities from the perspective of students and instructors. Journal of Computing in Higher Education. https://doi.org/10.1007/s12528-021-09274-2
  • Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam. Education and Information Technologies. https://doi.org/10.1007/s10639-021-10465-8
  • Martin, J. (2000). Hidden gendered assumptions in mainstream organizational theory and research. Journal of Management Inquiry, 9(2), 207–216. https://doi.org/10.1177/105649260092017
  • Mesci, M. (2020). The mediating effect of organizational learning on the relationship between the cost leadership strategy and business performance: A study on travel agencies. Journal of Economy Culture and Society, February, 323–343. https://doi.org/10.26650/jecs2020-0085
  • Pressley, T. (2021). Factors contributing to teacher burnout during COVID-19. Educational Researcher, July, 325–327. https://doi.org/10.3102/0013189X211004138
  • Santelli, B., Stewart, K., & Mandernach, J. (2020). Supporting high quality teaching in online programs. Journal of Educators Online, 17(1).
  • Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (Track): The development and validation of an assessment instrument for preservice teachers. Journal of Research on Technology in Education, 42(2), 123–149. https://doi.org/10.1080/15391523.2009.10782544
  • 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
  • Silva, W. A. D., de Sampaio Brito, T. R., & Pereira, C. R. (2020). COVID-19 anxiety scale (CAS): Development and psychometric properties. Current Psychology, 1. https://doi.org/10.1007/s12144-020-01195-0
  • Sokal, L. J., Trudel, L. G. E., & Babb, J. C. (2020). Supporting teachers in times of change: the job demands- resources model and teacher burnout during the COVID-19 pandemic. International Journal of Contemporary Education, 3(2), 67. https://doi.org/10.11114/ijce.v3i2.4931
  • Taber, K. S. (2018). The use of cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
  • Toker, B. (2012). life satisfaction among academicians: An empirical study on the universities of turkey. Procedia - Social and Behavioral Sciences, 47(1), 190–195. https://doi.org/10.1016/j.sbspro.2012.06.637
  • Tümkaya, S. (2007). Burnout and humor relationship among university lecturers. Humor, 20(1), 73–92. https://doi.org/10.1515/HUMOR.2007.004
  • Whitehead, A., Ryba, K., & O’Driscoll, M. (2000). Burnout among New Zealand primary school teachers. New Zealand Journal of Psychology, 29(2), 52–60.
  • Yeşilyurt, E., Ulaş, A. H., & Akan, D. (2016). Teacher self-efficacy, academic self-efficacy, and computer self-efficacy as predictors of attitude toward applying computer-supported education. Computers in Human Behavior, 64(November), 591–601. https://doi.org/10.1016/j.chb.2016.07.038
  • Zadok-Gurman, T., Jakobovich, R., Dvash, E., Zafrani, K., Rolnik, B., Ganz, A. B., & Lev-Ari, S. (2021). Effect of inquiry-based stress reduction (Ibsr) intervention on well-being, resilience and burnout of teachers during the covid-19 pandemic. International Journal of Environmental Research and Public Health, 18(7). https://doi.org/10.3390/ijerph18073689
Yıl 2023, Cilt: 24 Sayı: 2, 64 - 92, 01.04.2023
https://doi.org/10.17718/tojde.1020442

