Cited by 744Education during COVID-19 pandemicEducational Outcomes and InfluencesE-Learning and COVID-19

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Influence of COVID-19 confinement on students’ performance in higher education

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Gonzalez, T., de la Rubia, M. A., Hincz, K. P., Comas-Lopez, M., Subirats, Laia, Fort, Santi, Sacha, G. M.·2020·PLOS ONE

DOI 10.1371/journal.pone.0239490PMC PMC7546684

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Abstract

This study analyzes the effects of COVID-19 confinement on the autonomous learning performance of students in higher education. Using a field experiment with 458 students from three different subjects at Universidad Autónoma de Madrid (Spain), we study the differences in assessments by dividing students into two groups. The first group (control) corresponds to academic years 2017/2018 and 2018/2019. The second group (experimental) corresponds to students from 2019/2020, which is the group of students that had their face-to-face activities interrupted because of the confinement. The results show that there is a significant positive effect of the COVID-19 confinement on students' performance. This effect is also significant in activities that did not change their format when performed after the confinement. We find that this effect is significant both in subjects that increased the number of assessment activities and subjects that did not change the student workload. Additionally, an analysis of students' learning strategies before confinement shows that students did not study on a continuous basis. Based on these results, we conclude that COVID-19 confinement changed students' learning strategies to a more continuous habit, improving their efficiency. For these reasons, better scores in students' assessment are expected due to COVID-19 confinement that can be explained by an improvement in their learning performance.

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Fig 1 Representation of the CAT model. Green arrows indicate the path students take when they answer a question correctly. Students follow red arrows when an incorrect answer is given. Grades are represented at the bottom of the figure, improving with each step to the right.CC BY · PubMed Central

Fig 2 Scheme of the strategy followed to accurately measure the autonomous work of students and the influence of rewards.CC BY · PubMed Central

Fig 3 Description of the experiment.CC BY · PubMed Central

Fig 4 Distribution of self-evaluation activities in “Applied Computing”. (a) Individual scores of all the students in the academic year 2017/2018 (ordered chronologically). Each dot corresponds to a single attempt of a student. (b) Number of attempts in the academic year 2017/2018 distributed in time periods. Inset shows the distribution in the days between May 16 and May 21.CC BY · PubMed Central

Fig 5 Distribution of attempts in the self-evaluation/learning phase in “Design of Water Treatment Facilities”. The horizontal axis corresponds to the dates and the vertical axis to the grades obtained in every individual attempt. The attempts made by all students in the 3 stages are presented.CC BY · PubMed Central

Fig 6 Attempts vs. scores ordered chronologically for the three academic years under study in “Applied Computing”.CC BY · PubMed Central

Fig 7 Students’ scores in the face-to-face period (before confinement) and in the distance teaching period (during confinement). Data is presented for the 3 academic courses (2017/2018 and 2018/2019 being the control group and 2019/2020 the experimental group) as mean±SD. Symbols indicate statistically significant differences (p<0.05) between course 2019/2020 and 2017/2018 (*), 2019/2020 and 2018/2019 (#) or between the period before and after the confinement during the same course (¶).CC BY · PubMed Central

Fig 8 Results of students enrolled in Metabolism during the last 3 academic years. (a) The score obtained by students in the different activities of the continuous assessment is represented. (b) Proportion of students that passed the continuous assessment activities (score≥5). (c) Proportion of students that did not carry out the continuous assessment activities. From the 11 activities, only 2 are in-person activities under normal conditions (number 5 and 9, highlighted with a box), the other activities were always on-line. The end of in-person teaching and beginning of confinement is indicated with a red arrow. Data is presented as mean±SD. Symbols indicate statistically significant differences (p<0.05) between courses 2017/2018 and 2018/2019 (§), 2017/2018 and 2019/2020 (*) and 2018/2019 and 2019/2020 (#).CC BY · PubMed Central

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KORONAVİRÜS KAPANMA (KISITLAMA) DÖNEMİNDE ÜNİVERSİTE ÖĞRENCİLERİNİN YORGUNLUK DÜZEYİ VE KAS-İSKELET SİSTEMİ RAHATSIZLIKLARI ARASINDAKİ İLİŞKİNİN BAZI DEĞİŞKENLER AÇISINDAN İNCELENMESİ
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Authors: Gonzalez, T., de la Rubia, M. A., Hincz, K. P., Comas-Lopez, M., Subirats, L., Fort, S., & Sacha, G. M.
Affiliations: Universidad Autónoma de Madrid (ES)
Universitat Oberta de Catalunya (ES)
EURECAT Centre Tecnològic de Catalunya (ES)
Corresponding author: Sacha, G. M.
ORCID: Subirats, Laia
Fort, Santi
Sacha, G. M.
Venue: PLOS ONE
Publisher: Public Library of Science (PLoS)
Published: 2020-10-09
Volume: 15
Issue: 10
Pages: e0239490
ISSN: 1932-6203 (ISSN-L)
DOI: 10.1371/journal.pone.0239490
PMC: PMC7546684
OpenAlex: W3091995338
Cited by: 743
References: 45
Citations by year: 2026: 23 · 2025: 52 · 2024: 71 · 2023: 142 · 2022: 203 · 2021: 230 · 2020: 22
FWCI: 226.20
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
Locations: PLoS ONE (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Hispana (submittedVersion)
Biblos-e Archivo (Universidad Autónoma de Madrid) (submittedVersion, public-domain)
Funders: Erasmus+ Program (2017-1-ES01-KA203-038266)
Topics: Social Sciences › Education › Education during COVID-19 pandemic
Social Sciences › Education › Educational Outcomes and Influences
Social Sciences › Education › E-Learning and COVID-19
Keywords: COVID-19 lockdown, university students, student performance, self-directed learning, learning strategies, assessment performance, student workload, Universidad Autónoma de Madrid
MeSH terms: Betacoronavirus, COVID-19, SARS-CoV-2, Adult, Educational Measurement, Female, Humans, Male, Models, Theoretical, Pneumonia, Viral, Spain, Students, Medical, Coronavirus Infections, Education, Distance, Young Adult, Pandemics

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Influence of COVID-19 confinement on students’ performance in higher education

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