research report on covid 19 for students

SYSTEMATIC REVIEW article

Effects of covid-19-related school closures on student achievement-a systematic review.

• 1 Goethe University Frankfurt, Frankfurt, Germany
• 2 Center for Educational Measurement, Faculty of Educational Sciences, University of Oslo, Oslo, Norway

The COVID-19 pandemic led to numerous governments deciding to close schools for several weeks in spring 2020. Empirical evidence on the impact of COVID-19-related school closures on academic achievement is only just emerging. The present work aimed to provide a first systematic overview of evidence-based studies on general and differential effects of COVID-19-related school closures in spring 2020 on student achievement in primary and secondary education. Results indicate a negative effect of school closures on student achievement, specifically in younger students and students from families with low socioeconomic status. Moreover, certain measures can be identified that might mitigate these negative effects. The findings are discussed in the context of their possible consequences for national educational policies when facing future school closures.

Introduction

In spring 2020, the COVID-19 pandemic caused severe disruption to everyday life around the world. As one of several measures taken to prevent the spread of the virus, many governments closed schools for several weeks or months. Although school closures are considered to be one of the most efficient interventions to curb the spread of the virus ( Haug et al., 2020 ), many educators and researchers raised concerns about the effects of COVID-19-related school closures on student academic achievement and learning inequalities. For instance, Woessmann (2020) estimated a negative effect of 0.10 SD on student achievement due to COVID-19-related school closures. Moreover, Haeck and Lefebvre (2020) estimated that socioeconomic achievement gaps would increase by up to 30%.

The negative effects of school closures due to summer vacation or natural disasters, and of absenteeism on student achievement are already well documented in the literature (for an overview see Kuhfeld et al., 2020a ). Less is known, however, about the impact of COVID-19-related school closures on student achievement. The primary focus of the literature on COVID-19-related school closures to date was on the reception and use of digital learning technologies and remote learning ( Andrew et al., 2020 ; Grewenig et al., 2020 ; Maity et al., 2020 ; Pensiero et al., 2020 ; Blume et al., 2021 ). Moreover, the psychological impact of COVID-19-related school closures, the use of school counseling in connection with COVID-19 ( O'Connor, 2020 ; Xie et al., 2020 ; Ehrler et al., 2021 ; Gadermann et al., 2021 ; O'Sullivan et al., 2021 ), and the effects of the school closures on student motivation ( Zaccoletti et al., 2020 ; Smith et al., 2021 ) were investigated. Existing projections of the impact of COVID-19 on student achievement paint quite a bleak picture. A learning loss of up to 38 points on the Programme for International Student Assessment (PISA 1 ) scale is estimated, which corresponds to an effect size (Cohen's d ) of 0.38 or 0.9 school years ( Azevedo et al., 2020 ; Kuhfeld et al., 2020a ; Wyse et al., 2020 ; Kaffenberger, 2021 ).

Thus, a year into the pandemic, it is a good time for a first stocktaking of the actual, evidence-based impact of COVID-19-related school closures on student achievement. Consequently, the present work aimed to answer two research questions. First, what was the general effect of COVID-19-related school closures in spring 2020 on student achievement in primary and secondary education? Second, did school closures have differential effects on specific student groups?

The review is organized following the reporting guidelines of the PRISMA statement ( Page et al., 2021 ) and structured as follows. We first illustrate our systematic literature search, the inclusion criteria, the risk of bias assessment, and the synthesis of the relevant information from the studies selected. We then report the general and differential effects of the COVID-19-related school closures on student achievement, which are discussed in the context of their possible consequences for future national educational policies.

Literature Search

To identify relevant studies that investigated the effect of COVID-19-related school closures on student achievement, we searched the Web of Science database for articles published between March 1, 2020 and April 30, 2021. We used the following keywords and search string: [Covid OR Corona OR “SARS-CoV-2” AND school AND learn* OR “test score” OR performance OR competenc* OR achievement OR grades]. The results were refined by using the following categories: education, educational research, economics, education scientific disciplines, psychology educational, psychology multidisciplinary, social sciences interdisciplinary, and education special. The indexes searched were SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH, BKCI-S, BKCI-SSH, ESCI, CCR-EXPANDED, and IC. Because the COVID-19 pandemic was still ongoing at the time this review was written, and the field of research on the effects of COVID-19-related school closures on student achievement is rapidly evolving, we additionally searched the preprint servers PsyArXiv, EdArXiv, and SocArXiv using the aforementioned keywords. With this initial literature search, we obtained 601 potentially relevant studies. After selecting relevant articles out of these studies, we used the backward reference searching method (i.e., examining the works cited in the selected articles) to identify additional potentially relevant studies. See Figure 1 for a PRISMA flowchart of the literature search process.

Figure 1 . PRISMA flowchart of the literature search and screening process.

Selection of Studies

The abstracts of the studies selected were carefully read by the authors, and further inclusion was decided based on the following initial criteria. The studies (1) had to have a clear focus on COVID-19-related school closures, they (2) had to focus on primary and secondary education, and they (3) had to have student achievement (or test scores) as the dependent variable. This initial selection left 109 studies for potential inclusion in the review. These studies were thoroughly read by the authors and two research assistants. We carefully assessed the quality of included studies and based the decision to include studies in the review on the following primary set of inclusion criteria: Studies were required (1) to have collected actual data prior to and during/after COVID-19-related school closures, and (2) to have applied statistical analyses and to report an effect size. This set of inclusion criteria was chosen in order to select studies that provided the aforementioned evidence-based insights. Thus, reviews or discussions on how COVID-19 affects educational processes were excluded. Likewise, exploratory analyses or simple surveys (where only percentages were reported) were also excluded. For example, Chadwick and McLoughlin (2021) investigated the impact of COVID-19 related school closures on student's science learning. However, they only questioned teachers on the impact of COVID-19 related school closures on teaching, learning, and assessment. Because the study did not meet the inclusion criteria of having collected actual data on student achievement, including a comparison of data prior to and during/after COVID-19-related school closures, and applying statistical analyses rather than solely reporting percentages, the study was excluded from the systematic review. Similarly, studies by Haeck and Lefebvre (2020) , Kaffenberger (2021) , and Kuhfeld et al. (2020a) were excluded from the systematic review because they reported predicted effects of COVID-19 related school closures on student achievement but did not collect actual data prior to and during/after COVID-19-related school closures.

To determine the degree of rater agreement on the selection of the studies, a randomly selected subset of 20 studies was evaluated by both the authors and the research assistants. Any remaining divergent evaluations were highlighted in the evaluation forms and subsequently discussed. The second selection procedure yielded nine studies that were suitable for inclusion in the review. Subsequently, a backward search of references within the nine selected studies yielded two additional studies, which were then also included in the review.

Risk of Bias Assessment

The Cochrane Risk Assessment of the included studies was conducted independently by the first and second author using the “Risk Of Bias in Non-Randomized Studies of Interventions” tool (ROBINS-I; Sterne et al., 2016 ). The result of the risk assessment is summarized in Figure 2 . Taken together, the highest risk of bias is due to the lack of inclusion of potential confounding variables (Domain 1). Most studies, however, included at least a few relevant controls. Bias due to selection of participants was unlikely as the groups were formed naturally. Similarly, where applicable, interventions were classified correctly. Except for Clark et al. (2020) , no information could be obtained about deviations from intended interventions. This is because the COVID-19 related school closures were not intended interventions. Thus, although there is no information, the risk due to deviations from intended interventions was deemed low. Lastly, bias due to missing data, measurement of outcomes, or selection of reported results is unlikely, as most studies exhibited very small proportions of missing data (except Depping et al., 2021 ), and were highly transparent in their reporting of the results (except, partially, van der Velde et al., 2021 , who only report significant mean differences between groups in sufficient detail). Depping et al. (2021) , however, thoroughly discuss and provide convincing reasons for assuming that missing data does not substantially influence their results.

Figure 2 . Result of the cochrane risk of bias assessment.

We synthesized the eleven studies by extracting the following information that was relevant for our research questions: (1) country, (2) duration of school closure, (3) sample description (type of school and sample size), (4) subjects for which student achievement was investigated, (5) statistical method, (6) general effects of the COVID-19-related school closures on student achievement, and (7) differential effects as reported by subgroup analyses (see Table 1 for a detailed list of the studies included). The focal piece of information was the reported general and differential effects. Where possible, general effects reported in different metrics (e.g., percentile scores), were converted to changes in SD . We then calculated the median of the reported effects, for the overall general effect, as well as for the general effect on reading and mathematics. In light of the relatively small number of studies, random- or even mixed-effects meta-analytic models were not feasible.

Table 1 . Descriptive criteria of studies included.

General Effects of COVID-19-Related School Closures on Student Achievement

The studies on the effect of COVID-19-related school closures on student achievement selected for our review reported mixed findings, with effects ranging from−0.37 SD to +0.25 SD ( Mdn = −0.08 SD ). Most studies found negative effects of COVID-19 related school closures on student achievement. Seven studies reported a negative effect on mathematics ( Clark et al., 2020 ; Kuhfeld et al., 2020b ; Maldonado and De Witte, 2020 ; Tomasik et al., 2020 ; Depping et al., 2021 ; Engzell et al., 2021 ; Schult et al., 2021 ), five studies on reading ( Clark et al., 2020 ; Maldonado and De Witte, 2020 ; Tomasik et al., 2020 ; Engzell et al., 2021 ; Schult et al., 2021 ), and two studies on other subjects, such as science ( Maldonado and De Witte, 2020 ; Engzell et al., 2021 ). This is in line with expected learning losses due to COVID-19 related school closures and the assumption that, in spring 2020, the ad hoc implementation of online teaching gave students, teachers, schools, and parents little time to prepare for or adapt to measures of remote learning.

Three studies reported positive effects of COVID-19 related school closures on student achievement. Meeter (2021) and Spitzer and Musslick (2021) showed students to improve their mathematics achievement when learning with an online-learning software during the COVID-related school closures. Similarly, van der Velde et al. (2021) reported an increase in correct solutions on open questions within a French learning program. Interestingly, these three studies focused on online-learning software. Thus, the positive effects may be explained by the students under investigation being familiar working with the corresponding online-learning software prior to school closures. Hence, they did not have to adapt to a new learning environment when in-person teaching was interrupted due to COVID-19. Moreover, students increased the time using the online-learning software at home, were less distracted or experienced less time pressure in a home-schooling rather than classroom setting, or were presented with individualized assignments within the online program (see also Meeter, 2021 ; Spitzer and Musslick, 2021 ; van der Velde et al., 2021 ).

Additionally, two studies found positive effects on student achievement in mathematics and reading ( Gore et al., 2021 ), or in reading only ( Depping et al., 2021 ). This result might be accounted for by the achievement measurement being timed some months after school closures in both studies and the possibility of effective compensatory measures being implemented by teachers, schools, and local policy makers during this time to counteract learning losses, such as offering learning groups during summer vacation in parts of Germany ( Depping et al., 2021 ).

Even though the median for the effect on mathematics and reading is comparable when averaging above all studies ( d = −0.10 SD and−0.09 SD for mathematics and reading, respectively), some included studies found different effects for different subjects. On the one hand, reasons for finding larger learning losses in reading than in mathematics might be that “mathematics is easier to teach in distance learning, as it is simple to provide exercises and tests digitally or as worksheets” ( Maldonado and De Witte, 2020 , p. 13). As another explanation, many students might not speak the language in which they are tested in at home, hence, not benefitting much in their language skills during school closures (e.g., Maldonado and De Witte, 2020 ). On the other hand, reasons for finding larger learning losses in mathematics than in reading might be that students spent more time on reading during school closures and that supporting children in their reading skills might have been easier to realize for parents than supporting children in improving their competencies in mathematics (e.g., Depping et al., 2021 ; Schult et al., 2021 ).

