Abstract
The COVID-19 pandemic has posed an unprecedented threat to the resilience of higher education worldwide, and university students had been thrust overnight into the emergency online learning. The end of COVID-19 pandemic is in sight, however, teachers and students have been forced to live with its disruptive effects indefinitely. Online teaching has been regarded as a panacea for maintaining the resilience of higher education during COVID-19 pandemic, it is significantly important to reflect on students’ learning experiences and learning gains in online classes to improve future online teaching quality. Using a sample of 3514 participants located in the Chinese university context, this study aimed to investigate the determinants that affect students’ learning gains in online learning anchored by self-determination theory. The results indicated a significant positive impact of teachers’ emotional support in predicting students’ learning gains in online classes, and also revealed the positive mediating effect of students’ basic psychological needs satisfaction in bridging these two variables. Moreover, the findings highlighted the sophisticated role of students’ achievement motivation interacting with teachers’ emotional support to influence students’ basic psychological needs satisfaction and learning gains. Implications regarding how to improve undergraduate students’ learning gains in the future’s online teaching were discussed.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data Availability
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to measures to protect participant confidentiality.
Notes
Notes: The significance of the demographic information in this study is threefold. Firstly, it helped us capture an overall picture of a large sample, enabling generalization of the study’s result. Secondly, demographic variables were included as control variables in the proposed model to eliminate possible confound effects. Thirdly, we attempted to construct and test a multi-group structural equation model relating to students from double first-class universities and non-double first-class universities, but the results were not significant and therefore not presented in the manuscript.
References
Aboagye, E., Yawson, J. A., & Appiah, K. N. (2020). COVID-19 and e-learning: The challenges of students in tertiary institutions. Social Education Research, 2(1), 1–8. https://doi.org/10.37256/ser.212021422
Amerstorfer, C. M., & Freiin von Münster-Kistner, C. (2021). Student perceptions of academic engagement and student-teacher relationships in problem-based learning. Frontiers in Psychology, 12, 713057. https://doi.org/10.3389/fpsyg.2021.713057
Atkinson, J. W., & Litwin, G. H. (1960). Achievement motive and test anxiety conceived as motive to approach success and motive to avoid failure. The Journal of Abnormal and Social Psychology, 60(1), 52–63. https://doi.org/10.1037/h0041119
Barrot, J. S., Llenares, I. I., & del Rosario, L. S. (2021). Students’ online learning challenges during the pandemic and how they cope with them: The case of the Philippines. Education and Information Technologies, 26, 7321–7338. https://doi.org/10.1007/s10639-021-10589-x
Biwer, F., Wiradhany, W., Egbrink, M. O., Hospers, H., & Bruin, A. D. (2021). Changes and adaptations: How university students self-regulate their online learning during the COVID-19 pandemic. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2021.642593
Brooker, A., Corrin, L., de Barba, P., Lodge, J., & Kennedy, G. (2018). A tale of two MOOCs: How student motivation and participation predict learning outcomes in different MOOCs. Australasian Journal of Educational Technology, 34(1), 73–87. https://doi.org/10.14742/ajet.3237
Brooks, C. F., & Young, S. L. (2015). Emotion in online college classrooms: Examining the influence of perceived teacher communication behavior on students’ emotional experiences. Technology, Pedagogy and Education, 24(4), 515–527. https://doi.org/10.1080/1475939X.2014.995215
