Assessing university students’ study-related burnout and academic well-being in digital learning environments
A systematic literature review
Keywords:Digital learning environment, Digital assessment, Academic well-being, Study-related burnout, Systematic literature review
Previous research suggested a strong connection between students’ experiences of traditional learning environments and study-related burnout (Brown et al., 2012; Chen et al., 2017; Meriläinen, 2014; Kuittinen & Meriläinen, 2014). However, digital learning environments and how they can pedagogically support students’ well-being remain, in many respects, an unexplored area (Ruokamo et al., 2016; Lewin & Lundie, 2016). Moreover, pedagogical assessment, including how it can support students’ academic well-being, often lags behind the latest technological developments (Spector, 2014; Popenici & Kerr, 2017; Bates et al., 2020; Holmes et al., 2019; Luckin et al., 2016).
This research systematically reviews the literature relevant to study-related burnout and academic well-being in digital learning environments. It is done by surveying articles published between 2012 and 2021. First, the findings suggest that there is a body of studies focusing on certain dimensions of study-related burnout. Second, students’ well-being in digital learning environments is less studied and relies mostly on emotional achievement theory and research on academic emotions. Finally, supporting students’ academic well-being through digital assessment is mostly enabled through formative assessment, but it is moving toward artificial intelligence and game-based assessment. Thus, more research is needed on the subject.
Asikainen, H., Salmela-Aro, K., Parpala, A., & Katajavuori, N. (2020). Learning profiles and their relation to study-related burnout and academic achievement among university students. Learning and Individual Differences, 78, 101781. https://doi.org/10.1016/j.lindif.2019.101781
Arity, V., & Vesty, G. (2020). Designing authentic assessments: Engaging business students in flow experience with digital technologies. In T. McLaughlin, A. Chester, B. Kennedy & S. Young (Eds.), Tertiary education in a time of change (pp. 21–38). Springer Singapore. https://doi.org/10.1007/978-981-15-5883-2_3
Bates, T., Cobo, C., Mariño, O., & Wheeler, S. (2020). Can artificial intelligence transform higher education? Int J Educ Technol High Educ, 17, 42 (2020). https://doi.org/10.1186/s41239-020-00218-x
Bhagat, S., & Kim, D. J. (2020). Higher education amidst COVID-19: Challenges and silver lining. Information Systems Management, 37(4), 366–371. https://doi.org/10.1080/10580530.2020.1824040
Biggs, J. (2003). Aligning teaching and assessing to course objectives. Teaching and Learning in Higher Education: New Trends and Innovations, 2(4), 13–17.
Boada-Grau, J., Merino-Tejedor, E., Sánchez-García, J. C., Prizmic-Kuzmica, A. J., & Vigil-Colet, A. (2015). Adaptation and psychometric properties of the SBI-U scale for Academic Burnout in university students. Anales de Psicología/Annals of Psychology, 31(1), 290–297. https://doi.org/10.6018/analesps.31.1.168581
Boelens, R., De Wever, B., & Voet, M. (2017). Four key challenges to the design of blended learning: A systematic literature review. Educational Research Review, 22, 1–18. https://doi.org/10.1016/j.edurev.2017.06.001
Boud, D. & Falchikov, N. (2006). Aligning assessment with long-term learning. Assessment & Evaluation in Higher Education, 31(4), 399–413. https://doi.org/10.1080/02602930600679050
Brown, G. T., Harris, L. R., & Harnett, J. (2012). Teacher beliefs about feedback within an assessment for learning environment: Endorsement of improved learning over student well-being. Teaching and Teacher Education, 28(7), 968–978. https://doi.org/10.1016/j.tate.2012.05.003
Cai, S., Liu, E., Yang, Y., & Liang, J. C. (2019). Tablet‐based AR technology: Impacts on students’ conceptions and approaches to learning mathematics according to their self‐efficacy. British Journal of Educational Technology, 50(1), 248–263. https://doi.org/10.1111/bjet.12718
Chen, C., Fan, J., & Jury, M. (2017). Are perceived learning environments related to subjective well-being? A visit to university students. Learning and Individual Differences, 54, 226–233. https://doi.org/10.1016/j.lindif.2017.01.001
Creswell, J. (2018). Research design: Qualitative, quantitative, and mixed methods approaches. Sage Publications.