Differential Effects on Groups of Students

The studies selected for our review reported three main differential effects of COVID-19-related school closures on student achievement in different groups of students. First, the main finding was that younger children were more negatively affected in their learning than older children were (-0.37 SD vs.−0.10 SD ; Tomasik et al., 2020 ). Second, children from families with a low socioeconomic status (SES) were more affected than children from families with a high SES were ( Maldonado and De Witte, 2020 ; Engzell et al., 2021 ). In this context, one study reported an interaction between grade and SES, that is, for younger children from schools with low school-level SES, learning losses of 0.16 SD were found, while younger children from schools with medium school-level SES experienced learning gains of 0.15 SD ( Gore et al., 2021 ). Third, low-performing students were more affected by COVID-19-related school closures in mathematics, while high-performing students were more affected by COVID-19-related school closures in reading ( Schult et al., 2021 ). Finally, low-performing students benefited more from systematic online-learning methods ( Clark et al., 2020 ; Spitzer and Musslick, 2021 ).

As the original studies were not designed to identify the reasons for these effects, additional studies are required to explain the three main differential effects exhaustively. In the following, we provide potential explanations as stated in the original studies. Regarding the first main differential effect (younger students are more affected compared to older students), Tomasik et al. (2020) state that the slower pace of students in primary school may be due to younger children relying more on cognitive scaffolding during instruction, because their capability for self-regulated learning might not be sufficiently developed. From a socio-emotional perspective, younger children might have been more sensitive to stressors related to the COVID-19 pandemic ( Tomasik et al., 2020 ).

The reasons for students from low SES families being more affected relate to access to remote learning, their learning behavior, and the support provided from families and schools. Children from families with a low SES are less likely to have access to remote learning ( UNESCO, 2021 ), are less often provided with active learning assistance from their schools ( Tomasik et al., 2020 ), and spend less time on learning ( Meeter, 2021 ) than children from families with a high SES. Moreover, parents with a high SES are more likely to provide greater psychological support for their children ( OECD, 2019 ), which seems to be specifically relevant in a situation such as the COVID-19 pandemic.

The differential effect on low-performing and high-performing students may be due to high-performing students being capable of improving their performance regardless of the learning environment, while low-performing students specifically benefit from systematic online learning ( Clark et al., 2020 ). Additionally, low-performing students might be less distracted in comparison to learning in a classroom setting ( Spitzer and Musslick, 2021 ). Finally, with the possibility to adapt the assignments in online programs individually to the students, low-performing children might have been addressed more thoroughly according to their needs ( Spitzer and Musslick, 2021 ).

The present work aimed to provide a first systematic overview of studies that reported effects of COVID-19-related school closures on student achievement and to answer two research questions. First, what was the general effect of COVID-19-related school closures in spring 2020 on student achievement in primary and secondary education? Second, did school closures have differential effects on specific student groups?

In sum, there is clear evidence for a negative effect of COVID-19-related school closures on student achievement. The reported effects are comparable in size to findings of research on summer losses ( d = −0.005 SD to −0.05 SD per week; see also Kuhfeld et al., 2020a ) and comparable to Woessmann's initial estimate. Hence, even though remote learning was implemented during COVID-19-related school closures, the effects achieved by remote learning were similar to those achieved when no teaching was implemented at all during summer vacation. Alarmingly, specifically younger children ( Tomasik et al., 2020 ) and children from families with a low SES ( Maldonado and De Witte, 2020 ; Engzell et al., 2021 ) were negatively affected by COVID-19-related school closures. This finding is in line with predictions of widening learning gaps and additive learning losses in subsequent school years ( Grewenig et al., 2020 ; Haeck and Lefebvre, 2020 ; Pensiero et al., 2020 ; Kaffenberger, 2021 ). This indicates that most remote learning measures implemented during the first school closures in spring 2020 were not effective for student learning; there was no difference between them and the absence of systematic teaching during summer vacation.

However, the present review can also identify online-learning measures that seem to be beneficial for student learning. Taking a closer look at studies that reported positive effects of school closures on student achievement, three of these studies ( Meeter, 2021 ; Spitzer and Musslick, 2021 ; van der Velde et al., 2021 ) used some kind of online-learning software to assess student achievement. Students in the studies of both Meeter (2021) and Spitzer and Musslick (2021) worked with online-learning software for mathematics, and students in the study of van der Velde et al. (2021) worked on online-learning software for language learning (i.e., for French). Hence, the positive effects of COVID-19-related school closures on performance in such online-learning programs may have occurred due to the increased use of software during school closures and the fact that students from these studies were familiar working with online-learning programs, hence, did not have to adapt to a new learning environment during COVID-19-related school closures. Additionally, Spitzer and Musslick (2021) reported that low-performing students benefited even more than high-performing students regarding their performance during COVID-19-related school closures from using the learning software. The authors explained this finding by considering that low-performing students were potentially less distracted by other students in a home-learning setting. These findings are in line with results by Clark et al. (2020) , showing low-performing students to specifically benefit from systematic online material.

The present review gives insights into the effects of the COVID-19 related school closures on student achievement in spring 2020. It has to be noted that the number of countries for which evidence of these effects are available is still small, and clustered around developed countries. Especially studies from developing countries are not available yet. We know, however, that the reduction in in-person learning was smaller for low-income countries than for medium-income countries ( UNESCO, 2021 ). Nevertheless, the proportion of students enrolled in primary or secondary education is considerably smaller in poorer countries ( Ward, 2020 ). It may be possible that studies coming from developing countries provide novel insights into the general and especially the differential effects of the COVID-19 related school closures on student achievement. The results of our systematic review can serve as a benchmark for these studies, once they emerge in the literature.

The first COVID-19-related school closures in spring 2020 were followed by similar measures in the fall and winter of 2020/2021. Due to the cumulative nature of learning processes and student achievement, additional learning losses are likely. Nevertheless, school closures do not seem to be initiated as quickly now as they were at the beginning of the pandemic, which is positive for learning. To counter the learning losses, on a micro level, educational policy makers should determine potential supportive measures that increase the active learning time on task. On a macro level, national policy makers should determine potential compensatory measures to support students in their learning and to avoid failed educational careers. In this regard, systematic online material and software have been found to compensate for learning losses, specifically in high-risk children. Hence, educational policy makers and educators should be aware of the importance of providing children with systematic material and ensuring that high-risk children, in particular, have access to adequate learning environments in order to circumvent learning losses and widening learning gaps that may be caused by subsequent school closures. We expect future studies focusing on the subsequent school closures to provide a more differentiated picture of the effects of COVID-19 related school closures on student achievement. For instance, studies may investigate whether there are differences in educational outcomes across countries with differing lockdown measures. Similarly, studies may investigate the reasons for the subject-specific general effects and the three main differential effects identified in this systematic review. Such studies require longitudinal approaches, and may provide educational policy makers with crucial additional information.

The goal of this systematic review was to provide a first evidence-based insight into the effects of COVID-19-related school closures on student achievement in primary and secondary education. The onus is now on national educational policy makers to be aware of these effects and, together with educational and psychological research fields, to work toward the implementation of measures to mitigate or even counteract these negative effects. This may be one of the most important societal tasks for the post-COVID time.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Author Contributions

SH and CK conducted the literature review and synthesis, with critical input by AF. SH wrote and revised the manuscript with contributions and feedback provided by CK, TD, and AF. All authors have been involved in the conceptual design of the review.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

1. ^ PISA is an international large-scale assessment testing the skills and knowledge of 15-year-old students in three core domains (Mathematics, Reading, and Science). Its main survey is administered every three years, with each rotating as the major domain. The results of the main surveys are scaled to fit approximately normal distributions, with means around 500 score points and standard deviations around 100 score points. A 10-point difference on the PISA scale corresponds to an effect size (Cohen's d ) of 0.10 ( OECD, 2019 ).

Andrew, A., Cattan, S., Costa-Dias, M., Farquharson, C., Kraftman, L., Krutikova, S., et al. (2020). Learning During the Lockdown: REAL-time data on Children's Experiences During Home Learning. The Institute for Fiscal Studies . Available online at: https://www.ifs.org.uk/publications/14848

Google Scholar

Azevedo, J. P., Hasan, A., Goldemberg, D., Iqbal, S. A., and Geven, K. (2020). Simulating the Potential Impacts of COVID-19 School Closures on Schooling and Learning Outcomes: A Set of Global Estimates . Washington, D.C.: The World Bank.

Blume, F., Schmidt, A., Kramer, A. C., Schmiedek, F., and Neubauer, A. B. (2021). Homeschooling during the SARS-CoV-2 pandemic: the role of students' trait self-regulation and task attributes of daily learning tasks for students' daily self-regulation. Zeitschrift für Erziehungswissenschaft 1–25. doi: 10.31234/osf.io/tnrdj

PubMed Abstract | CrossRef Full Text | Google Scholar

Chadwick, R., and McLoughlin, E. (2021). Impact of the covid-19 crisis on learning, teaching and facilitation of practical activities in science upon reopening of Irish schools. Irish Educ. Stud. 40, 197–205. doi: 10.1080/03323315.2021.1915838

CrossRef Full Text | Google Scholar

Clark, A. E., Nong, H., Zhu, H., and Zhu, R. (2020). Compensating for Academic Loss: Online Learning and Student Performance During the COVID-19 Pandemic. HAL . Available online at: https://halshs.archives-ouvertes.fr/halshs-02901505

Depping, D., Lücken, M., Musekamp, F., and Thonke, F. (2021). Kompetenzstände Hamburger Schüler * innen vor und während der Corona-Pandemie [Alternative pupils' competence measurement in Hamburg during the Corona pandemic], “in Schule während der Corona-Pandemie. Neue Ergebnisse und Überblick über ein dynamisches Forschungsfeld , eds D. Fickermann and B. Edelste (Münster: Waxmann), 51–79.