Chen, C., Elliot, A. J., & Sheldon, K. M. (2019). Psychological need support as a predictor of intrinsic and external motivation: The mediational role of achievement goals. Educational Psychology, 39(8), 1090–1113. https://doi.org/10.1080/01443410.2019.1618442
Chen, K. C., & Jang, S. J. (2010). Motivation in online learning: Testing a model of self-determination theory. Computers in Human Behavior, 26(4), 741–752. https://doi.org/10.1016/j.chb.2010.01.011
Chiu, T. K. F. (2021). Applying the self-determination theory (SDT) to explain student engagement in online learning during the COVID-19 pandemic. Journal of Research on Technology in Education, 54, S14–S30. https://doi.org/10.1080/15391523.2021.1891998
Chiu, T. K. F., Lin, T. J., & Lonka, K. (2021). Motivating online learning: The challenges of COVID-19 and beyond. Asia-Pacific Education Researcher, 30(3), 187–190. https://doi.org/10.1007/s40299-021-00566-w
De Barba, P. G., Kennedy, G. E., & Ainley, M. D. (2016). The role of students’ motivation and participation in predicting performance in a MOOC. Journal of Computer Assisted Learning, 32(3), 218–231. https://doi.org/10.1111/jcal.12130
Dhawan, S. (2020). Online learning: A panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems, 49(1), 5–22. https://doi.org/10.1177/0047239520934018
Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: A general analytical framework using moderated path analysis. Psychological Methods, 12(1), 1–22. https://doi.org/10.1037/1082-989X.12.1.1
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74(1), 59–109. https://doi.org/10.3102/00346543074001059
Fryer, L. K., & Bovee, H. N. (2021). Teaching for course interest. Studies in Higher Education, 46(11), 2122–2133. https://doi.org/10.1080/03075079.2020.1712692
Gagné, M. (2003). The role of autonomy support and autonomy orientation in prosocial behavior engagement. Motivation and Emotion, 27(3), 199–223. https://doi.org/10.1023/A:1025007614869
Goldman, Z. W., & Goodboy, A. K. (2014). Making students feel better: Examining the relationships between teacher confirmation and college students’ emotional outcomes. Communication Education, 63(3), 259–277. https://doi.org/10.1080/03634523.2014.920091
Goldman, Z. W., Goodboy, A. K., & Weber, K. (2017). College students’ psychological needs and intrinsic motivation to learn: An examination of self-determination theory. Communication Quarterly, 65(2), 167–191. https://doi.org/10.1080/01463373.2016.1215338
Hayes, A. F. (2009). Beyond Baron and Kenny: Statistical mediation analysis in the new millennium. Communication monographs, 76(4), 408–420. https://doi.org/10.1080/03637750903310360
Hodges, C., Moore, S., Lockee, B., Trust, T., & Bond, A. (2020, March 27). The difference between emergency remote teaching and online learning. EDUCAUSE Review. Retrieved October 7, 2022, from https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning
Holzer, J., Lüftenegger, M., Korlat, S., Pelikan, E., Salmela-Aro, K., Spiel, C., & Schober, B. (2021). Higher education in times of COVID-19: University students’ basic need satisfaction, self-regulated learning, and well-being. AERA Open, 7, 1–13. https://doi.org/10.1177/23328584211003164
Hsu, H. C. K., Wang, C. V., & Levesque-Bristol, C. (2019). Reexamining the impact of self-determination theory on learning outcomes in the online learning environment. Education and Information Technologies, 24(3), 2159–2174. https://doi.org/10.1007/s10639-019-09863-w
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
Huang, Y., & Wang, S. Y. (2022a). How to motivate student engagement in emergency online learning? Evidence from the COVID-19 situation. Higher education, 1–23. https://doi.org/10.1007/s10734-022-00880-2
Huang, Y. T., & Wang, Y. (2022b). Research on the influencing mechanism of undergraduates’ learning engagement in blended teaching during the COVID-19: Based on the perspective of the community of inquiry. Chinese Higher Education, 3, 52–59. (in Chinese)
Jiang, L., & Yu, S. (2021). Understanding changes in EFL teachers’ feedback practice during COVID-19: Implications for teacher feedback literacy at a time of crisis. Asia-Pacific Education Researcher, 30(6), 509–518. https://doi.org/10.1007/s40299-021-00583-9