Öz

Kaynakça

  • Ainur, A. K., Sayang, M. D., Jannoo, Z., & Yap, B. W. (2017). Sample size and non-normality effects on goodness of fit measures in structural equation models. Pertanika Journal of Science and Technology, 25(2), 575–586.
  • Al-Fudail, M., & Mellar, H. (2008). Investigating teacher stress when using technology. Computers and Education, 51(3), 1103–1110. https://doi.org/10.1016/j.compedu.2007.11.004
  • Altinay-Gazi, Z., & Altinay-Aksal, F. (2017). Technology as mediation tool for improving teaching profession in higher education practices. Eurasia Journal of Mathematics, Science and Technology Education, 13(3), 803–813. https://doi.org/10.12973/eurasia.2017.00644a
  • Antoniou, A.-S., Ploumpi, A., & Ntalla, M. (2013). Occupational stress and professional burnout in teachers of primary and secondary education: The role of coping strategies. Psychology, 04(03), 349–355. https://doi.org/10.4236/psych.2013.43a051
  • Austin, V., Shah, S., & Muncer, S. (2005). Teacher stress and coping strategies used to reduce stress. Occupational Therapy International, 12(2), 63–80. https://doi.org/10.1002/oti.16
  • Behr, D. (2017). Assessing the use of back translation: the shortcomings of back translation as a quality testing method. International Journal of Social Research Methodology, 20(6), 573–584. https://doi.org/10.1080/13645579.2016.1252188
  • Chen, H., Liu, F., Pang, L., Liu, F., Fang, T., Wen, Y., Chen, S., Xie, Z., Zhang, X., Zhao, Y., & Gu, X. (2020). Are you tired of working amid the pandemic? The role of professional identity and job satisfaction against job burnout. International Journal of Environmental Research and Public Health, 17(24), 1–14. https://doi.org/10.3390/ijerph17249188
  • Cordaro, M. (2020). Pouring from an Empty Cup: The case for compassion fatigue in higher education. Building Healthy Academic Communities Journal, 4(2), 17. https://doi.org/10.18061/bhac.v4i2.7618
  • Cooper, L., Laster-Loftus, A., & Mandernach, B. J. (2019). Efficient online instruction: Maximum impact in minimal time. Online Journal of Distance Learning Administration, 22(3).
  • Cross, T., & Polk, L. (2018). Burn bright, not out: Tips for managing online teaching. Journal of Educators Online, 15(3). https://doi.org/10.9743/jeo.2018.15.3.1
  • Dong, Y., Xu, C., Chai, C. S., & Zhai, X. (2020). Exploring the structural relationship among teachers’ technostress, technological pedagogical content knowledge (TPACK), computer self-efficacy and school support. Asia-Pacific Education Researcher, 29(2), 147–157. https://doi.org/10.1007/s40299-019-00461-5
  • Estrada-Muñoz, C., Castillo, D., Vega-Muñoz, A., & Boada-Grau, J. (2020). Teacher technostress in the chilean school system. International Journal of Environmental Research and Public Health, 17(15), 1–17. https://doi.org/10.3390/ijerph17155280
  • Fagan, M. H., Neill, S., & Wooldridge, B. R. (2003). An empirical investigation into the relationship between computer self-efficacy, anxiety, experience, support and usage. Journal of Computer Information Systems, 44(2), 95–104. https://doi.org/10.1080/08874417.2004.11647572
  • Fernández-Castillo, A. (2021). State-anxiety and academic burnout regarding university access selective examinations in Spain during and after the COVID-19 lockdown. Frontiers in Psychology, 12, 17. https://doi.org/10.3389/fpsyg.2021.621863
  • Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/10.1177/002224378101800313
  • García-González, M. A., Torrano, F., & García-González, G. (2020). Analysis of stress factors for female professors at online universities. International Journal of Environmental Research and Public Health, 17(8). https://doi.org/10.3390/ijerph17082958
  • Hammond, H., Coplan, M., & Mandernach, B. J. (2018). Administrative considerations impacting the quality of online teaching. Online Journal of Distance Learning Administration, 21(4), 1–18.
  • Hidalgo-Andrade, P., Hermosa-Bosano, C., & Paz, C. (2021). Teachers’ mental health and self-reported coping strategies during the covid-19 pandemic in ecuador: A mixed-methods study. Psychology Research and Behavior Management, 14, 933–944. https://doi.org/10.2147/PRBM.S314844
  • Hogan, R. L., & McKnight, M. A. (2007). Exploring burnout among university online instructors: An initial investigation. Internet and Higher Education, 10(2), 117–124. https://doi.org/10.1016/j.iheduc.2007.03.001
  • Joo, Y. J., Lim, K. Y., & Kim, N. H. (2016). The effects of secondary teachers’ technostress on the intention to use technology in South Korea. Computers and Education, 95, 114–122. https://doi.org/10.1016/j.compedu.2015.12.004