Ehrler, M., Werninger, I., Schnider, B., Eichelberger, D. A., Naef, N., Disselhoff, V., et al. (2021). Impact of the COVID-19 pandemic on children with and without risk for neurodevelopmental impairments. Acta Paediatr. 110, 1281–1288. doi: 10.1111/apa.15775

Engzell, P., Frey, A., and Verhagen, M. D. (2021). Learning loss due to school closures during the COVID-19 pandemic. SocArXiv. doi: 10.31235/osf.io/ve4z7

Gadermann, A. C., Thomson, K. C., Richardson, C. G., Gagné, M., McAuliffe, C., Hirani, S., et al. (2021). Examining the impacts of the COVID-19 pandemic on family mental health in Canada: findings from a national cross-sectional study. BMJ Open 11:e042871. doi: 10.1136/bmjopen-2020-042871

Gore, J., Fray, L., Miller, A., Harris, J., and Taggart, W. (2021). The impact of COVID-19 on student learning in New South Wales primary schools: an empirical study. Austr. Educ. Res. 1–33. doi: 10.1007/s13384-021-00436-w

Grewenig, E., Lergetporer, P., Werner, K., Woessmann, L., and Zierow, L. (2020). COVID-19 and Educational Inequality: How School Closures Affect Low-and High-Achieving Students . EconStor. Available online at: http://hdl.handle.net/10419/227347

Haeck, C., and Lefebvre, P. (2020). Pandemic school closures may increase inequality in test scores. Canad. Pub. Policy 46, S82–S87. doi: 10.3138/cpp.2020-055

Haug, N., Geyrhofer, L., Londei, A., Dervic, E., Desvars-Larrive, A., Loreto, V., et al. (2020). Ranking the effectiveness of worldwide COVID-19 government interventions. Nat. Hum. Behav. 4, 1303–1312. doi: 10.1038/s41562-020-01009-0

Kaffenberger, M. (2021). Modelling the long-run learning impact of the Covid-19 learning shock: actions to (more than) mitigate loss. Int. J. Educ. Dev. 81:102326. doi: 10.1016/j.ijedudev.2020.102326

Kuhfeld, M., Soland, J., Tarasawa, B., Johnson, A., Ruzek, E., and Liu, J. (2020a). Projecting the potential impact of COVID-19 school closures on academic achievement. Educ. Res. 49, 549–565. doi: 10.3102/0013189X20965918

Kuhfeld, M., Tarasawa, B., Johnson, A., Ruzek, E., and Lewis, K. (2020b). Learning during COVID-19: Initial findings on students' reading and math achievement and growth . NWEA. Available online at: https://www.ewa.org/sites/main/files/file-attachments/learning_during_covid-19_brief_nwea_nov2020_final.pdf?1606835922

Maity, S., Sahu, T. N., and Sen, N. (2020). Panoramic view of digital education in COVID-19: a new explored avenue. Rev. Educ. 9, 424–426. doi: 10.1002/rev3.3249

Maldonado, J. E., and De Witte, K. (2020). The effect of school closures on standardised student test outcomes . KU Leuven, Faculty of Economics and Business. Available online at: https://lirias.kuleuven.be/retrieve/588087

Meeter, M. (2021). Primary school mathematics during Covid-19: No evidence of learning gaps in adaptive practicing results. PsyArXiv.

O'Connor, M. (2020). School counselling during COVID-19: an initial examination of school counselling use during a 5-week remote learning period. Past. Care Educ. 1–11. doi: 10.1080/02643944.2020.1855674

OECD (2019). PISA 2018 Results (Volume II): Where All Students Can Succeed . OECD Publishing. doi: 10.1787/b5fd1b8f-en

O'Sullivan, K., Clark, S., McGrane, A., Rock, N., Burke, L., Boyle, N., et al. (2021). A qualitative study of child and adolescent mental health during the COVID-19 pandemic in Ireland. Int. J. Environ. Res. Public Health 18:1062. doi: 10.3390/ijerph18031062

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., et al. (2021). The prisma 2020 statement: An updated guideline for reporting systematic reviews. BMJ 372:n71. doi: 10.31222/osf.io/v7gm2

Pensiero, N., Kelly, A., and Bokhove, C. (2020). Learning inequalities during the Covid-19 pandemic: How families cope with home-schooling . University of Southampton research report.

Schult, J., Mahler, N., Fauth, B., and Lindner, M. A. (2021). Did students learn less during the COVID-19 pandemic? reading and mathematics competencies before and after the first pandemic wave. PsyArXiv. doi: 10.31234/osf.io/pqtgf

Smith, J., Guimond, F. A., Bergeron, J., St-Amand, J., Fitzpatrick, C., and Gagnon, M. (2021). Changes in students' achievement motivation in the context of the COVID-19 pandemic: a function of extraversion/introversion? Educ. Sci. 11:30. doi: 10.3390/educsci11010030

Spitzer, M., and Musslick, S. (2021). Academic performance of K-12 students in an online-learning environment for mathematics increased during the shutdown of schools in wake of the Covid-19 pandemic. PLoS ONE , 16:e0255629. doi: 10.1371/journal.pone.0255629

Sterne, J. A. C., Hernán, M. A., Reeves, B. C., Savović, J., Berkman, N. D., Viswanathan, M., et al. (2016). ROBINS-I: a tool for assessing risk of bias in non-randomized studies of interventions. BMJ 355:i4919. doi: 10.1136/bmj.i4919

Tomasik, M. J., Helbling, L. A., and Moser, U. (2020). Educational gains of in-person vs. distance learning in primary and secondary schools: a natural experiment during the COVID-19 pandemic school closures in Switzerland. Int. J. Psychol. 56, 566–576. doi: 10.1002/ijop.12728

UNESCO UNICEF, The World Bank, and OECD. (2021). What's Next? Lessons on Education Recovery . Washington, DC: The World Bank.

van der Velde, M., Sense, F., Spijkers, R., Meeter, M., and van Rijn, H. (2021). Lockdown learning: changes in online study activity and performance of Dutch secondary school students during the COVID-19 pandemic. PsyArXiv. doi: 10.31234/osf.io/fr2v8

Ward, M. (2020). PISA for Development: Out-of-School Assessment, PISA in Focus . OECD Publishing. doi: 10.1787/491fb74a-en

Woessmann, L. (2020). Folgekosten ausbleibenden Lernens: Was wir über die Corona-bedingten Schulschließungen aus der Forschung lernen können [Follow-up costs of an absence of learning: What research can teach us about corona-related school closures]. ifo Schnelldienst 73, 38–44. http://hdl.handle.net/10419/225139

Wyse, A. E., Stickney, E. M., Butz, D., Beckler, A., and Close, C. N. (2020). The potential impact of COVID-19 on student learning and how schools can respond. Educ. Measure. Issue Pract. 39, 60–64. doi: 10.1111/emip.12357

Xie, X., Xue, Q., Zhou, Y., Zhu, K., Liu, Q., Zhang, J., et al. (2020). Mental health status among children in home confinement during the coronavirus disease 2019 outbreak in Hubei Province, China. JAMA Pediatr. 174, 898–900. doi: 10.1001/jamapediatrics.2020.1619

Zaccoletti, S., Camacho, A., Correia, N., Aguiar, C., Mason, L., Alves, R. A., et al. (2020). Parents' perceptions of student academic motivation during the COVID-19 lockdown: A cross-country comparison. Front. Psychol. 11. doi: 10.3389/fpsyg.2020.592670

Keywords: systematic review, COVID-19, school closure, student achievement, learning loss

Citation: Hammerstein S, König C, Dreisörner T and Frey A (2021) Effects of COVID-19-Related School Closures on Student Achievement-A Systematic Review. Front. Psychol. 12:746289. doi: 10.3389/fpsyg.2021.746289

Received: 23 July 2021; Accepted: 20 August 2021; Published: 16 September 2021.

Reviewed by:

Copyright © 2021 Hammerstein, König, Dreisörner and Frey. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Svenja Hammerstein, hammerstein@psych.uni-frankfurt.de

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Published: 30 January 2023

A systematic review and meta-analysis of the evidence on learning during the COVID-19 pandemic

• Bastian A. Betthäuser   ORCID: orcid.org/0000-0002-4544-4073 1 , 2 , 3 ,
• Anders M. Bach-Mortensen   ORCID: orcid.org/0000-0001-7804-7958 2 &
• Per Engzell   ORCID: orcid.org/0000-0002-2404-6308 3 , 4 , 5  

Nature Human Behaviour volume  7 ,  pages 375–385 ( 2023 ) Cite this article

75k Accesses

150 Citations

1973 Altmetric

Metrics details

• Social policy

To what extent has the learning progress of school-aged children slowed down during the COVID-19 pandemic? A growing number of studies address this question, but findings vary depending on context. Here we conduct a pre-registered systematic review, quality appraisal and meta-analysis of 42 studies across 15 countries to assess the magnitude of learning deficits during the pandemic. We find a substantial overall learning deficit (Cohen’s d  = −0.14, 95% confidence interval −0.17 to −0.10), which arose early in the pandemic and persists over time. Learning deficits are particularly large among children from low socio-economic backgrounds. They are also larger in maths than in reading and in middle-income countries relative to high-income countries. There is a lack of evidence on learning progress during the pandemic in low-income countries. Future research should address this evidence gap and avoid the common risks of bias that we identify.

Similar content being viewed by others

Elementary school teachers’ perspectives about learning during the COVID-19 pandemic

A methodological perspective on learning in the developing brain

Measuring and forecasting progress in education: what about early childhood?

The coronavirus disease 2019 (COVID-19) pandemic has led to one of the largest disruptions to learning in history. To a large extent, this is due to school closures, which are estimated to have affected 95% of the world’s student population 1 . But even when face-to-face teaching resumed, instruction has often been compromised by hybrid teaching, and by children or teachers having to quarantine and miss classes. The effect of limited face-to-face instruction is compounded by the pandemic’s consequences for children’s out-of-school learning environment, as well as their mental and physical health. Lockdowns have restricted children’s movement and their ability to play, meet other children and engage in extra-curricular activities. Children’s wellbeing and family relationships have also suffered due to economic uncertainties and conflicting demands of work, care and learning. These negative consequences can be expected to be most pronounced for children from low socio-economic family backgrounds, exacerbating pre-existing educational inequalities.

It is critical to understand the extent to which learning progress has changed since the onset of the COVID-19 pandemic. We use the term ‘learning deficit’ to encompass both a delay in expected learning progress, as well as a loss of skills and knowledge already gained. The COVID-19 learning deficit is likely to affect children’s life chances through their education and labour market prospects. At the societal level, it can have important implications for growth, prosperity and social cohesion. As policy-makers across the world are seeking to limit further learning deficits and to devise policies to recover learning deficits that have already been incurred, assessing the current state of learning is crucial. A careful assessment of the COVID-19 learning deficit is also necessary to weigh the true costs and benefits of school closures.

A number of narrative reviews have sought to summarize the emerging research on COVID-19 and learning, mostly focusing on learning progress relatively early in the pandemic 2 , 3 , 4 , 5 , 6 . Moreover, two reviews harmonized and synthesized existing estimates of learning deficits during the pandemic 7 , 8 . In line with the narrative reviews, these two reviews find a substantial reduction in learning progress during the pandemic. However, this finding is based on a relatively small number of studies (18 and 10 studies, respectively). The limited evidence that was available at the time these reviews were conducted also precluded them from meta-analysing variation in the magnitude of learning deficits over time and across subjects, different groups of students or country contexts.

In this Article, we conduct a systematic review and meta-analysis of the evidence on COVID-19 learning deficits 2.5 years into the pandemic. Our primary pre-registered research question was ‘What is the effect of the COVID-19 pandemic on learning progress amongst school-age children?’, and we address this question using evidence from studies examining changes in learning outcomes during the pandemic. Our second pre-registered research aim was ‘To examine whether the effect of the COVID-19 pandemic on learning differs across different social background groups, age groups, boys and girls, learning areas or subjects, national contexts’.

We contribute to the existing research in two ways. First, we describe and appraise the up-to-date body of evidence, including its geographic reach and quality. More specifically, we ask the following questions: (1) what is the state of the evidence, in terms of the available peer-reviewed research and grey literature, on learning progress of school-aged children during the COVID-19 pandemic?, (2) which countries are represented in the available evidence? and (3) what is the quality of the existing evidence?

Our second contribution is to harmonize, synthesize and meta-analyse the existing evidence, with special attention to variation across different subpopulations and country contexts. On the basis of the identified studies, we ask (4) to what extent has the learning progress of school-aged children changed since the onset of the pandemic?, (5) how has the magnitude of the learning deficit (if any) evolved since the beginning of the pandemic?, (6) to what extent has the pandemic reinforced inequalities between children from different socio-economic backgrounds?, (7) are there differences in the magnitude of learning deficits between subject domains (maths and reading) and between age groups (primary and secondary students)? and (8) to what extent does the magnitude of learning deficits vary across national contexts?