Davies, R. (2016). Ceaselessly exploring: Interactions in mobile mediated online learning. Studies in Philosophy and Education, 35, 235–240. https://doi.org/10.1007/s11217-016-9515-6
Ellis, R. A., & Goodyear, P. (2013). Student experiences of e-learning in higher education: The ecology of sustainable innovation. Routledge. https://doi.org/10.4324/9780203872970
Entwistle, N. (2000). Approaches to studying and levels of understanding: The influences of teaching and assessment. Higher Education, 15, 156—218.
Entwistle, N., McCune, V., & Hounsell, J. (2002). Approaches to studying and perceptions of university teaching-learning environments: Concepts, measures and preliminary findings. Enhancing Teaching and Learning Environments in Undergraduate Courses Occasional Report 1. 1—19. https://www.researchgate.net/profile/Noel-Entwistle/publication/313443807_Approaches_to_Studying_and_Perceptions_of_University_Teaching-Learning_EnvironmentsConcepts_Measures_and_Preliminary_Findings/links/589af522aca2721f0db24d1e/Approaches-to-Studying-and-Perceptions-of-University-Teaching-Learning-EnvironmentsConcepts-Measures-and-Preliminary-Findings.pdf
Entwistle, N. J., McCune, V., & Hounsell, J. (2003). Investigating ways of enhancing university teaching-learning environments: Measuring students’ approaches to studying and perceptions of teaching. In E. De Corte, L. Verschaffel, N. J. Entwistle, & J. van Merrienboer (Eds.), Unravelling basic components and dimensions of powerful learning environments (pp. 89–107). Elsevier Science.
Fiorilli, C., De Stasio, S., Di Chiacchio, C., Pepe, A., & Salmela-Aro, K. (2017). School burnout, depressive symptoms and engagement: Their combined effect on student achievement. International Journal of Educational Research, 84, 1–12. https://doi.org/10.1016/j.ijer.2017.04.001Get
Hailikari, T., Tuononen, T., & Parpala, A. (2018). Students’ experiences of the factors affecting their study progress: Differences in study profiles. Journal of Further and Higher Education, 42(1), 1–12. https://doi.org/10.1080/0309877X.2016.1188898
Hart, C. (1998). Doing a literature review. Releasing the social science research imagination. Sage Publications Ltd.
Harvey, L. (2003). Student feedback. Quality in Higher Education, 9(1), 3–20. https://doi.org/10.1080/13538320308164
Heckel, C., & Ringeisen, T. (2019). Pride and anxiety in online learning environments: Achievement emotions as mediators between learners’ characteristics and learning outcomes. Journal of Computer Assisted Learning, 35(5), 667—677. https://doi.org/10.1111/jcal.12367
Herrmann, K., Bager-Elsborg, A., & Parpala, A. (2016). Measuring perceptions of the learning environment and approaches to learning: Validation of the learn questionnaire. Scandinavian Journal of Educational Research, 5, 526—539. https://doi.org/10.1080/00313831.2016.1172497
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, 106789. https://doi.org/10.1016/j.chb.2021.106789
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education. Center for Curriculum Redesign. https://doi.org/10.1007/978-3-319-60013-0_107-1
Kankaraš, M., & Suarez-Alvarez, J. (2019). Assessment framework of the OECD study on social and emotional skills. OECD Education Working Papers, 207. OECD Publishing. https://doi.org/10.1787/5007adef-en
Kim, Y. J., & Rosenheck, L. (2020). Reimagining assessment through play: A case study of MetaRubric. In M. Bearman, P. Dawson, R. Ajjawi, J. Tai & D. Boud (Eds.), Re-imagining university assessment in a digital world, (pp. 263–276). Springer. https://doi.org/10.1007/978-3-030-41956-1_18
Kuittinen, M., & Meriläinen, M. (2014). The effect of study‐related burnout on student perceptions. Journal of International Education in Business, 4(1), 42—62. https://doi.org/10.1108/18363261111170586
Kümmel, E., Moskaliuk, J., Cress, U., & Kimmerle, J. (2020). Digital learning environments in higher education: A literature review of the role of individual vs. social settings for measuring learning outcomes. Education Sciences, 10(3), 1—19. https://doi.org/10.3390/educsci10030078
