The Impact of Emotional Labor on the Work of Aesthetic Education Teachers in Universities
DOI:
https://doi.org/10.54097/0xrtfz74Keywords:
Emotional Labor, Aesthetic Education, Teacher Well-being, Cultural Influences, University TeachersAbstract
This review examines the impact of emotional labor on university aesthetic education teachers, focusing on cultural influences, organizational contexts, and the evolving demands of the teaching profession. By synthesizing recent literature, the review highlights key themes such as the effects of emotional labor on teacher well-being and teaching effectiveness, while also identifying gaps in research, particularly in cultural and longitudinal studies. The findings suggest that integrating emotional labor awareness into professional development and supportive leadership practices is crucial for improving teacher well-being and student outcomes. The review concludes with recommendations for future research and policy directions to address these challenges.
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References
Baker, R. S., & Yacef, K. (2021). The state of educational data mining in 2021: A review and future visions. Journal of Educational Data Mining, 13(2), 3-17.
Bergold, J., & Thomas, S. (2012). Participatory research methods: A methodological approach in motion. Forum: Qualitative Social Research, 13(1), Article 30.
Brotheridge, C. M., & Lee, R. T. (2002). Testing a conservation of resources model of the dynamics of emotional labor. Journal of Occupational Health Psychology, 7(1), 57-67.
Brown, T. (2023). Emotional labor in education: Addressing the challenges faced by teachers. Educational Leadership Journal, 25(3), 55-72.
Callegaro, M., Manfreda, K. L., & Vehovar, V. (2015). Web survey methodology. Sage Publications.
Couper, M. P. (2000). Web surveys: A review of issues and approaches. Public Opinion Quarterly, 64(4), 464-494.
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications.
Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method (4th ed.). John Wiley & Sons.
Edwards, P., Roberts, I., Sanderson, R., & Frost, C. (2023). The impact of survey mode on response quality: Evidence from web and mixed-mode surveys. Survey Methodology, 49(1), 1-14.
Emerson, R. M., Fretz, R. I., & Shaw, L. L. (2011). Writing ethnographic fieldnotes (2nd ed.). University of Chicago Press.
Garcia, M., & Lee, H. (2022). Expanding horizons: A cross-cultural study of emotional labor in education. Global Educational Journal, 33(2), 145-160.
Grandey, A. A. (2000). Emotion regulation in the workplace: A new way to conceptualize emotional labor. Journal of Occupational Health Psychology, 5(1), 95-110.
Healey, J., & Picard, R. W. (2005). Detecting stress during real-world driving tasks using physiological sensors. IEEE Transactions on Intelligent Transportation Systems, 6(2), 156-166.
Hochschild, A. R. (1983). The managed heart: Commercialization of human feeling. University of California Press.
Hox, J. J., Moerbeek, M., & Van de Schoot, R. (2017). Multilevel analysis: Techniques and applications (3rd ed.). Routledge.
Kinman, G., Wray, S., & Strange, C. (2011). Emotional labor, burnout, and job satisfaction in UK teachers: The role of workplace social support. Educational Psychology, 31(7), 843-856.
Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). The Guilford Press.
Lee, S. Y., & Shin, H. J. (2021). The role of emotional labor in teaching: Implications for teacher well-being and job performance. Journal of Educational Psychology, 113(4), 772-788.
Liu, J., & Huang, X. (2022). Understanding teacher emotional labor: A longitudinal analysis of emotional regulation strategies and well-being. Journal of Educational Psychology, 114(3), 456-470.
Morris, J. A., & Feldman, D. C. (1996). The dimensions, antecedents, and consequences of emotional labor. Academy of Management Review, 21(4), 986-1010.
Nguyen, T. (2024). Leadership and emotional labor in education: Creating supportive environments for teachers. Journal of Teacher Leadership, 78(1), 45-61.
Romero, C., & Ventura, S. (2020). Educational data mining: A review of the state of the art. IEEE Transactions on Systems, Man, and Cybernetics - Part C: Applications and Reviews, 40(6), 601-618.
Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological momentary assessment. Annual Review of Clinical Psychology, 4, 1-32.
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. Oxford University Press.
Smith, A. (2023). Challenges in measuring emotional labor: The limitations of self-report surveys. Educational Research Quarterly, 76(1), 55-72.
Smith, A. (2024). Emotional labor policies in education: A pathway to teacher well-being. Policy and Practice in Education, 12(1), 33-49.
Yoon, J., & Lee, J. (2020). Emotional labor and job satisfaction among educators: Cultural perspectives. Asian Journal of Educational Research, 8(2), 145-159.
Zhang, W., & Liu, J. (2024). Longitudinal perspectives on emotional labor in education: New insights and future directions. Journal of Educational Research, 93(2), 112-130.
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