Below, we report our answers to each of these questions in turn. The questions correspond to the analysis plan set out in our pre-registered protocol ( https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021249944 ), but we have adjusted the order and wording to aid readability. We had planned to examine gender differences in learning progress during the pandemic, but found there to be insufficient evidence to conduct this subgroup analysis, as the large majority of the identified studies do not provide evidence on learning deficits separately by gender. We also planned to examine how the magnitude of learning deficits differs across groups of students with varying exposures to school closures. This was not possible as the available data on school closures lack sufficient depth with respect to variation of school closures within countries, across grade levels and with respect to different modes of instruction, to meaningfully examine this association.

The state of the evidence

Our systematic review identified 42 studies on learning progress during the COVID-19 pandemic that met our inclusion criteria. To be included in our systematic review and meta-analysis, studies had to use a measure of learning that can be standardized (using Cohen’s d ) and base their estimates on empirical data collected since the onset of the COVID-19 pandemic (rather than making projections based on pre-COVID-19 data). As shown in Fig. 1 , the initial literature search resulted in 5,153 hits after removal of duplicates. All studies were double screened by the first two authors. The formal database search process identified 15 eligible studies. We also hand searched relevant preprint repositories and policy databases. Further, to ensure that our study selection was as up to date as possible, we conducted two full forward and backward citation searches of all included studies on 15 February 2022, and on 8 August 2022. The citation and preprint hand searches allowed us to identify 27 additional eligible studies, resulting in a total of 42 studies. Most of these studies were published after the initial database search, which illustrates that the body of evidence continues to expand. Most studies provide multiple estimates of COVID-19 learning deficits, separately for maths and reading and for different school grades. The number of estimates ( n  = 291) is therefore larger than the number of included studies ( n  = 42).

Flow diagram of the study identification and selection process, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

The geographic reach of evidence is limited

Table 1 presents all included studies and estimates of COVID-19 learning deficits (in brackets), grouped by the 15 countries represented: Australia, Belgium, Brazil, Colombia, Denmark, Germany, Italy, Mexico, the Netherlands, South Africa, Spain, Sweden, Switzerland, the UK and the United States. About half of the estimates ( n  = 149) are from the United States, 58 are from the UK, a further 70 are from other European countries and the remaining 14 estimates are from Australia, Brazil, Colombia, Mexico and South Africa. As this list shows, there is a strong over-representation of studies from high-income countries, a dearth of studies from middle-income countries and no studies from low-income countries. This skewed representation should be kept in mind when interpreting our synthesis of the existing evidence on COVID-19 learning deficits.

The quality of evidence is mixed

We assessed the quality of the evidence using an adapted version of the Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool 9 . More specifically, we analysed the risk of bias of each estimate from confounding, sample selection, classification of treatments, missing data, the measurement of outcomes and the selection of reported results. A.M.B.-M. and B.A.B. performed the risk-of-bias assessments, which were independently checked by the respective other author. We then assigned each study an overall risk-of-bias rating (low, moderate, serious or critical) based on the estimate and domain with the highest risk of bias.

Figure 2a shows the distribution of all studies of COVID-19 learning deficits according to their risk-of-bias rating separately for each domain (top six rows), as well as the distribution of studies according to their overall risk of bias rating (bottom row). The overall risk of bias was considered ‘low’ for 15% of studies, ‘moderate’ for 30% of studies, ‘serious’ for 25% of studies and ‘critical’ for 30% of studies.

a , Domain-specific and overall distribution of studies of COVID-19 learning deficits by risk of bias rating using ROBINS-I, including studies rated to be at critical risk of bias ( n  = 19 out of a total of n  = 61 studies shown in this figure). In line with ROBINS-I guidance, studies rated to be at critical risk of bias were excluded from all analyses and other figures in this article and in the Supplementary Information (including b ). b , z curve: distribution of the z scores of all estimates included in the meta-analysis ( n  = 291) to test for publication bias. The dotted line indicates z  = 1.96 ( P  = 0.050), the conventional threshold for statistical significance. The overlaid curve shows a normal distribution. The absence of a spike in the distribution of the z scores just above the threshold for statistical significance and the absence of a slump just below it indicate the absence of evidence for publication bias.

In line with ROBINS-I guidance, we excluded studies rated to be at critical risk of bias ( n  = 19) from all of our analyses and figures, except for Fig. 2a , which visualizes the distribution of studies according to their risk of bias 9 . These are thus not part of the 42 studies included in our meta-analysis. Supplementary Table 2 provides an overview of these studies as well as the main potential sources of risk of bias. Moreover, in Supplementary Figs. 3 – 6 , we replicate all our results excluding studies deemed to be at serious risk of bias.

As shown in Fig. 2a , common sources of potential bias were confounding, sample selection and missing data. Studies rated at risk of confounding typically compared only two timepoints, without accounting for longer time trends in learning progress. The main causes of selection bias were the use of convenience samples and insufficient consideration of self-selection by schools or students. Several studies found evidence of selection bias, often with students from a low socio-economic background or schools in deprived areas being under-represented after (as compared with before) the pandemic, but this was not always adjusted for. Some studies also reported a higher amount of missing data post-pandemic, again generally without adjustment, and several studies did not report any information on missing data. For an overview of the risk-of-bias ratings for each domain of each study, see Supplementary Fig. 1 and Supplementary Tables 1 and 2 .

No evidence of publication bias

Publication bias can occur if authors self-censor to conform to theoretical expectations, or if journals favour statistically significant results. To mitigate this concern, we include not only published papers, but also preprints, working papers and policy reports.

Moreover, Fig. 2b tests for publication bias by showing the distribution of z -statistics for the effect size estimates of all identified studies. The dotted line indicates z  = 1.96 ( P  = 0.050), the conventional threshold for statistical significance. The overlaid curve shows a normal distribution. If there was publication bias, we would expect a spike just above the threshold, and a slump just below it. There is no indication of this. Moreover, we do not find a left-skewed distribution of P values (see P curve in Supplementary Fig. 2a ), or an association between estimates of learning deficits and their standard errors (see funnel plot in Supplementary Fig. 2b ) that would suggest publication bias. Publication bias thus does not appear to be a major concern.

Having assessed the quality of the existing evidence, we now present the substantive results of our meta-analysis, focusing on the magnitude of COVID-19 learning deficits and on the variation in learning deficits over time, across different groups of students, and across country contexts.

Learning progress slowed substantially during the pandemic

Figure 3 shows the effect sizes that we extracted from each study (averaged across grades and learning subject) as well as the pooled effect size (red diamond). Effects are expressed in standard deviations, using Cohen’s d . Estimates are pooled using inverse variance weights. The pooled effect size across all studies is d  = −0.14, t (41) = −7.30, two-tailed P  = 0.000, 95% confidence interval (CI) −0.17 to −0.10. Under normal circumstances, students generally improve their performance by around 0.4 standard deviations per school year 10 , 11 , 12 . Thus, the overall effect of d  = −0.14 suggests that students lost out on 0.14/0.4, or about 35%, of a school year’s worth of learning. On average, the learning progress of school-aged children has slowed substantially during the pandemic.

Effect sizes are expressed in standard deviations, using Cohen’s d , with 95% CI, and are sorted by magnitude.

Learning deficits arose early in the pandemic and persist

One may expect that children were able to recover learning that was lost early in the pandemic, after teachers and families had time to adjust to the new learning conditions and after structures for online learning and for recovering early learning deficits were set up. However, existing research on teacher strikes in Belgium 13 and Argentina 14 , shortened school years in Germany 15 and disruptions to education during World War II 16 suggests that learning deficits are difficult to compensate and tend to persist in the long run.

Figure 4 plots the magnitude of estimated learning deficits (on the vertical axis) by the date of measurement (on the horizontal axis). The colour of the circles reflects the relevant country, the size of the circles indicates the sample size for a given estimate and the line displays a linear trend. The figure suggests that learning deficits opened up early in the pandemic and have neither closed nor substantially widened since then. We find no evidence that the slope coefficient is different from zero ( β months  = −0.00, t (41) = −7.30, two-tailed P  = 0.097, 95% CI −0.01 to 0.00). This implies that efforts by children, parents, teachers and policy-makers to adjust to the changed circumstance have been successful in preventing further learning deficits but so far have been unable to reverse them. As shown in Supplementary Fig. 8 , the pattern of persistent learning deficits also emerges within each of the three countries for which we have a relatively large number of estimates at different timepoints: the United States, the UK and the Netherlands. However, it is important to note that estimates of learning deficits are based on distinct samples of students. Future research should continue to follow the learning progress of cohorts of students in different countries to reveal how learning deficits of these cohorts have developed and continue to develop since the onset of the pandemic.

The horizontal axis displays the date on which learning progress was measured. The vertical axis displays estimated learning deficits, expressed in standard deviation (s.d.) using Cohen’s d . The colour of the circles reflects the respective country, the size of the circles indicates the sample size for a given estimate and the line displays a linear trend with a 95% CI. The trend line is estimated as a linear regression using ordinary least squares, with standard errors clustered at the study level ( n  = 42 clusters). β months  = −0.00, t (41) = −7.30, two-tailed P  = 0.097, 95% CI −0.01 to 0.00.

Socio-economic inequality in education increased

Existing research on the development of learning gaps during summer vacations 17 , 18 , disruptions to schooling during the Ebola outbreak in Sierra Leone and Guinea 19 , and the 2005 earthquake in Pakistan 20 shows that the suspension of face-to-face teaching can increase educational inequality between children from different socio-economic backgrounds. Learning deficits during the COVID-19 pandemic are likely to have been particularly pronounced for children from low socio-economic backgrounds. These children have been more affected by school closures than children from more advantaged backgrounds 21 . Moreover, they are likely to be disadvantaged with respect to their access and ability to use digital learning technology, the quality of their home learning environment, the learning support they receive from teachers and parents, and their ability to study autonomously 22 , 23 , 24 .

Most studies we identify examine changes in socio-economic inequality during the pandemic, attesting to the importance of the issue. As studies use different measures of socio-economic background (for example, parental income, parental education, free school meal eligibility or neighbourhood disadvantage), pooling the estimates is not possible. Instead, we code all estimates according to whether they indicate a reduction, no change or an increase in learning inequality during the pandemic. Figure 5 displays this information. Estimates that indicate an increase in inequality are shown on the right, those that indicate a decrease on the left and those that suggest no change in the middle. Squares represent estimates of changes in inequality during the pandemic in reading performance, and circles represent estimates of changes in inequality in maths performance. The shading represents when in the pandemic educational inequality was measured, differentiating between the first, second and third year of the pandemic. Estimates are also arranged horizontally by grade level. A large majority of estimates indicate an increase in educational inequality between children from different socio-economic backgrounds. This holds for both maths and reading, across primary and secondary education, at each stage of the pandemic, and independently of how socio-economic background is measured.

Each circle/square refers to one estimate of over-time change in inequality in maths/reading performance ( n  = 211). Estimates that find a decrease/no change/increase in inequality are grouped on the left/middle/right. Within these categories, estimates are ordered horizontally by school grade. The shading indicates when in the pandemic a given measure was taken.