  • Kelly, N., & Antonio, A. (2016). Teacher peer support in social network sites. Teaching and Teacher Education, 56, 138–149. https://doi.org/10.1016/j.tate.2016.02.007
  • Lackritz, J. R. (2004). Exploring burnout among university faculty: Incidence, performance, and demographic issues. Teaching and Teacher Education, 20(7), 713–729. https://doi.org/10.1016/j.tate.2004.07.002
  • Lee, S. A. (2020). Coronavirus anxiety scale: A brief mental health screener for COVID-19 related anxiety. Death Studies, 44(7), 393–401. https://doi.org/10.1080/07481187.2020.1748481
  • Maatuk, A. M., Elberkawi, E. K., Aljawarneh, S., Rashaideh, H., & Alharbi, H. (2021). The COVID-19 pandemic and E-learning: Challenges and opportunities from the perspective of students and instructors. Journal of Computing in Higher Education. https://doi.org/10.1007/s12528-021-09274-2
  • Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: an empirical study in Vietnam. Education and Information Technologies. https://doi.org/10.1007/s10639-021-10465-8
  • Martin, J. (2000). Hidden gendered assumptions in mainstream organizational theory and research. Journal of Management Inquiry, 9(2), 207–216. https://doi.org/10.1177/105649260092017
  • Mesci, M. (2020). The mediating effect of organizational learning on the relationship between the cost leadership strategy and business performance: A study on travel agencies. Journal of Economy Culture and Society, February, 323–343. https://doi.org/10.26650/jecs2020-0085
  • Pressley, T. (2021). Factors contributing to teacher burnout during COVID-19. Educational Researcher, July, 325–327. https://doi.org/10.3102/0013189X211004138
  • Santelli, B., Stewart, K., & Mandernach, J. (2020). Supporting high quality teaching in online programs. Journal of Educators Online, 17(1).
  • Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (Track): The development and validation of an assessment instrument for preservice teachers. Journal of Research on Technology in Education, 42(2), 123–149. https://doi.org/10.1080/15391523.2009.10782544
  • 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
  • Silva, W. A. D., de Sampaio Brito, T. R., & Pereira, C. R. (2020). COVID-19 anxiety scale (CAS): Development and psychometric properties. Current Psychology, 1. https://doi.org/10.1007/s12144-020-01195-0
  • Sokal, L. J., Trudel, L. G. E., & Babb, J. C. (2020). Supporting teachers in times of change: the job demands- resources model and teacher burnout during the COVID-19 pandemic. International Journal of Contemporary Education, 3(2), 67. https://doi.org/10.11114/ijce.v3i2.4931
  • Taber, K. S. (2018). The use of cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
  • Toker, B. (2012). life satisfaction among academicians: An empirical study on the universities of turkey. Procedia - Social and Behavioral Sciences, 47(1), 190–195. https://doi.org/10.1016/j.sbspro.2012.06.637
  • Tümkaya, S. (2007). Burnout and humor relationship among university lecturers. Humor, 20(1), 73–92. https://doi.org/10.1515/HUMOR.2007.004
  • Whitehead, A., Ryba, K., & O’Driscoll, M. (2000). Burnout among New Zealand primary school teachers. New Zealand Journal of Psychology, 29(2), 52–60.
  • Yeşilyurt, E., Ulaş, A. H., & Akan, D. (2016). Teacher self-efficacy, academic self-efficacy, and computer self-efficacy as predictors of attitude toward applying computer-supported education. Computers in Human Behavior, 64(November), 591–601. https://doi.org/10.1016/j.chb.2016.07.038
  • Zadok-Gurman, T., Jakobovich, R., Dvash, E., Zafrani, K., Rolnik, B., Ganz, A. B., & Lev-Ari, S. (2021). Effect of inquiry-based stress reduction (Ibsr) intervention on well-being, resilience and burnout of teachers during the covid-19 pandemic. International Journal of Environmental Research and Public Health, 18(7). https://doi.org/10.3390/ijerph18073689
Toplam 39 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Articles
Yazarlar

Thuan Minh Hoang Nguyen Bu kişi benim 0000-0002-3152-9148

Thu Hoai Thi Do Bu kişi benim 0000-0002-8734-0643

Quang Nhat Nguyen Bu kişi benim 0000-0002-9149-5066

Yayımlanma Tarihi 1 Nisan 2023
Gönderilme Tarihi 8 Kasım 2021
Yayımlandığı Sayı Yıl 2023 Cilt: 24 Sayı: 2

Kaynak Göster

APA Nguyen, T. M. H., Do, T. H. T., & Nguyen, Q. N. (2023). FACTORS CONTRIBUTING TO VIETNAMESE UNIVERSITY LECTURERS’ BURNOUT IN ONLINE EMERGENCY CLASSROOMS AMIDST THE COVID-19 PANDEMIC. Turkish Online Journal of Distance Education, 24(2), 64-92. https://doi.org/10.17718/tojde.1020442