Lajoie, S. P., Pekrun, R., Azevedo, R., & Leighton, J. P. (2020). Understanding and measuring emotions in technology-rich learning environments. Learning and Instruction, 70, 101272. https://doi.org/10.1016/j.learninstruc.2019.101272
Lewin, D., & Lundie, D. (2016). Philosophies of digital pedagogy. Studies in Philosophy and Education, 35(3), 235—240. https://doi.org/10.1007/s11217-016-9514-7
Luckin, R. (2017). Towards artificial intelligence-based assessment systems. Nature Human Behaviour, 1(3), 0028. https://doi.org/10.1038/s41562-016-0028
Luckin, R. (2018). Machine learning and human intelligence: The future of education for the 21st century. UCL IOE Press.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
Mattsson, M., Hailikari, T., & Parpala, A. (2020). All happy emotions are alike but every unhappy emotion is unhappy in its own way: A network perspective to academic emotions. Frontiers in Psychology, 11(742), 1–18. https://doi.org/10.3389/fpsyg.2020.00742
Meriläinen, M. (2014). Factors affecting study-related burnout among Finnish university students: Teaching-learning environment, achievement motivation and the meaning of life. Quality in Higher Education, 20(3), 309–329. https://doi.org/10.1080/13538322.2014.978136
Meriläinen, M., & Kuittinen, M. (2014). The relation between Finnish university students’ perceived level of study-related burnout, perceptions of the teaching–learning environment and perceived achievement motivation. Pastoral Care in Education, 32(3), 186–196. https://doi.org/10.1080/02643944.2014.893009
Nieminen, J. H., & Tuohilampi, L. (2020). ‘Finally studying for myself’–examining student agency in summative and formative self-assessment models. Assessment & Evaluation in Higher Education, 45(7), 1031–1045. https://doi.org/10.1080/02602938.2020.1720595
Nieminen, J. H., Asikainen, H., & Rämö, J. (2021). Promoting deep approach to learning and self-efficacy by changing the purpose of self-assessment: A comparison of summative and formative models. Studies in Higher Education, 46(7), 1296–1311. https://doi.org/10.1080/03075079.2019.1688282
OECD. (2021). Building the future of education. https://www.oecd.org/education/
Panadero, E., Brown, G. T., & Strijbos. J. W. (2016). The future of student self-assessment: A review of known unknowns and potential directions. Educational Psychology Review 28(4), 803–830. https://doi.org/10.1007/s10648-015-9350-2
Parpala, A., Lindblom‐Ylänne, S., Komulainen, E., Litmanen, T., & Hirsto, L. (2010). Students’ approaches to learning and their experiences of the teaching–learning environment in different disciplines. British Journal of Educational Psychology, 80(2), 269–282. https://doi.org/10.1348/000709909X476946
Parpala, A., & Lindblom-Ylänne, S. (2012). Using a research instrument for developing quality at the university. Quality in Higher Education, 18(3), 313–328. https://doi.org/10.1080/13538322.2012.733493
Parpala, A., Lindblom-Ylänne, S., Komulainen, E., & Entwistle, N. (2013). Assessing students’ experiences of teaching–learning environments and approaches to learning: Validation of a questionnaire in different countries and varying contexts. Learning Environments Research, 16(2), 201–215. https://doi.org/10.1007/s10984-013-9128-8
Parpala, A., Katajavuori, N., Haarala-Muhonen, A., & Asikainen, H. (2021). How did students with different learning profiles experience ‘normal’ and online teaching situation during COVID-19 spring? Social Sciences, 10(9), 337. https://doi.org/10.3390/socsci10090337
Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2010). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist, 37(2), 91–105. https://doi.org/10.1207/S15326985EP3702_4
Popenici, S. A., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 1–13. https://doi.org/10.1186/s41039-017-0062-8
Postareff, L., Mattsson, M., Lindblom-Ylänne, S. & Hailikari, T. (2017). The complex relationship between emotions, approaches to learning, study success and study progress during the transition to university. Higher Education, 73, 441–457. https://doi.org/10.1007/s10734-016-0096-7