Learning deficits are larger in maths than in reading

Available research on summer learning deficits 17 , 25 , student absenteeism 26 , 27 and extreme weather events 28 suggests that learning progress in mathematics is more dependent on formal instruction than in reading. This might be due to parents being better equipped to help their children with reading, and children advancing their reading skills (but not their maths skills) when reading for enjoyment outside of school. Figure 6a shows that, similarly to earlier disruptions to learning, the estimated learning deficits during the COVID-19 pandemic are larger for maths than for reading (mean difference δ  = −0.07, t (41) = −4.02, two-tailed P  = 0.000, 95% CI −0.11 to −0.04). This difference is statistically significant and robust to dropping estimates from individual countries (Supplementary Fig. 9 ).

Each plot shows the distribution of COVID-19 learning deficit estimates for the respective subgroup, with the box marking the interquartile range and the white circle denoting the median. Whiskers mark upper and lower adjacent values: the furthest observation within 1.5 interquartile range of either side of the box. a , Learning subject (reading versus maths). Median: reading −0.09, maths −0.18. Interquartile range: reading −0.15 to −0.02, maths −0.23 to −0.09. b , Level of education (primary versus secondary). Median: primary −0.12, secondary −0.12. Interquartile range: primary −0.19 to −0.05, secondary −0.21 to −0.06. c , Country income level (high versus middle). Median: high −0.12, middle −0.37. Interquartile range: high −0.20 to −0.05, middle −0.65 to −0.30.

No evidence of variation across grade levels

One may expect learning deficits to be smaller for older than for younger children, as older children may be more autonomous in their learning and better able to cope with a sudden change in their learning environment. However, older students were subject to longer school closures in some countries, such as Denmark 29 , based partly on the assumption that they would be better able to learn from home. This may have offset any advantage that older children would otherwise have had in learning remotely.

Figure 6b shows the distribution of estimates of learning deficits for students at the primary and secondary level, respectively. Our analysis yields no evidence of variation in learning deficits across grade levels (mean difference δ  = −0.01, t (41) = −0.59, two-tailed P  = 0.556, 95% CI −0.06 to 0.03). Due to the limited number of available estimates of learning deficits, we cannot be certain about whether learning deficits differ between primary and secondary students or not.

Learning deficits are larger in poorer countries

Low- and middle-income countries were already struggling with a learning crisis before the pandemic. Despite large expansions of the proportion of children in school, children in low- and middle-income countries still perform poorly by international standards, and inequality in learning remains high 30 , 31 , 32 . The pandemic is likely to deepen this learning crisis and to undo past progress. Schools in low- and middle-income countries have not only been closed for longer, but have also had fewer resources to facilitate remote learning 33 , 34 . Moreover, the economic resources, availability of digital learning equipment and ability of children, parents, teachers and governments to support learning from home are likely to be lower in low- and middle-income countries 35 .

As discussed above, most evidence on COVID-19 learning deficits comes from high-income countries. We found no studies on low-income countries that met our inclusion criteria, and evidence from middle-income countries is limited to Brazil, Colombia, Mexico and South Africa. Figure 6c groups the estimates of COVID-19 learning deficits in these four middle-income countries together (on the right) and compares them with estimates from high-income countries (on the left). The learning deficit is appreciably larger in middle-income countries than in high-income countries (mean difference δ  = −0.29, t (41) = −2.78, two-tailed P  = 0.008, 95% CI −0.50 to −0.08). In fact, the three largest estimates of learning deficits in our sample are from middle-income countries (Fig. 3 ) 36 , 37 , 38 .

Two years since the COVID-19 pandemic, there is a growing number of studies examining the learning progress of school-aged children during the pandemic. This paper first systematically reviews the existing literature on learning progress of school-aged children during the pandemic and appraises its geographic reach and quality. Second, it harmonizes, synthesizes and meta-analyses the existing evidence to examine the extent to which learning progress has changed since the onset of the pandemic, and how it varies across different groups of students and across country contexts.

Our meta-analysis suggests that learning progress has slowed substantially during the COVID-19 pandemic. The pooled effect size of d  = −0.14, implies that students lost out on about 35% of a normal school year’s worth of learning. This confirms initial concerns that substantial learning deficits would arise during the pandemic 10 , 39 , 40 . But our results also suggest that fears of an accumulation of learning deficits as the pandemic continues have not materialized 41 , 42 . On average, learning deficits emerged early in the pandemic and have neither closed nor widened substantially. Future research should continue to follow the learning progress of cohorts of students in different countries to reveal how learning deficits of these cohorts have developed and continue to develop since the onset of the pandemic.

Most studies that we identify find that learning deficits have been largest for children from disadvantaged socio-economic backgrounds. This holds across different timepoints during the pandemic, countries, grade levels and learning subjects, and independently of how socio-economic background is measured. It suggests that the pandemic has exacerbated educational inequalities between children from different socio-economic backgrounds, which were already large before the pandemic 43 , 44 . Policy initiatives to compensate learning deficits need to prioritize support for children from low socio-economic backgrounds in order to allow them to recover the learning they lost during the pandemic.

There is a need for future research to assess how the COVID-19 pandemic has affected gender inequality in education. So far, there is very little evidence on this issue. The large majority of the studies that we identify do not examine learning deficits separately by gender.

Comparing estimates of learning deficits across subjects, we find that learning deficits tend to be larger in maths than in reading. As noted above, this may be due to the fact that parents and children have been in a better position to compensate school-based learning in reading by reading at home. Accordingly, there are grounds for policy initiatives to prioritize the compensation of learning deficits in maths and other science subjects.

A limitation of this study and the existing body of evidence on learning progress during the COVID-19 pandemic is that the existing studies primarily focus on high-income countries, while there is a dearth of evidence from low- and middle-income countries. This is particularly concerning because the small number of existing studies from middle-income countries suggest that learning deficits have been particularly severe in these countries. Learning deficits are likely to be even larger in low-income countries, considering that these countries already faced a learning crisis before the pandemic, generally implemented longer school closures, and were under-resourced and ill-equipped to facilitate remote learning 32 , 33 , 34 , 35 , 45 . It is critical that this evidence gap on low- and middle-income countries is addressed swiftly, and that the infrastructure to collect and share data on educational performance in middle- and low-income countries is strengthened. Collecting and making available these data is a key prerequisite for fully understanding how learning progress and related outcomes have changed since the onset of the pandemic 46 .

A further limitation is that about half of the studies that we identify are rated as having a serious or critical risk of bias. We seek to limit the risk of bias in our results by excluding all studies rated to be at critical risk of bias from all of our analyses. Moreover, in Supplementary Figs. 3 – 6 , we show that our results are robust to further excluding studies deemed to be at serious risk of bias. Future studies should minimize risk of bias in estimating learning deficits by employing research designs that appropriately account for common sources of bias. These include a lack of accounting for secular time trends, non-representative samples and imbalances between treatment and comparison groups.

The persistence of learning deficits two and a half years into the pandemic highlights the need for well-designed, well-resourced and decisive policy initiatives to recover learning deficits. Policy-makers, schools and families will need to identify and realize opportunities to complement and expand on regular school-based learning. Experimental evidence from low- and middle-income countries suggests that even relatively low-tech and low-cost learning interventions can have substantial, positive effects on students’ learning progress in the context of remote learning. For example, sending SMS messages with numeracy problems accompanied by short phone calls was found to lead to substantial learning gains in numeracy in Botswana 47 . Sending motivational text messages successfully limited learning losses in maths and Portuguese in Brazil 48 .

More evidence is needed to assess the effectiveness of other interventions for limiting or recovering learning deficits. Potential avenues include the use of the often extensive summer holidays to offer summer schools and learning camps, extending school days and school weeks, and organizing and scaling up tutoring programmes. Further potential lies in developing, advertising and providing access to learning apps, online learning platforms or educational TV programmes that are free at the point of use. Many countries have already begun investing substantial resources to capitalize on some of these opportunities. If these interventions prove effective, and if the momentum of existing policy efforts is maintained and expanded, the disruptions to learning during the pandemic may be a window of opportunity to improve the education afforded to children.

Eligibility criteria

We consider all types of primary research, including peer-reviewed publications, preprints, working papers and reports, for inclusion. To be eligible for inclusion, studies have to measure learning progress using test scores that can be standardized across studies using Cohen’s d . Moreover, studies have to be in English, Danish, Dutch, French, German, Norwegian, Spanish or Swedish.

Search strategy and study identification

We identified relevant studies using the following steps. First, we developed a Boolean search string defining the population (school-aged children), exposure (the COVID-19 pandemic) and outcomes of interest (learning progress). The full search string can be found in Section 1.1 of Supplementary Information . Second, we used this string to search the following academic databases: Coronavirus Research Database, the Education Resources Information Centre, International Bibliography of the Social Sciences, Politics Collection (PAIS index, policy file index, political science database and worldwide political science abstracts), Social Science Database, Sociology Collection (applied social science index and abstracts, sociological abstracts and sociology database), Cumulative Index to Nursing and Allied Health Literature, and Web of Science. Second, we hand-searched multiple preprint and working paper repositories (Social Science Research Network, Munich Personal RePEc Archive, IZA, National Bureau of Economic Research, OSF Preprints, PsyArXiv, SocArXiv and EdArXiv) and relevant policy websites, including the websites of the Organization for Economic Co-operation and Development, the United Nations, the World Bank and the Education Endowment Foundation. Third, we periodically posted our protocol via Twitter in order to crowdsource additional relevant studies not identified through the search. All titles and abstracts identified in our search were double-screened using the Rayyan online application 49 . Our initial search was conducted on 27 April 2021, and we conducted two forward and backward citation searches of all eligible studies identified in the above steps, on 14 February 2022, and on 8 August 2022, to ensure that our analysis includes recent relevant research.

Data extraction

From the studies that meet our inclusion criteria we extracted all estimates of learning deficits during the pandemic, separately for maths and reading and for different school grades. We also extracted the corresponding sample size, standard error, date(s) of measurement, author name(s) and country. Last, we recorded whether studies differentiate between children’s socio-economic background, which measure is used to this end and whether studies find an increase, decrease or no change in learning inequality. We contacted study authors if any of the above information was missing in the study. Data extraction was performed by B.A.B. and validated independently by A.M.B.-M., with discrepancies resolved through discussion and by conferring with P.E.

Measurement and standardizationr

We standardize all estimates of learning deficits during the pandemic using Cohen’s d , which expresses effect sizes in terms of standard deviations. Cohen’s d is calculated as the difference in the mean learning gain in a given subject (maths or reading) over two comparable periods before and after the onset of the pandemic, divided by the pooled standard deviation of learning progress in this subject:

Effect sizes expressed as β coefficients are converted to Cohen’s d :

We use a binary indicator for whether the study outcome is maths or reading. One study does not differentiate the outcome but includes a composite of maths and reading scores 50 .

Level of education

We distinguish between primary and secondary education. We first consulted the original studies for this information. Where this was not stated in a given study, students’ age was used in conjunction with information about education systems from external sources to determine the level of education 51 .

Country income level

We follow the World Bank’s classification of countries into four income groups: low, lower-middle, upper-middle and high income. Four countries in our sample are in the upper-middle-income group: Brazil, Colombia, Mexico and South Africa. All other countries are in the high-income group.

