The DOI matches its Crossref record; 44 of the 45 references it cites were found in a registry or an index.
Influence of COVID-19 confinement on students’ performance in higher education
Open accessAbstract
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.
Overview
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
Verification
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?
In the citing paper
“Our results then seem to confirm, at a larger scale, those of Gonzalez et al. (2020) in a different university in Madrid.”
From Emergency remote teaching and students’ academic performance in higher education during the COVID-19 pandemic: A case study (2021) · cites this paper as Gonzalez et al., 2020
In the citing paper
“As mentioned in Section 6, while counter-intuitive, this result confirms, across a larger number of courses, the findings of Gonzalez et al. (2020) in a very similar albeit smaller context.”
From Emergency remote teaching and students’ academic performance in higher education during the COVID-19 pandemic: A case study (2021) · cites this paper as Gonzalez et al. (2020)
In the citing paper
“At the university level, in a single university, for 458 students in STEM faculties, learning outcomes actually improved (Gonzalez et al., 2020).”
From Learning loss during Covid-19: An early systematic review (2022) · cites this paper as Gonzalez et al. (2020)
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other
Mann, H. B., & Whitney, D. R. (1947) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177730491 · Cited by 14,320 · cited 1×
“Means were compared by a Kruskal-Wallis test [46] and, when differences were found, by a Mann-Whitney post hoc test [47] to determine which pairs of means were different.”
MethodUse of Ranks in One-Criterion Variance Analysis
Kruskal, W. H., & Wallis, W. A. (1952) · Journal of the American Statistical Association · doi:10.1080/01621459.1952.10483441 · Cited by 13,912 · cited 1×
“Means were compared by a Kruskal-Wallis test [46] and, when differences were found, by a Mann-Whitney post hoc test [47] to determine which pairs of means were different.”
MethodZimmerman, B. J. (2008) · American Educational Research Journal · doi:10.3102/0002831207312909 · Cited by 3,735 · cited 1×
“Related to autonomous learning, many studies have been performed regarding the concept of self-regulated learning (SRL), in which students are active and responsible for their own learning process [18, 19] as well as being knowledgeable, self-aware and able to select their own approach to learning [20, 21].”
BackgroundFundamentals of item response theory
(1992) · Choice Reviews Online · doi:10.5860/choice.29-4185 · Cited by 3,420
Zimmerman, B. J., & Martinez-Pons, M. (1990) · Journal of Educational Psychology · doi:10.1037/0022-0663.82.1.51 · Cited by 1,825 · cited 1×
“Related to autonomous learning, many studies have been performed regarding the concept of self-regulated learning (SRL), in which students are active and responsible for their own learning process [18, 19] as well as being knowledgeable, self-aware and able to select their own approach to learning [20, 21].”
BackgroundComputerized Adaptive Testing: A Primer
Wainer, H., Dorans, N. J., Flaugher, R. L., Green, B. F., & Mislevy, R. J. (1990) · Medical Entomology and Zoology · Cited by 1,169
La evaluación online en la educación superior en tiempos de la COVID-19
García‐Peñalvo, F. J., Corell, A., García, V. A., & de Prado, M. G. (2020) · Education in the Knowledge Society (EKS) · doi:10.14201/eks.23086 · Cited by 866
The MOOC model for digital practice
McAuley, A. B. T., Stewart, B. E., Siemens, G., & Cormier, D. (2010) · Cited by 698
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
Wainer, H., Dorans, N. J., Flaugher, R. L., Green, B. F., & Mislevy, R. J. (2000) · Routledge eBooks · doi:10.4324/9781410605931 · Cited by 659
Campus traffic and e-Learning during COVID-19 pandemic
Favale, T., Soro, F., Trevisan, M., Drago, I., & Mellia, M. (2020) · Computer Networks · doi:10.1016/j.comnet.2020.107290 · Cited by 618 · cited 1×
“In [15], we can see that the most popular remote collaboration tools are private chat messages, followed by two-participant-calls, multiperson-meetings, and team chat messages.”
BackgroundTests for departure from normality. Empirical results for the distributions of b2 and √b1
D’Agostino, R. B., & Pearson, E. S. (1973) · Biometrika · doi:10.1093/biomet/60.3.613 · Cited by 607
The metacognitive control components of self-regulated learning
Corno, L. (1986) · Contemporary Educational Psychology · doi:10.1016/0361-476x(86)90029-9 · Cited by 417 · cited 1×
“Related to autonomous learning, many studies have been performed regarding the concept of self-regulated learning (SRL), in which students are active and responsible for their own learning process [18, 19] as well as being knowledgeable, self-aware and able to select their own approach to learning [20, 21].”
BackgroundTracking e-learning through published papers: A systematic review
Rodrigues, H., Almeida, F., Figueiredo, V., & Lopes, S. L. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.03.007 · Cited by 399 · cited 1×
“Fortunately, there is a range of modern tools available to face the challenge of distance learning imposed by the COVID-19 pandemic [3].”