Rasi, P., Vuojärvi, H., & Ruokamo, H. (2019). Media literacy education for all ages. Journal of Media Literacy Education, 11(2), 1–19. https://doi.org/10.23860/JMLE-2019-11-2-1
Reisoğlu, I., Topu, B., Yılmaz, R., Yılmaz, T. K., & Göktaş, Y. (2017). 3D virtual learning environments in education: A meta-review. Asia Pacific Education Review, 18(1), 81–100. https://doi.org/10.1007/s12564-016-9467-0
Richardson, J. T. E. (2005). Instruments for obtaining student feedback: A review of the literature. Assessment & Evaluation in Higher Education, 30(4), 387–415. https://doi.org/10.1080/02602930500099193
Ruokamo, H. M. A., Kotilainen, S., Kupiainen, R., & Maasilta, M. (2016). Media education today and tomorrow. Finnish Society on Media Education.
Ryan, T. (2020). Effective feedback in digital learning environments. Melbourne CSHE discussion paper. Melbourne Centre for the Study of Higher Education. https://melbourne-cshe.unimelb.edu.au/__data/assets/pdf_file/0004/3417079/effective-feedback-in-digital-learning-environments_final.pdf
Sawyer, R. K. (2017). Teaching creativity in art and design studio classes: A systematic literature review. Educational Research Review, 22, 99–113. https://doi.org/10.1016/j.edurev.2017.07.002
Salmela-Aro, K., Kiuru, N., Leskinen, E., & Nurmi, J. E. (2009). School burnout inventory (SBI) reliability and validity. European Journal of Psychological Assessment, 25(1), 48–57. https://doi.org/10.1027/1015-57188.8.131.52
Salmela-Aro, K., & Kunttu, K. (2010). Study burnout and engagement in higher education. Unterrichtswissenschaft: Zeitschrift für Lernforschung, 38(4), 322–337.
Salmela-Aro, K., & Read, S. (2017). Study engagement and burnout profiles among Finnish higher education students. Burnout Research, 7, 21–28. https://doi.org/10.1016/j.burn.2017.11.001
Salmela-Aro, K., & Upadyaya, K. (2020). School engagement and school burnout profiles during high school–The role of socio-emotional skills. European Journal of Developmental Psychology, 17(6), 943–964. https://doi.org/10.1080/17405629.2020.1785860
Seibert, G. S., Ross, W. M., Fitzgerald, M. C., &. Fincham, F. D. (2016). Understanding school burnout: Does self-control matter? Learning and Individual Differences, 49, 120–127. https://doi.org/10.1016/j.lindif.2016.05.024
Sargent, J., & Lynch, S. (2021). ‘None of my other teachers know my face/emotions/thoughts’: Digital technology and democratic assessment practices in higher education physical education. Technology, Pedagogy and Education, 30(5), 693—705. https://doi.org/10.1080/1475939X.2021.1942972
Schaufeli, W. B., Desart, S., & De Witte, H. (2020). Burnout assessment tool (BAT)—development, validity, and reliability. International Journal of Environmental Research and Public Health, 17(24), 9495. https://doi.org/10.3390/ijerph17249495
Schiff, D. (2021). Out of the laboratory and into the classroom: The future of artificial intelligence in education. AI & Society, 36(1), 331–348. https://doi.org/10.1007/s00146-020-01033-8
Shen, C. W., & Ho, J. T. (2020). Technology-enhanced learning in higher education: A bibliometric analysis with latent semantic approach. Computers in Human Behavior, 104, 106177. https://doi.org/10.1016/j.chb.2019.106177
Spector, J. M. (2014). Conceptualizing the emerging field of smart learning environments. Smart Learning Environments, 1(1), 2 (2014). https://doi.org/10.1186/s40561-014-0002-7
Srivastava, N., Velloso, E., Lodge, J. M., Erfani, S., & Bailey, J. (2019). Continuous evaluation of video lectures from real-time difficulty self-report. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 586, 1–12. https://doi.org/10.1145/3290605.3300816
Subhash, S., & Cudney, E. A. (2018). Gamified learning in higher education: A systematic review of the literature. Computers in Human Behavior, 87, 192–206. https://doi.org/10.1016/j.chb.2018.05.028
Tan, K. (2007). Conceptions of self-assessment: What is needed for long term learning? In D. Boud & N. Falchikov (Eds.), Rethinking assessment in higher education: Learning for the longer term (pp. 114–127). Routledge.