Data synthesis

We synthesize our data using three synthesis techniques. First, we generate a forest plot, based on all available estimates of learning progress during the pandemic. We pool estimates using a random-effects restricted maximum likelihood model and inverse variance weights to calculate an overall effect size (Fig. 3 ) 52 . Second, we code all estimates of changes in educational inequality between children from different socio-economic backgrounds during the pandemic, according to whether they indicate an increase, a decrease or no change in educational inequality. We visualize the resulting distribution using a harvest plot (Fig. 5 ) 53 . Third, given that the limited amount of available evidence precludes multivariate or causal analyses, we examine the bivariate association between COVID-19 learning deficits and the months in which learning was measured using a scatter plot (Fig. 4 ), and the bivariate association between COVID-19 learning deficits and subject, grade level and countries’ income level, using a series of violin plots (Fig. 6 ). The reported estimates, CIs and statistical significance tests of these bivariate associations are based on common-effects models with standard errors clustered by study, and two-sided tests. With respect to statistical tests reported, the data distribution was assumed to be normal, but this was not formally tested. The distribution of estimates of learning deficits is shown separately for the different moderator categories in Fig. 6 .

Pre-registration

We prospectively registered a protocol of our systematic review and meta-analysis in the International Prospective Register of Systematic Reviews (CRD42021249944) on 19 April 2021 ( https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021249944 ).

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The data used in the analyses for this manuscript were compiled by the authors based on the studies identified in the systematic review. The data are available on the Open Science Framework repository ( https://doi.org/10.17605/osf.io/u8gaz ). For our systematic review, we searched the following databases: Coronavirus Research Database ( https://proquest.libguides.com/covid19 ), Education Resources Information Centre database ( https://eric.ed.gov ), International Bibliography of the Social Sciences ( https://about.proquest.com/en/products-services/ibss-set-c/ ), Politics Collection ( https://about.proquest.com/en/products-services/ProQuest-Politics-Collection/ ), Social Science Database ( https://about.proquest.com/en/products-services/pq_social_science/ ), Sociology Collection ( https://about.proquest.com/en/products-services/ProQuest-Sociology-Collection/ ), Cumulative Index to Nursing and Allied Health Literature ( https://www.ebsco.com/products/research-databases/cinahl-database ) and Web of Science ( https://clarivate.com/webofsciencegroup/solutions/web-of-science/ ). We also searched the following preprint and working paper repositories: Social Science Research Network ( https://papers.ssrn.com/sol3/DisplayJournalBrowse.cfm ), Munich Personal RePEc Archive ( https://mpra.ub.uni-muenchen.de ), IZA ( https://www.iza.org/content/publications ), National Bureau of Economic Research ( https://www.nber.org/papers?page=1&perPage=50&sortBy=public_date ), OSF Preprints ( https://osf.io/preprints/ ), PsyArXiv ( https://psyarxiv.com ), SocArXiv ( https://osf.io/preprints/socarxiv ) and EdArXiv ( https://edarxiv.org ).

Code availability

All code needed to replicate our findings is available on the Open Science Framework repository ( https://doi.org/10.17605/osf.io/u8gaz ).

The Impact of COVID-19 on Children. UN Policy Briefs (United Nations, 2020).

Donnelly, R. & Patrinos, H. A. Learning loss during Covid-19: An early systematic review. Prospects (Paris) 51 , 601–609 (2022).

Hammerstein, S., König, C., Dreisörner, T. & Frey, A. Effects of COVID-19-related school closures on student achievement: a systematic review. Front. Psychol. https://doi.org/10.3389/fpsyg.2021.746289 (2021).

Panagouli, E. et al. School performance among children and adolescents during COVID-19 pandemic: a systematic review. Children 8 , 1134 (2021).

Article   PubMed   PubMed Central   Google Scholar  

Patrinos, H. A., Vegas, E. & Carter-Rau, R. An Analysis of COVID-19 Student Learning Loss (World Bank, 2022).

Zierer, K. Effects of pandemic-related school closures on pupils’ performance and learning in selected countries: a rapid review. Educ. Sci. 11 , 252 (2021).

Article   Google Scholar  

König, C. & Frey, A. The impact of COVID-19-related school closures on student achievement: a meta-analysis. Educ. Meas. Issues Pract. 41 , 16–22 (2022).

Storey, N. & Zhang, Q. A meta-analysis of COVID learning loss. Preprint at EdArXiv (2021).

Sterne, J. A. et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ https://doi.org/10.1136/bmj.i4919 (2016).

Azevedo, J. P., Hasan, A., Goldemberg, D., Iqbal, S. A. & Geven, K. Simulating the Potential Impacts of COVID-19 School Closures on Schooling and Learning Outcomes: A Set of Global Estimates (World Bank, 2020).

Bloom, H. S., Hill, C. J., Black, A. R. & Lipsey, M. W. Performance trajectories and performance gaps as achievement effect-size benchmarks for educational interventions. J. Res. Educ. Effectiveness 1 , 289–328 (2008).

Hill, C. J., Bloom, H. S., Black, A. R. & Lipsey, M. W. Empirical benchmarks for interpreting effect sizes in research. Child Dev. Perspect. 2 , 172–177 (2008).

Belot, M. & Webbink, D. Do teacher strikes harm educational attainment of students? Labour 24 , 391–406 (2010).

Jaume, D. & Willén, A. The long-run effects of teacher strikes: evidence from Argentina. J. Labor Econ. 37 , 1097–1139 (2019).

Cygan-Rehm, K. Are there no wage returns to compulsory schooling in Germany? A reassessment. J. Appl. Econ. 37 , 218–223 (2022).

Ichino, A. & Winter-Ebmer, R. The long-run educational cost of World War II. J. Labor Econ. 22 , 57–87 (2004).

Cooper, H., Nye, B., Charlton, K., Lindsay, J. & Greathouse, S. The effects of summer vacation on achievement test scores: a narrative and meta-analytic review. Rev. Educ. Res. 66 , 227–268 (1996).

Allington, R. L. et al. Addressing summer reading setback among economically disadvantaged elementary students. Read. Psychol. 31 , 411–427 (2010).

Smith, W. C. Consequences of school closure on access to education: lessons from the 2013–2016 Ebola pandemic. Int. Rev. Educ. 67 , 53–78 (2021).

Andrabi, T., Daniels, B. & Das, J. Human capital accumulation and disasters: evidence from the Pakistan earthquake of 2005. J. Hum. Resour . https://doi.org/10.35489/BSG-RISE-WP_2020/039 (2021).

Parolin, Z. & Lee, E. K. Large socio-economic, geographic and demographic disparities exist in exposure to school closures. Nat. Hum. Behav. 5 , 522–528 (2021).

Goudeau, S., Sanrey, C., Stanczak, A., Manstead, A. & Darnon, C. Why lockdown and distance learning during the COVID-19 pandemic are likely to increase the social class achievement gap. Nat. Hum. Behav. 5 , 1273–1281 (2021).

Article   PubMed   Google Scholar  

Bailey, D. H., Duncan, G. J., Murnane, R. J. & Au Yeung, N. Achievement gaps in the wake of COVID-19. Educ. Researcher 50 , 266–275 (2021).

van de Werfhorst, H. G. Inequality in learning is a major concern after school closures. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2105243118 (2021).

Alexander, K. L., Entwisle, D. R. & Olson, L. S. Schools, achievement, and inequality: a seasonal perspective. Educ. Eval. Policy Anal. 23 , 171–191 (2001).

Aucejo, E. M. & Romano, T. F. Assessing the effect of school days and absences on test score performance. Econ. Educ. Rev. 55 , 70–87 (2016).

Gottfried, M. A. The detrimental effects of missing school: evidence from urban siblings. Am. J. Educ. 117 , 147–182 (2011).

Goodman, J. Flaking Out: Student Absences and Snow Days as Disruptions of Instructional Time (National Bureau of Economic Research, 2014).

Birkelund, J. F. & Karlson, K. B. No evidence of a major learning slide 14 months into the COVID-19 pandemic in Denmark. European Societies https://doi.org/10.1080/14616696.2022.2129085 (2022).

Angrist, N., Djankov, S., Goldberg, P. K. & Patrinos, H. A. Measuring human capital using global learning data. Nature 592 , 403–408 (2021).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Torche, F. in Social Mobility in Developing Countries: Concepts, Methods, and Determinants (eds Iversen, V., Krishna, A. & Sen, K.) 139–171 (Oxford Univ. Press, 2021).

World Development Report 2018: Learning to Realize Education’s Promise (World Bank, 2018).

Policy Brief: Education during COVID-19 and Beyond (United Nations, 2020).

One Year into COVID-19 Education Disruption: Where Do We Stand? (UNESCO, 2021).

Azevedo, J. P., Hasan, A., Goldemberg, D., Geven, K. & Iqbal, S. A. Simulating the potential impacts of COVID-19 school closures on schooling and learning outcomes: a set of global estimates. World Bank Res. Observer 36 , 1–40 (2021).

Google Scholar  

Ardington, C., Wills, G. & Kotze, J. COVID-19 learning losses: early grade reading in South Africa. Int. J. Educ. Dev. 86 , 102480 (2021).

Hevia, F. J., Vergara-Lope, S., Velásquez-Durán, A. & Calderón, D. Estimation of the fundamental learning loss and learning poverty related to COVID-19 pandemic in Mexico. Int. J. Educ. Dev. 88 , 102515 (2022).

Lichand, G., Doria, C. A., Leal-Neto, O. & Fernandes, J. P. C. The impacts of remote learning in secondary education during the pandemic in Brazil. Nat. Hum. Behav. 6 , 1079–1086 (2022).

Major, L. E., Eyles, A., Machin, S. et al. Learning Loss since Lockdown: Variation across the Home Nations (Centre for Economic Performance, London School of Economics and Political Science, 2021).

Di Pietro, G., Biagi, F., Costa, P., Karpinski, Z. & Mazza, J. The Likely Impact of COVID-19 on Education: Reflections Based on the Existing Literature and Recent International Datasets (Publications Office of the European Union, 2020).

Fuchs-Schündeln, N., Krueger, D., Ludwig, A. & Popova, I. The Long-Term Distributional and Welfare Effects of COVID-19 School Closures (National Bureau of Economic Research, 2020).

Kaffenberger, M. Modelling the long-run learning impact of the COVID-19 learning shock: actions to (more than) mitigate loss. Int. J. Educ. Dev. 81 , 102326 (2021).

Attewell, P. & Newman, K. S. Growing Gaps: Educational Inequality around the World (Oxford Univ. Press, 2010).

Betthäuser, B. A., Kaiser, C. & Trinh, N. A. Regional variation in inequality of educational opportunity across europe. Socius https://doi.org/10.1177/23780231211019890 (2021).

Angrist, N. et al. Building back better to avert a learning catastrophe: estimating learning loss from covid-19 school shutdowns in africa and facilitating short-term and long-term learning recovery. Int. J. Educ. Dev. 84 , 102397 (2021).

Conley, D. & Johnson, T. Opinion: Past is future for the era of COVID-19 research in the social sciences. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2104155118 (2021).

Angrist, N., Bergman, P. & Matsheng, M. Experimental evidence on learning using low-tech when school is out. Nat. Hum. Behav. 6 , 941–950 (2022).

Lichand, G., Christen, J. & van Egeraat, E. Do Behavioral Nudges Work under Remote Learning? Evidence from Brazil during the Pandemic (Univ. Zurich, 2022).

Ouzzani, M., Hammady, H., Fedorowicz, Z. & Elmagarmid, A. Rayyan—a web and mobile app for systematic reviews. Syst. Rev. 5 , 1–10 (2016).

Tomasik, M. J., Helbling, L. A. & Moser, U. Educational gains of in-person vs. distance learning in primary and secondary schools: a natural experiment during the COVID-19 pandemic school closures in Switzerland. Int. J. Psychol. 56 , 566–576 (2021).

Eurybase: The Information Database on Education Systems in Europe (Eurydice, 2021).

