Changes and Adaptations: How University Students Self-Regulate Their Online Learning During the COVID-19 Pandemic
Open accessAbstract
During the COVID-19 (coronavirus disease 2019) pandemic, universities had to shift from face-to-face to emergency remote education. Students were forced to study online, with limited access to facilities and less contact with peers and teachers, while at the same time being exposed to more autonomy. This study examined how students adapted to emergency remote learning, specifically focusing on students’ resource-management strategies using an individual differences approach. One thousand eight hundred university students completed a questionnaire on their resource-management strategies and indicators of (un)successful adaptation to emergency remote learning. On average, students reported being less able to regulate their attention, effort, and time and less motivated compared to the situation before the crisis started; they also reported investing more time and effort in their self-study. Using a k -means cluster analysis, we identified four adaptation profiles and labeled them according to the reported changes in their resource-management strategies: the overwhelmed, the surrenderers, the maintainers, and the adapters. Both the overwhelmed and surrenderers appeared to be less able to regulate their effort, attention, and time and reported to be less motivated to study than before the crisis. In contrast, the adapters appreciated the increased level of autonomy and were better able to self-regulate their learning. The resource-management strategies of the maintainers remained relatively stable. Students’ responses to open-answer questions on their educational experience, coded using a thematic analysis, were consistent with the quantitative profiles. Implications about how to support students in adapting to online learning are discussed.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Practicing desirably difficult strategies should benefit everyone, both learners who want to master a subject and learners whose main aim is to achieve a sufficient grade to pass a course as efficiently as possible.
“Importantly, practicing desirably difficult strategies should benefit everyone , both learners who want to master a certain subject and learners whose main aim is to achieve a sufficient grade to pass a course as efficiently as possible.”
From Worth the Effort: the Start and Stick to Desirable Difficulties (S2D2) Framework (2023) · cites this paper as Biwer et al., 2021
The Introduction discusses associations between resource-management strategies and academic performance, while the Discussion describes different student adaptation profiles. Neither section addresses desirably difficult strategies or whether practicing them benefits both mastery-focused learners and learners seeking an efficient passing grade; searches for those terms found no supporting passage. The available passages have no page numbers. (LLM, conf=0.70)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003) · Department of Psychology - University of Koblenz-Landau · doi:10.23668/psycharchives.12784 · Cited by 8,975 · see citing works
Becoming a Self-Regulated Learner: An Overview
Zimmerman, B. J. (2002) · Theory Into Practice · doi:10.1207/s15430421tip4102_2 · Cited by 7,305 · cited 1× · see citing works
“They need to plan, monitor, and control their own learning process during self-study and thus engage in selfregulated learning (Nelson and Narrens, 1990; Zimmerman, 2002).”
BackgroundRichardson, M., Abraham, C., & Bond, R. (2012) · Psychological Bulletin · doi:10.1037/a0026838 · Cited by 3,646 · see citing works
A Review of Self-regulated Learning: Six Models and Four Directions for Research
Panadero, E. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00422 · Cited by 2,915 · cited 1× · see citing works
“Three main categories of learning strategies can be differentiated in self-regulated learning: cognitive, metacognitive, and resource-management strategies (Duncan and McKeachie, 2005; Panadero, 2017).”
BackgroundEffects of COVID-19 on College Students’ Mental Health in the United States: Interview Survey Study
Son, C., Hegde, S., Smith, A., Wang, X., & Sasangohar, F. (2020) · Journal of Medical Internet Research · doi:10.2196/21279 · Cited by 2,822 · see citing works
Broadbent, J., & Poon, W. L. (2015) · The Internet and Higher Education · doi:10.1016/j.iheduc.2015.04.007 · Cited by 1,692 · see citing works
Efklides, A. (2011) · Educational Psychologist · doi:10.1080/00461520.2011.538645 · Cited by 1,211 · see citing works
Motivational profiles from a self-determination perspective: The quality of motivation matters.
Vansteenkiste, M., Sierens, E., Soenens, B., Luyckx, K., & Lens, W. (2009) · Journal of Educational Psychology · doi:10.1037/a0015083 · Cited by 1,074 · cited 2× · see citing works
“The optimal number of clusters was selected based on the explained variance, parsimony, and interpretability of the solution (Vansteenkiste et al., 2009; Kusurkar et al., 2020).”
BackgroundMethodMega, C., Ronconi, L., & De Beni, R. (2014) · Journal of Educational Psychology · doi:10.1037/a0033546 · Cited by 1,007 · see citing works
Comparing online and blended learner's self-regulated learning strategies and academic performance
Broadbent, J. (2017) · The Internet and Higher Education · doi:10.1016/j.iheduc.2017.01.004 · Cited by 679 · see citing works
Changing circumstances, disrupting habits.