Tan, K. H. (2009). Meanings and practices of power in academics’ conceptions of student self-assessment. Teaching in Higher Education, 14(4), 361–373. https://doi.org/10.1080/13562510903050111
Tempelaar, D. T., Niculescu, A., Rienties, B., Gijselaers, W. H., & Giesbers, B. (2012). How achievement emotions impact students’ decisions for online learning, and what precedes those emotions. The Internet and Higher Education, 15(3), 161–169. https://doi.org/10.1016/j.iheduc.2011.10.003
Tempelaar, D. (2020). Supporting the less-adaptive student: The role of learning analytics, formative assessment and blended learning. Assessment & Evaluation in Higher Education, 45(4), 579–593. https://doi.org/10.1080/02602938.2019.1677855
Thompson, P. (2013). The digital natives as learners: Technology use patterns and approaches to learning. Computers & Education, 65, 12–33. https://doi.org/10.1016/j.compedu.2012.12.022
Troussas, C., Krouska, A., & Sgouropoulou, C. (2020). Collaboration and fuzzy-modeled personalization for mobile game-based learning in higher education. Computers & Education, 144, 103698. https://doi.org/10.1016/j.compedu.2019.103698
Tzafilkou, K., & Economides, A. A. (2021). Mobile game-based learning in distance education: A mixed analysis of learners’ emotions and gaming features. In P. Zaphiris & A. Ioannou, (Eds.), Learning and Collaboration Technologies: Games and Virtual Environments for Learning (pp. 115–132). Springer International Publishing. https://doi.org/10.1007/978-3-030-77943-6_8
United Nations. (2015). Transforming our world: The 2030 agenda for sustainable development. https://www.un.org/ga/search/view_doc.asp?symbol=A/RES/70/1&Lang=E
Väisänen, S., Pietarinen, J., Pyhältö, K., Toom, A., & Soini, T. (2018). Student teachers’ proactive strategies for avoiding study-related burnout during teacher education. European Journal of Teacher Education, 41(3), 301–317. https://doi.org/10.1080/02619768.2018.1448777
Väätäjä, J. O., & Ruokamo, H. (2021). Conceptualizing dimensions and a model for digital pedagogy. Journal of Pacific Rim Psychology, 15, 1834490921995395. https://doi.org/10.1177/1834490921995395
Yang, H., & Chen, J. (2016). Learning perfectionism and learning burnout in a primary school student sample: A test of a learning-stress mediation model. Journal of Child and Family Studies, 25(1), 345–353. https://doi.org/10.1007/s10826-015-0213-8
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
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39 (2019). https://doi.org/10.1186/s41239-019-0171-0
How to Cite
Copyright (c) 2022 Katri Koivuneva, Heli Ruokamo
This work is licensed under a Creative Commons Attribution 4.0 International License.
Seminar.net is a fully open access journal, which means that all articles are available on the internet to all users immediately upon publication. Non-commercial use and distribution in any medium is permitted, provided the author and the journal are properly credited. The journal allow reuse and remixing of content in accordance with a Creative Commons license CC BY
- The journal allows the author(s) to hold the copyright without restrictions.
- The journal allows the author(s) to retain publishing rights without restrictions.
- Seminar.net does not charge authors for publishing with us.