BackgroundTests for Departure from Normality. Empirical Results for the Distributions of b 2 and √b 1
D’Agostino, R. B., & Pearson, E. S. (1973) · Biometrika · doi:10.2307/2335012 · Cited by 363
Zimmerman, B. J., & Kitsantas, A. (2014) · Contemporary Educational Psychology · doi:10.1016/j.cedpsych.2014.03.004 · Cited by 342 · cited 1×
“Related to autonomous learning, many studies have been performed regarding the concept of self-regulated learning (SRL), in which students are active and responsible for their own learning process [18, 19] as well as being knowledgeable, self-aware and able to select their own approach to learning [20, 21].”
BackgroundMaldonado‐Mahauad, J., Pérez‐Sanagustín, M., Kizilcec, R. F., Morales, N., & Muñoz-Gama, J. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.11.011 · Cited by 338
Exploring feedback and student characteristics relevant for personalizing feedback strategies
Narciss, S., Sosnovsky, S., Schnaubert, L., Andrès, E., Eichelmann, A., Goguadze, G., & Melis, E. (2014) · Computers & Education · doi:10.1016/j.compedu.2013.09.011 · Cited by 260 · cited 1×
“More advanced CAT platforms use personalization to individual learner ́s characteristics by adapting questions and providing tailored feedback [32].”
BackgroundÖzyurt, Ö., & Özyurt, H. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2015.06.020 · Cited by 191 · cited 1×
“These studies and the development of adequate tools for evaluation and self-evaluation of learners have become especially necessary in the COVID-19 pandemic in order to guarantee good performance in e-learning environments [27].”
MethodPanadero, E., Broadbent, J., Boud, D., & Lodge, J. M. (2019) · European Journal of Psychology of Education · doi:10.1007/s10212-018-0407-8 · Cited by 190
Theorizing and researching levels of processing in self‐regulated learning
Winne, P. H. (2017) · British Journal of Educational Psychology · doi:10.1111/bjep.12173 · Cited by 186
Ebner, M., Schön, S., Braun, C., Ebner, M., Grigoriadis, Y., Haas, M., Leitner, P., & Taraghi, B. (2020) · Future Internet · doi:10.3390/fi12060094 · Cited by 166
Complexity leadership in learning analytics: Drivers, challenges and opportunities
Tsai, Y., Poquet, O., Gašević, D., Dawson, S., & Pardo, A. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12846 · Cited by 162 · cited 1×
“In recent years, many studies have been performed analyzing the advantages and challenges of massive data analysis in higher education [11].”
BackgroundWang, T. (2011) · Computers & Education · doi:10.1016/j.compedu.2011.01.003 · Cited by 159
Predictive power of regularity of pre-class activities in a flipped classroom
Jovanović, J., Mirriahi, N., Gašević, D., Dawson, S., & Pardo, A. (2019) · Computers & Education · doi:10.1016/j.compedu.2019.02.011 · Cited by 157 · cited 2×
“Jovanovic et al also demonstrated that assisting students in their management of learning resources is critical for a correct management of their learning strategies in terms of regularity [13].”
BackgroundAnalytics of time management strategies in a flipped classroom
Ahmad Uzir, N., Gašević, D., Matcha, W., Jovanović, J., & Pardo, A. (2020) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12392 · Cited by 129 · cited 2×
“An increase in the students’ performance due to adequate time management in the learning process is well-established in the literature [12, 13].”
BackgroundA comparative analysis of forums and wikis as tools for online collaborative learning
Biasutti, M. (2017) · Computers & Education · doi:10.1016/j.compedu.2017.04.006 · Cited by 115 · cited 2×
“E-learning has experienced significant change due to the exponential growth of the internet and information technology [4].”
BackgroundBellhäuser, H., Lösch, T., Winter, C., & Schmitz, B. (2016) · The Internet and Higher Education · doi:10.1016/j.iheduc.2016.07.002 · Cited by 109
Using Response Times to Detect Aberrant Responses in Computerized Adaptive Testing
van der Linden, W. J., & van Krimpen-Stoop, E. M. L. A. (2003) · Psychometrika · doi:10.1007/bf02294800 · Cited by 106 · cited 1×
“CAT allows dynamic changes for each test item based on previous answers of the student [31].”
MethodMartin, A. J., & Lazendic, G. (2017) · Journal of Educational Psychology · doi:10.1037/edu0000205 · Cited by 93 · cited 1×
“Some platforms couple the advantages of CAT-specific feedback with multistage adaptive testing [38].”
Designing videogames to improve students' motivation
Molins-Ruano, P., Sevilla, C., Santini, S., Haya, P. A., Rodrı́guez, P., & Sacha, G. M. (2013) · Computers in Human Behavior · doi:10.1016/j.chb.2013.06.013 · Cited by 91
Self-citationInvestigating variation in learning processes in a FutureLearn MOOC
Rizvi, S., Rienties, B., Rogaten, J., & Kizilcec, R. F. (2019) · Journal of Computing in Higher Education · doi:10.1007/s12528-019-09231-0 · Cited by 71 · cited 1×
“Even courses that solely offer online contents such as Massive Open Online Courses (MOOCs) [6, 7] have also become popular.”