Juan, L. N., & Jaime, L. (2019). Determinants of classroom engagement: A prospective test based on self-determination theory. Teachers and Teaching, 25(2), 147–159. https://doi.org/10.1080/13540602.2018.1542297
Ladyshewsky, Richard K. (2013). Instructor presence in online courses and student satisfaction. International Journal for the Scholarship of Teaching and Learning, 7(1), 1–23. https://doi.org/10.20429/ijsotl.2013.070113
Lang, J. W. B., & Fries, S. (2006). A revised 10-item version of the achievement motives scale. European Journal of Psychological Assessment, 22(3), 216–224. https://doi.org/10.1027/1015-5759.22.3.216
Leenknecht, M., Wijnia, L., Loyens, S. M., & Rikers, R. (2017). Need-supportive teaching in higher education: Configurations of autonomy support, structure, and involvement. Teaching and Teacher Education, 68, 134–142. https://doi.org/10.1016/j.tate.2017.08.020
Liew, T. W., Zin, N. A. M., & Sahari, N. (2017). Exploring the affective, motivational and cognitive effects of pedagogical agent enthusiasm in a multimedia learning environment. Human-Centric Computing and Information Sciences, 7(1), 1–21. https://doi.org/10.1186/s13673-017-0089-2
Lin, T. J. (2021). Exploring the differences in Taiwanese university students’ online learning task value, goal orientation, and self-efficacy before and after the COVID-19 outbreak. Asia-Pacific Education Researcher, 30(3), 191–203. https://doi.org/10.1007/s40299-021-00553-1
Linnenbrink, E. A., & Pintrich, P. R. (2002). Motivation as an enabler for academic success. School Psychology Review, 31(3), 313–327. https://doi.org/10.1080/02796015.2002.12086158
Marinoni, G., & Land, H.V. (2020, May 27). The impact of COVID-19 on higher education around the world. IAU Global Survey report. Retrieved October 15, 2022, from https://www.iauaiu.net/IMG/pdf/iau_covid19_ and_he_survey_report_final_may_2020.pdf
McGrath, C.H., Guerin, B., Harte, E.C., Frearson, M., & Manville, C. (2015). Learning Gain in Higher Education. International Perspectives on Higher Education Research. Santa Monica, CA: RAND Corporation. Retrieved October 15, 2022, from https://www.rand.org/pubs/research_reports/RR996.html
Mega, C., Ronconi, L., & De Beni, R. (2014). What makes a good student? How emotions, self-regulated learning, and motivation contribute to academic achievement. Journal of Educational Psychology, 106(1), 121–131. https://doi.org/10.1037/a0033546
Ministry of Education. (2021, December 17). National report on the teaching quality of undergraduate education in general universities (Year 2020). Retrieved October 15, 2022, from http://www.moe.gov.cn/jyb_xwfb/gzdt_gzdt/s5987/202112/t20211217_588017.html
Niemiec, C. P., & Ryan, R. M. (2009). Autonomy, competence, and relatedness in the classroom: Applying self-determination theory to educational practice. Theory and Research in Education, 7(2), 133–144. https://doi.org/10.1177/1477878509104318
Ntoumanis, N., Ng, J. Y., Prestwich, A., et al. (2020). A meta-analysis of self-determination theory-informed intervention studies in the health domain: Effects on motivation, health behavior, physical, and psychological health. Health Psychology Review, 15(2), 214–244. https://doi.org/10.1080/17437199.2020.1718529
O’Sullivan, P. B., Hunt, S. K., & Lippert, L. R. (2004). Mediated immediacy: A language of affiliation in a technological age. Journal of Language and Social Psychology, 23(4), 464–490. https://doi.org/10.1177/0261927X04269588
Patall, E. A., & Zambrano, J. (2019). Facilitating student outcomes by supporting autonomy: Implications for practice and policy. Policy Insights from the Behavioral and Brain Sciences, 6(2), 115–122. https://doi.org/10.1177/2372732219862572
Pianta, R. C., Belsky, J., Vandergrift, N., Houts, R., & Morrison, F. J. (2008). Classroom effects on children’s achievement trajectories in elementary school. American Educational Research Journal, 45(2), 365–397. https://doi.org/10.3102/0002831207308230
Pianta, R. C., Hamre, B. K., Hayes, N., et al. (2011). Classroom assessment scoring system—Secondary (CLASS-S). University of Virginia.