Wood, W., Tam, L., & Witt, M. G. (2005) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.88.6.918 · Cited by 678 · see citing works
Hsu, H.-C. K., Wang, C. V., & Levesque-Bristol, C. (2019) · Education and Information Technologies · doi:10.1007/s10639-019-09863-w · Cited by 349 · see citing works
Why do i keep interrupting myself?: environment, habit and self-interruption
Dabbish, L., Mark, G., & González, V. M. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979405 · Cited by 132 · see citing works
Flagged first, then by citations
Research works printed but not linked: 26
- Barnard L. Lan W. Y. To Y. M. Paton V. O. Lai S.-L. (2009). Measuring self-regulation in online and blended learning environments. Internet High. Educ. 12 1– 6. 10.1016/j.iheduc.2008.10.005 · DOI
- Barnard-Brak L. Lan W. Paton V. (2010). Profiles in self-regulated learning in the online learning environment. Intern. Rev. Res. Open Distan. Learn. 11 61– 80. 10.19173/irrodl.v11i1.769 · DOI
- Boekaerts M. Niemivirta M. (2000). “ Self-regulated learning: finding a balance between learning goals and ego-protective goals,” in Handbook of Self-Regulation, eds Boekaerts M. Pintrich P. R. Zeidner M. (Cambridge, MA: Academic Press), 417– 450.
- Broadbent J. Fuller-Tyszkiewicz M. (2018). Profiles in self-regulated learning and their correlates for online and blended learning students. Educ. Technol. Res. Dev. 66 1435– 1455. 10.1007/s11423-018-9595-9 · DOI
- Dolmans D. H. De Grave W. Wolfhagen I. H. van der Vleuten C. P. (2005). Problem-based learning: future challenges for educational practice and research. Med. Educ. 39 732– 741. 10.1111/j.1365-2929.2005.02205.x 15960794 · DOI
- Dörrenbächer L. Perels F. (2016). Self-regulated learning profiles in college students: their relationship to achievement, personality, and the effectiveness of an intervention to foster self-regulated learning. Learn. Individ. Differ. 51 229– 241. 10.1016/j.lindif.2016.09.015 · DOI
- Dresel M. Schmitz B. Schober B. Spiel C. Ziegler A. Engelschalk T. (2015). Competencies for successful self-regulated learning in higher education: structural model and indications drawn from expert interviews. Stud. High. Educ. 40 454– 470. 10.1080/03075079.2015.1004236 · DOI
- Duncan T. G. McKeachie W. J. (2005). The making of the motivated strategies for learning questionnaire. Educ. Psychol. 40 117– 128. 10.1207/s15326985ep4002_6 26627889 · DOI · Paper page
- Green J. K. Burrow M. S. Carvalho L. (2020). Designing for transition: supporting teachers and students cope with emergency remote education. Postdigit. Sci. Educ. 2 906– 922. 10.1007/s42438-020-00185-6 PMC7443393 40477144 · DOI
- Jansen R. S. van Leeuwen A. Janssen J. Kester L. Kalz M. (2017). Validation of the self-regulated online learning questionnaire. J. Comput. High. Educ. 29 6– 27. 10.1007/s12528-016-9125-x · DOI
- Kebritchi M. Lipschuetz A. Santiague L. (2017). Issues and challenges for teaching successful online courses in higher education: a literature review. J. Educ. Technol. Syst. 46 4– 29. 10.1177/0047239516661713 · DOI · Paper page
- King N. (2004). “ Using templates in the thematic analysis of text,” in Essential Guide to Qualitative Methods in Organizational Research, eds Cassell C. Symon G. (Thousand Oaks, CA: SAGE Publications Ltd), 256– 270. 10.4135/9781446280119.n21 · DOI
- Kitsantas A. Winsler A. Huie F. (2008). Self-regulation and ability predictors of academic success during college: a predictive validity study. J. Adv. Acad. 20 42– 68. 10.4219/jaa-2008-867 · DOI
- Kline R. B. (2005). “ Hypothesis testing,” in Principles and Practice of Structural Equation Modeling, 3rd Edn, eds Kenny D. A. Little T. D. (New York, NY: The Guilford Press), 189– 229.