Borenstein, M., Hedges, L. V., Higgins, J. P. & Rothstein, H. R. A basic introduction to fixed-effect and random-effects models for meta-analysis. Res. Synth. Methods 1 , 97–111 (2010).

Ogilvie, D. et al. The harvest plot: a method for synthesising evidence about the differential effects of interventions. BMC Med. Res. Methodol. 8 , 1–7 (2008).

Gore, J., Fray, L., Miller, A., Harris, J. & Taggart, W. The impact of COVID-19 on student learning in New South Wales primary schools: an empirical study. Aust. Educ. Res. 48 , 605–637 (2021).

Gambi, L. & De Witte, K. The Resiliency of School Outcomes after the COVID-19 Pandemic: Standardised Test Scores and Inequality One Year after Long Term School Closures (FEB Research Report Department of Economics, 2021).

Maldonado, J. E. & De Witte, K. The effect of school closures on standardised student test outcomes. Br. Educ. Res. J. 48 , 49–94 (2021).

Vegas, E. COVID-19’s Impact on Learning Losses and Learning Inequality in Colombia (Center for Universal Education at Brookings, 2022).

Depping, D., Lücken, M., Musekamp, F. & Thonke, F. in Schule während der Corona-Pandemie. Neue Ergebnisse und Überblick über ein dynamisches Forschungsfeld (eds Fickermann, D. & Edelstein, B.) 51–79 (Münster & New York: Waxmann, 2021).

Ludewig, U. et al. Die COVID-19 Pandemie und Lesekompetenz von Viertklässler*innen: Ergebnisse der IFS-Schulpanelstudie 2016–2021 (Institut für Schulentwicklungsforschung, Univ. Dortmund, 2022).

Schult, J., Mahler, N., Fauth, B. & Lindner, M. A. Did students learn less during the COVID-19 pandemic? Reading and mathematics competencies before and after the first pandemic wave. Sch. Eff. Sch. Improv. https://doi.org/10.1080/09243453.2022.2061014 (2022).

Schult, J., Mahler, N., Fauth, B. & Lindner, M. A. Long-term consequences of repeated school closures during the COVID-19 pandemic for reading and mathematics competencies. Front. Educ. https://doi.org/10.3389/feduc.2022.867316 (2022).

Bazoli, N., Marzadro, S., Schizzerotto, A. & Vergolini, L. Learning Loss and Students’ Social Origins during the COVID-19 Pandemic in Italy (FBK-IRVAPP Working Papers 3, 2022).

Borgonovi, F. & Ferrara, A. The effects of COVID-19 on inequalities in educational achievement in Italy. Preprint at SSRN https://doi.org/10.2139/ssrn.4171968 (2022).

Contini, D., Di Tommaso, M. L., Muratori, C., Piazzalunga, D. & Schiavon, L. Who lost the most? Mathematics achievement during the COVID-19 pandemic. BE J. Econ. Anal. Policy 22 , 399–408 (2022).

Engzell, P., Frey, A. & Verhagen, M. D. Learning loss due to school closures during the COVID-19 pandemic. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2022376118 (2021).

Haelermans, C. Learning Growth and Inequality in Primary Education: Policy Lessons from the COVID-19 Crisis (The European Liberal Forum (ELF)-FORES, 2021).

Haelermans, C. et al. A Full Year COVID-19 Crisis with Interrupted Learning and Two School Closures: The Effects on Learning Growth and Inequality in Primary Education (Maastricht Univ., Research Centre for Education and the Labour Market (ROA), 2021).

Haelermans, C. et al. Sharp increase in inequality in education in times of the COVID-19-pandemic. PLoS ONE 17 , e0261114 (2022).

Schuurman, T. M., Henrichs, L. F., Schuurman, N. K., Polderdijk, S. & Hornstra, L. Learning loss in vulnerable student populations after the first COVID-19 school closure in the Netherlands. Scand. J. Educ. Res. https://doi.org/10.1080/00313831.2021.2006307 (2021).

Arenas, A. & Gortazar, L. Learning Loss One Year after School Closures (Esade Working Paper, 2022).

Hallin, A. E., Danielsson, H., Nordström, T. & Fälth, L. No learning loss in Sweden during the pandemic evidence from primary school reading assessments. Int. J. Educ. Res. 114 , 102011 (2022).

Blainey, K. & Hannay, T. The Impact of School Closures on Autumn 2020 Attainment (RS Assessment from Hodder Education and SchoolDash, 2021).

Blainey, K. & Hannay, T. The Impact of School Closures on Spring 2021 Attainment (RS Assessment from Hodder Education and SchoolDash, 2021).

Blainey, K. & Hannay, T. The Effects of Educational Disruption on Primary School Attainment in Summer 2021 (RS Assessment from Hodder Education and SchoolDash, 2021).

Understanding Progress in the 2020/21 Academic Year: Complete Findings from the Autumn Term (London: Department for Education, 2021).

Understanding Progress in the 2020/21 Academic Year: Initial Findings from the Spring Term (London: Department for Education, 2021).

Impact of COVID-19 on Attainment: Initial Analysis (Brentford: GL Assessment, 2021).

Rose, S. et al. Impact of School Closures and Subsequent Support Strategies on Attainment and Socio-emotional Wellbeing in Key Stage 1: Interim Paper 1 (National Foundation for Educational Research (NFER) and Education Endowment Foundation (EEF) , 2021).

Rose, S. et al. Impact of School Closures and Subsequent Support Strategies on Attainment and Socio-emotional Wellbeing in Key Stage 1: Interim Paper 2 (National Foundation for Educational Research (NFER) and Education Endowment Foundation (EEF), 2021).

Weidmann, B. et al. COVID-19 Disruptions: Attainment Gaps and Primary School Responses (Education Endowment Foundation, 2021).

Bielinski, J., Brown, R. & Wagner, K. No Longer a Prediction: What New Data Tell Us About the Effects of 2020 Learning Disruptions (Illuminate Education, 2021).

Domingue, B. W., Hough, H. J., Lang, D. & Yeatman, J. Changing Patterns of Growth in Oral Reading Fluency During the COVID-19 Pandemic. PACE Working Paper (Policy Analysis for California Education, 2021).

Domingue, B. et al. The effect of COVID on oral reading fluency during the 2020–2021 academic year. AERA Open https://doi.org/10.1177/23328584221120254 (2022).

Kogan, V. & Lavertu, S. The COVID-19 Pandemic and Student Achievement on Ohio’s Third-Grade English Language Arts Assessment (Ohio State Univ., 2021).

Kogan, V. & Lavertu, S. How the COVID-19 Pandemic Affected Student Learning in Ohio: Analysis of Spring 2021 Ohio State Tests (Ohio State Univ., 2021).

Kozakowski, W., Gill, B., Lavallee, P., Burnett, A. & Ladinsky, J. Changes in Academic Achievement in Pittsburgh Public Schools during Remote Instruction in the COVID-19 Pandemic (Institute of Education Sciences (IES), US Department of Education, 2020).

Kuhfeld, M. & Lewis, K. Student Achievement in 2021–2022: Cause for Hope and Continued Urgency (NWEA, 2022).

Lewis, K., Kuhfeld, M., Ruzek, E. & McEachin, A. Learning during COVID-19: Reading and Math Achievement in the 2020–21 School Year (NWEA, 2021).

Locke, V. N., Patarapichayatham, C. & Lewis, S. Learning Loss in Reading and Math in US Schools Due to the COVID-19 Pandemic (Istation, 2021).

Pier, L., Christian, M., Tymeson, H. & Meyer, R. H. COVID-19 Impacts on Student Learning: Evidence from Interim Assessments in California. PACE Working Paper (Policy Analysis for California Education, 2021).

Download references

Acknowledgements

Carlsberg Foundation grant CF19-0102 (A.M.B.-M.); Leverhulme Trust Large Centre Grant (P.E.), the Swedish Research Council for Health, Working Life and Welfare (FORTE) grant 2016-07099 (P.E.); the French National Research Agency (ANR) as part of the ‘Investissements d’Avenir’ programme LIEPP (ANR-11-LABX-0091 and ANR-11-IDEX-0005-02) and the Université Paris Cité IdEx (ANR-18-IDEX-0001) (P.E.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and affiliations.

Centre for Research on Social Inequalities (CRIS), Sciences Po, Paris, France

Bastian A. Betthäuser

Department of Social Policy and Intervention, University of Oxford, Oxford, UK

Bastian A. Betthäuser & Anders M. Bach-Mortensen

Nuffield College, University of Oxford, Oxford, UK

Bastian A. Betthäuser & Per Engzell

Social Research Institute, University College London, London, UK

Per Engzell

Swedish Institute for Social Research, Stockholm University, Stockholm, Sweden

You can also search for this author in PubMed   Google Scholar

Contributions

B.A.B., A.M.B.-M. and P.E. designed the study; B.A.B., A.M.B.-M. and P.E. planned and implemented the search and screened studies; B.A.B., A.M.B.-M. and P.E. extracted relevant data from studies; B.A.B., A.M.B.-M. and P.E. conducted the quality appraisal; B.A.B., A.M.B.-M. and P.E. conducted the data analysis and visualization; B.A.B., A.M.B.-M. and P.E. wrote the manuscript.

Corresponding author

Correspondence to Bastian A. Betthäuser .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Nature Human Behaviour thanks Guilherme Lichand, Sébastien Goudeau and Christoph König for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary information.

Supplementary methods, results, figures, tables, PRISMA Checklist and references.

Reporting Summary

Peer review file, 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.

Reprints and permissions

About this article

Cite this article.

Betthäuser, B.A., Bach-Mortensen, A.M. & Engzell, P. A systematic review and meta-analysis of the evidence on learning during the COVID-19 pandemic. Nat Hum Behav 7 , 375–385 (2023). https://doi.org/10.1038/s41562-022-01506-4

Download citation

Received : 24 June 2022

Accepted : 30 November 2022

Published : 30 January 2023

Issue Date : March 2023

DOI : https://doi.org/10.1038/s41562-022-01506-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Investigating the effect of covid-19 disruption in education using reds data.

• Alice Bertoletti
• Zbigniew Karpiński

Large-scale Assessments in Education (2024)

Innovate! Accelerate! Evaluate! Harnessing the RE-AIM framework to examine the global dissemination of parenting resources during COVID-19 to more than 210 million people

• Jamie M. Lachman
• Nisso Nurova
• Lucie Cluver

BMC Public Health (2024)

Developmental Losses of Preschool Children Three Years into the COVID-19 Pandemic

• Alejandro Vásquez-Echeverría
• Meliza Gónzalez
• Sylvana M Côté

Prevention Science (2024)

School reopening concerns amid a pandemic among higher education students: a developing country perspective for policy development

• Manuel B. Garcia

Educational Research for Policy and Practice (2024)

A democratic curriculum for the challenges of post-truth

• David Nally

Curriculum Perspectives (2024)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

How COVID-19 caused a global learning crisis

Executive summary.

In our latest report on unfinished learning, we examine the impact of the COVID-19 pandemic on student learning and well-being, and identify potential considerations for school systems as they support students in recovery and beyond. Our key findings include the following:

• The length of school closures varied widely across the world. School buildings in middle-income Latin America and South Asia were fully or partially closed the longest—for 75 weeks or more. Those in high-income Europe and Central Asia were fully or partially closed for less time (30 weeks on average), as were those in low-income sub-Saharan Africa (34 weeks on average).