Rapanta, C., Botturi, L., Goodyear, P., et al. (2020). Online university teaching during and after the COVID-19 crisis: Refocusing teacher presence and learning activity. Postdigital Science and Education, 2, 923–945. https://doi.org/10.1007/s42438-020-00155-y
Reeve, J. (2002). Self-determination theory applied to education settings. In E. L. Deci & R. M. Ryan (Eds.), Handbook of self-determination research (pp. 183–203). University of Rochester Press.
Reyes, M. R., Brackett, M. A., Rivers, S. E., et al. (2012). Classroom emotional climate, student engagement, and academic achievement. Journal of Educational Psychology, 104(3), 700–712. https://doi.org/10.1037/a0027268
Ryan, R. M., & Deci, E. L. (2017). Self-determination theory Basic psychological needs in motivation, development and wellness (p. 503). The Guilford Press.
Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions. Contemporary Educational Psychology, 61, 101860. https://doi.org/10.1016/j.cedpsych.2020.101860
Schunk, D. H., Meece, J. L., & Pintrich, P. R. (2014). Motivation in education: Theory research and applications (4th ed.). Pearson.
Seifert, T. L. (2004). Understanding student motivation. Educational Research, 46(2), 137–149. https://doi.org/10.1080/0013188042000222421
Shi, Q. H., & Guo, J. P. (2012). An empirical study on college students’ learning situation and influence mechanism in China. Educational Research, 2, 109–121.
UNESCO. (2020a, April 23). COVID-19 impact on education. Retrieved October 20, 2022, from https://en.unesco.org/covid19/educationresponse
UNESCO. (2020b, April 23). Nurturing the social and emotional wellbeing of children and young people during crises. UNESCO COVID-19 Education Response. Retrieved October 20, 2022, from https://unesdoc.unesco.org/ark:/48223/pf0000373271
Wang, M. T., & Eccles, J. S. (2013). School context, achievement motivation, and academic engagement: A longitudinal study of school engagement using a multidimensional perspective. Learning and Instruction, 28, 12–23. https://doi.org/10.1016/j.learninstruc.2013.04.002
Yang, B., & Huang, C. (2021). Turn crisis into opportunity in response to COVID-19: Experience from a Chinese university and future prospects. Studies in Higher Education, 46(1), 121–132. https://doi.org/10.1080/03075079.2020.1859687
Yu, S., & Xu, H. (2021). Feedback and assessment in second language education during the COVID-19 and beyond. Asia-Pacific Education Researcher, 30(6), 483–486. https://doi.org/10.1007/s40299-021-00631-4
Zhou, X., Chai, C. S., Jong, M. S., & Xiong, X. B. (2021). Does relatedness matter for online self-regulated learning to promote perceived learning gains and satisfaction? Asia-Pacific Education Researcher, 30(3), 205–215. https://doi.org/10.1007/s40299-021-00579-5
Funding
Zhejiang Provincial Philosophy and Social Science Planning Project, 23NDJC074YB.
Author information
Authors and Affiliations
Contributions
Removed for peer review.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that there are no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendix
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Shao, X., Chen, R., Wang, Y. et al. The Predictive Effect of Teachers’ Emotional Support on Chinese Undergraduate Students’ Online Learning Gains: An Examination of Self-determination Theory. Asia-Pacific Edu Res 33, 571–585 (2024). https://doi.org/10.1007/s40299-023-00754-w
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40299-023-00754-w