- Kusurkar R. A. Mak-van der Vossen M. Kors J. Grijpma J.-W. van der Burgt S. M. E. Koster A. S. (2020). ‘One size does not fit all’: the value of person-centred analysis in health professions education research. Perspect. Med. Educ. 10.1007/s40037-020-00633-w 33284407 PMC8368141 · DOI
- Laursen B. Hoff E. (2006). Person-centered and variable-centered approaches to longitudinal data. Merrill Palm. Q. 52: 377. 10.1353/mpq.2006.0029 · DOI
- Lehmann T. Hähnlein I. Ifenthaler D. (2014). Cognitive, metacognitive and motivational perspectives on preflection in self-regulated online learning. Comput. Hum. Behav. 32 313– 323. 10.1016/j.chb.2013.07.051 · DOI
- Marsh H. W. Balla J. R. McDonald R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: the effect of sample size. Psychol. Bull. 103 391– 410. 10.1037/0033-2909.103.3.391 · DOI
- Nelson T. O. Narrens L. (1990). Metamemory: a theoretical framework and new findings. Psychol. Learn. Motiv. 26 125– 173. 10.1016/s0079-7421(08)60053-5 · DOI · Paper page
- Nordmann E. Horlin C. Hutchison J. Murray J.-A. Robson L. Seery M. K. (2020). Ten simple rules for supporting a temporary online pivot in higher education. PLoS Comput. Biol. 16: e1008242. 10.1371/journal.pcbi.1008242 33001990 PMC7529278 · DOI
- Pintrich P. R. (2000). “ The role of goal orientation in self-regulated learning,” in Handbook of Self-Regulation, eds Boekaerts M. Pintrich P. R. Zeidner M. (Cambridge, MA: Academic Press), 451– 502. 10.1016/b978-012109890-2/50043-3 · DOI · Paper page
- Puzziferro M. (2008). Online technologies self-efficacy and self-regulated learning as predictors of final grade and satisfaction in college-level online courses. Am. J. Distan. Educ. 22 72– 89. 10.1080/08923640802039024 · DOI
- Rasheed R. A. Kamsin A. Abdullah N. A. (2020). Challenges in the online component of blended learning: a systematic review. Comput. Educ. 144: 103701. 10.1016/j.compedu.2019.103701 · DOI · Paper page
- Stone A. A. Shiffman S. (2002). Capturing momentary, self-report data: a proposal for reporting guidelines. Ann. Behav. Med. 24 236– 243. 10.1207/S15324796ABM2403_09 12173681 · DOI · Paper page
- Usher E. L. Schunk D. H. (2018). “ Social cognitive theoretical perspective of self-regulation,” in Handbook of Self-Regulation of Learning and Performance, 2nd Edn, eds Schunk D. H. Greene J. A. (New York, NY: Taylor & Francis Group), 19– 35. 10.4324/9781315697048-2 · DOI
- van Rooij E. C. M. Jansen E. P. W. A. van de Grift W. J. C. M. (2018). First-year university students’ academic success: the importance of academic adjustment. Eur. J. Psychol. Educ. 33 749– 767. 10.1007/s10212-017-0347-8 · DOI · Paper page
Cited by
Sorted by citations
Worth the Effort: the Start and Stick to Desirable Difficulties (S2D2) Framework
de Bruin, A. B. H., Biwer, F., Hui, L., Onan, E., David, L., & Wiradhany, W. (2023) · Educational Psychology Review · doi:10.1007/s10648-023-09766-w · Cited by 79 · see citing works
“This benefit stems from the fact that for both types of learners, learning will take effort (Biwer et al., 2021).”
BackgroundSelf-citationDaşcı, E., Salihoğlu, K., & Daşcı, E. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1272205 · Cited by 16 · see citing works
- Authors
- Biwer, F., Wiradhany, W., oude Egbrink, M., Hospers, H., Wasenitz, S., Jansen, W., & de Bruin, A.
- Affiliations
- Maastricht University (NL)
- Binus University (ID)
- Corresponding author
- Biwer, Felicitas
- Venue
- Frontiers in Psychology
- Publisher
- Frontiers Media SA
- Published
- 2021-04-23
- Volume
- 12
- Pages
- 642593-642593
- ISSN
- 1664-1078 (ISSN-L)
- PMC
- PMC8103204
- OpenAlex
- W3161724086
- Cited by
- 226
- References
- 13
- Citations by year
- 2026: 15 · 2025: 23 · 2024: 49 · 2023: 62 · 2022: 60 · 2021: 17
- FWCI
- 82.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Psychology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Topics
- Social Sciences › Education › Education during COVID-19 pandemic
- Social Sciences › Education › E-Learning and COVID-19
- Social Sciences › Psychology › Developmental and Educational Psychology › Student Stress and Coping
- Keywords
- emergency remote teaching, COVID-19 pandemic, student self-regulation, resource management strategies, student motivation, student independence, university students, attentional control, time management, effort regulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review