BackgroundLu, H. S., Hu, Y.-P., Gao, J.-J., & Kinshuk, K. (2016) · Computers & Education · doi:10.1016/j.compedu.2016.04.012 · Cited by 60 · cited 1×
“Over the decades, different systems and approaches based on CAT have been used in the educational space to enhance the learning process [39, 40].”
MethodAssessment of collaborative learning experiences by graphical analysis of wiki contributions
Palomo‐Duarte, M., Dodero, J. M., Medina‐Bulo, I., Posada, E. J. R., & Ruiz‐Rube, I. (2012) · Interactive Learning Environments · doi:10.1080/10494820.2012.680969 · Cited by 32
Strategies for controlling testlet exposure rates in computerized adaptive testing systems
Boyd, A., & Dodd, B. G. (2003) · Texas ScholarWorks (Texas Digital Library) · Cited by 28
Adaptive Model for Computer-Assisted Assessment in Programming SkillsPreprint
Molins-Ruano, P., González-Sacristán, C., Díez, F., Rodrı́guez, P., & Sacha, G. M. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1403.1465 · Cited by 26
Self-citationModelling experts' behavior with e-valUAM to measure computer science skills
Molins-Ruano, P., Rodrı́guez, P., Atrio, S., & Sacha, G. M. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.03.044 · Cited by 25 · cited 1×
“This solution is unfeasible in most cases, since most of the CAT models already require more items than comparable linear testing [43].”
Self-citationE -learning during Covid 19 Pandemic.Preprint
Gohiya, P., & Gohiya, A. (2020) · doi:10.21203/rs.3.rs-29575/v1 · Cited by 22
Castro-Schez, J. J., Redondo, M. Á., Jurado, F., & Albusac, J. A. (2013) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2013.10.011 · Cited by 16
Teamwork assessment in collaborative projects through process mining techniques
Caballero-Hernández, J. A., Balderas, A., Palomo‐Duarte, M., Dellatorre, P., Reinoso, A. J., & Dodero, J. M. (2020) · International journal of engineering education · Cited by 13
An ensemble approach in converging contents of LMS and KMS
Sabitha, A. S., Mehrotra, D., & Bansal, A. (2016) · Education and Information Technologies · doi:10.1007/s10639-016-9516-7 · Cited by 12
Stochastic programming for individualized test assembly with mixture response time models
Veldkamp, B. P., Avetisyan, M., Weissman, A., & Fox, J. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.04.060 · Cited by 11 · cited 15×
“2.1.1 CAT theoretical model.”
BackgroundInfluentialAdaptive tests as a tool for evaluating work groups in engineering
la Rubia, M. A. D., & Sacha, G. M. (2020) · International journal of engineering education · Cited by 5
Self-citationTeamwork Assessment in Collaborative Projects Through Process Mining Techniques
Caballero-Hernández, J. A., Balderas Alberico, A., Palomo Duarte, M., de la Torre Moreno, P., Reinoso, A. J., & Dodero, J. M. (2020) · Dialnet (Universidad de la Rioja) · doi:10.5281/zenodo.21714859 · Cited by 2
Flagged first, then by citations
1 of the 45 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- FJ García-Peñalvo, 2020, Online Assessment in Higher Education in the Time of COVID-19, Education in the Knowledge Society, 21, 12
- FM Lord, 1980, Applications of item response theory to practical problems
Cited by
Sorted by citations
College students’ use and acceptance of emergency online learning due to COVID-19
Patricia Aguilera-Hermida, A. (2020) · International Journal of Educational Research Open · doi:10.1016/j.ijedro.2020.100011 · Cited by 1,286
Kapasia, N., Paul, P., Roy, A., Saha, J., Zaveri, A., Mallick, R., Barman, B., Das, P., & Chouhan, P. (2020) · Children and Youth Services Review · doi:10.1016/j.childyouth.2020.105194 · Cited by 845
Barrot, J. S., Llenares, I. I., & del Rosario, L. S. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10589-x · Cited by 764
Iglesias-Pradas, S., Hernández-García, Á., Chaparro-Peláez, J., & Prieto, J. L. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106713 · Cited by 693
“As mentioned in Section 6, while counterintuitive, this result confirms, across a larger number of courses, the findings of Gonzalez et al. (2020) in a very similar albeit smaller context.”
ResultTurnbull, D., Chugh, R., & Luck, J. (2021) · Education and Information Technologies · doi:10.1007/s10639-021-10633-w · Cited by 529
Metadata
- 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.
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2020-10-09
- Volume
- 15
- Issue
- 10
- Pages
- e0239490
- ISSN
- 1932-6203 (ISSN-L)
- 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
- 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
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