About the authors

This article is a collaborative effort by Jake Bryant , Felipe Child , Emma Dorn , Jose Espinosa, Stephen Hall , Topsy Kola-Oyeneyin , Cheryl Lim, Frédéric Panier, Jimmy Sarakatsannis , Dirk Schmautzer , Seckin Ungur , and Bart Woord, representing views from McKinsey’s Education Practice.

• Access to quality remote and hybrid learning also varied both across and within countries. In Tanzania, while school buildings were closed, children in just 6 percent of households listened to radio lessons, 5 percent accessed TV lessons, and fewer than 1 percent participated in online learning. 1 Jacobus Cilliers and Shardul Oza, “What did children do during school closures? Insights from a parent survey in Tanzania,” Research on Improving Systems of Education (RISE), May 19, 2021.
• Furthermore, pandemic-related learning delays stack up on top of historical learning inequities. The World Bank estimates that while students in high-income countries gained an average of 50 harmonized learning outcomes (HLO) points a year prepandemic, students in low-income countries were gaining just 20, leaving those students several years behind. 2 Noam Angrist et al., “Measuring human capital using global learning data,” Nature , March 2021, Volume 592.
• High-performing systems, with relatively high levels of pre-COVID-19 performance, where students may be about one to five months behind due to the pandemic (for example, North America and Europe, where students are, on average, four months behind).
• Low-income prepandemic-challenged systems, with very low levels of pre-COVID-19 learning, where students may be about three to eight months behind due to the pandemic (for example, sub-Saharan Africa, where students are on average six months behind).
• Pandemic-affected middle-income systems, with moderate levels of pre-COVID-19 learning, where students may be nine to 15 months behind (for example, Latin America and South Asia, where students are, on average, 12 months behind).
• The pandemic also increased inequalities within systems. For example, it widened gaps between majority Black and majority White schools in the United States and increased preexisting urban-rural divides in Ethiopia.
• Beyond learning, the pandemic has had broader social and emotional impacts on students globally—with rising mental-health concerns, reports of violence against children, rising obesity, increases in teenage pregnancy, and rising levels of chronic absenteeism and dropouts.
• Lower levels of learning translate into lower future earnings potential for students and lower economic productivity for nations. By 2040, the economic impact of pandemic-related learning delays could lead to annual losses of $1.6 trillion worldwide, or 0.9 percent of total global GDP.
• Resilience: Safely reopen schools for in-person learning while ensuring resilience for future disruptions.
• Reenrollment: Encourage students, families, and teachers to reengage with learning in effective learning environments.
• Recovery: Support students as they recover from the academic and social-emotional impacts of the pandemic, starting with an understanding of each student’s needs.
• Reimagining: Recommit to quality education for every child, doubling down on the fundamentals of educational excellence and innovating to adapt.

In some parts of the world, students, parents, and teachers may be experiencing a novel feeling: cautious optimism. After two years of disruptions from COVID-19, the overnight shift to online and hybrid learning, and efforts to safeguard teachers, administrators, and students, cities and countries are seeing the first signs of the next normal. Masks are coming off. Events are being held in person. Extracurricular activities are back in full swing.

These signs of hope are counterbalanced by the lingering, widespread impact of the pandemic. While it’s too early to catalog all of the ways students have been affected, we are starting to see initial indications of the toll COVID-19 has taken on learning around the world. Our analysis of available data found no country was untouched, but the impact varied across regions and within countries. Even in places with effective school systems and near-universal connectivity and device access, learning delays were significant, especially for historically vulnerable populations. 3 Emma Dorn, Bryan Hancock, Jimmy Sarakatsannis, and Ellen Viruleg, “ COVID-19 and education: An emerging K-shaped recovery ,” McKinsey, December 14, 2021. In many countries that had poor education outcomes before the pandemic, the setbacks were even greater. In those countries, an even more ambitious, coordinated effort will likely be required to address the disruption students have experienced.

Our analysis highlights the extent of the challenge and demonstrates how the impact of the pandemic on learning extends across students, families, and entire communities. Beyond the direct effect on students, learning delays have the potential to affect economic growth: by 2040, according to McKinsey analysis, COVID-19-related unfinished learning could translate into $1.6 trillion in annual losses to the global economy.

Acting decisively in the near term could help to address learning delays as well as the broader social, emotional, and mental-health impact on students. In mobilizing to respond to the pandemic’s effect on student learning and thriving, countries also may need to reassess their education systems—what has been working well and what may need to be reimagined in light of the past two years. Our hope is that this article’s analysis provides a potential starting point for dialogue as nations seek to reinvigorate their education systems.

Gauging the pandemic’s widespread impact on education

One of the challenges in assessing the global effect of the pandemic on learning is the lack of data. Comparative international assessments mostly cover middle- to high-income countries and have not been carried out since the beginning of the pandemic. The next Program for International Student Assessment (PISA), for example, was delayed until 2022. 4 “PISA,” OECD, accessed March 30, 2022. Similarly, many countries had to cancel or defer national assessments. As a result, few nations have a complete data set, and many have no assessment data to indicate relative learning before and since school closures. Accordingly, our methodology used available data augmented by informed assumptions to get a directional picture of the pandemic’s effects on the scholastic achievement and well-being of students.

The pandemic’s impact on student learning

We evaluated the potential effect of the pandemic on student learning by multiplying the amount of time school was disrupted in each country by the estimated effectiveness of the schooling students received during disruptions.

The duration of school closures ran the gamut. During the 102-week period we studied (from the onset of COVID-19 to January 2022), school buildings in Latin America, including the Caribbean, and South Asia were fully or partially closed for 75 weeks or more, while those in Europe and Central Asia were fully or partially closed for an average of 30 weeks (Exhibit 1). Schools in some regions began reopening a few months into the pandemic, but as of January 2022, more than a quarter of the world’s student population resided in school systems where schools were not yet fully open.

Remote and hybrid learning similarly varied widely across and within countries. Some students were supported by internet access, devices, learning management systems, adaptive learning software, live videoconferencing with teachers and peers, and home environments with parents or hired professionals to support remote learning. Others had access to radio or television programs, paper packages, and text messaging. Some students may not have had access to any learning options. 5 What’s next? Lessons on education recovery: Findings from a survey of ministries of education amid the COVID-19 pandemic , UNESCO, UNICEF, the World Bank, and OECD, June 2021. We used the World Bank’s estimates on “mitigation effectiveness” by country income level to account for different levels of access to learning tools and quality through the pandemic (see the forthcoming methodological appendix for more details).

Our model suggests that in the first 23 months since the start of the pandemic, students around the world may have lost about eight months of learning, on average, with meaningful disparities across and within regions and countries. For example, students in South Asia, Latin America, and the Caribbean may be more than a year behind where they would have been absent the pandemic. In North America and Europe, students might be an average of four months behind (Exhibit 2).

The regional numbers only begin to tell the full story. The greater the range of school system performance and resources across regions, the greater the variation in student experiences. Students in Japan and Australia may be less than two months behind, while students in the Philippines and Indonesia may be more than a year behind where they would have been (Exhibit 3).

Within countries, the impact of COVID-19 has also affected individual students differently. Wherever assessments have taken place since the onset of the pandemic, they suggest widening gaps in both opportunity and achievement. Historically vulnerable and marginalized students are at an increased risk of falling further behind.

In the United States, students in majority Black schools were half a year behind in mathematics and reading by fall 2021, while students in majority White schools were just two months behind. 6 “ COVID-19 and education: An emerging K-shaped recovery ,” December 14, 2021. In Ethiopia, students in rural areas achieved under one-third of the expected learning from March to October 2020, while those in urban areas learned less than half of the expected amount. 7 Research on Improving Systems of Education (RISE) , “Learning inequalities widen following COVID-19 school closures in Ethiopia,” blog entry by Janice Kim, Pauline Rose, Ricardo Sabates, Dawit Tibebu Tiruneh, and Tassew Woldehanna, May 4, 2021. Assessments in New South Wales, Australia, detected minimal impact on learning overall, but third-grade students in the most disadvantaged schools experienced two months less growth in mathematics. 8 Leanne Fray et al., “The impact of COVID-19 on student learning in New South Wales primary schools: An empirical study,” The Australian Educational Researcher , 2021, Volume 48.

Would you like to learn more about our Education Practice ?

Covid-19-related losses on top of historical inequalities.

The learning crisis is not new. In the years before COVID-19, many school systems faced challenges in providing learning opportunities for many of their students. The World Bank estimates that before the pandemic, more than half of students in low- and middle-income countries were living in “learning poverty”—unable to read and understand a simple text by age ten. That number may rise as high as 70 percent due to pandemic-related school disruptions. 9 Joao Azevedo et al., “The state of the global education crisis: A path to recovery,” World Bank Group, December 3, 2021.

The World Bank’s harmonized learning outcomes (HLOs) compare learning achievement and growth across countries. This measure combines multiple global student assessments into one metric, with a range of 625 for advanced attainment and 300 for minimum attainment. According to the World Bank’s 2018 HLO database, students from some countries in the Middle East, North Africa, and South Asia were several years behind their counterparts in North America and Europe before the pandemic (Exhibit 4). 10 Data Blog , “Harmonized learning outcomes: transforming learning assessment data into national education policy reforms,” blog entry by Harry A. Patrinos and Noam Angrist, August 12, 2019.

Students in these countries were also progressing more slowly each year in school. While students in high-income countries may have been gaining 50 HLO points in a year, students in low-income countries were gaining just 20. In other words, not much learning was happening in some countries even before the pandemic.

Prepandemic learning levels and pandemic-related learning delays interacted in different ways in different countries and regions. Although each country is unique, three archetypes emerge based on the performance of education systems (Exhibit 5).

High-performing systems. Countries in this archetype generally had higher pre-COVID-19 learning levels. Systems had more capacity for remote learning, and school buildings remained closed for shorter time periods. 11 “Education: From disruption to recovery,” UNESCO, accessed March 11, 2022. Data suggest that after the initial shock of the pandemic in 2020, learning delays increased only moderately with subsequent school closures in the 2021–22 school year. Some high-income countries seem to show little evidence of decreased learning overall. According to the Australian National Assessment Program–Literacy and Numeracy (NAPLAN), the COVID-19 pandemic did not have a statistically significant impact on average student literacy and numeracy levels, even in Victoria, where learning was remote for more than 120 days. 12 “Highlights from Victorian preliminary results in NAPLAN 2021,” Victoria state government, August 26, 2021; Adam Carey, Melissa Cunningham, and Anna Prytz, “‘Children have suffered enormously’: School closures leave experts divided,” The Age , Melbourne, July 25, 2021. However, in many high-income countries, the impact of the pandemic on learning remained significant. Assessments of student learning in the United States in fall 2021 suggested students had fallen four months behind in mathematics and three months behind in reading. 13 “ COVID-19 and education: An emerging K-shaped recovery ,” December 14, 2021. Inequalities in learning also increased within many of these countries, with historically marginalized students most affected.

Lower-income, prepandemic-challenged systems. This archetype consists of mostly low-income and lower-middle-income countries with very low levels of pre-COVID-19 learning. When the pandemic struck, school buildings closed for varying periods of time, 14 “Education: From disruption to recovery,” UNESCO, accessed March 11, 2022. with limited options for remote learning. In Tanzania, for example, schools were closed for 15 weeks, and during this period, just 6 percent of households reported that their children listened to radio lessons, 5 percent watched TV lessons, and fewer than 1 percent accessed educational programs on the internet. 15 Jacobus Cilliers and Shardul Oza, “What did children do during school closures? Insights from a parent survey in Tanzania,” Research on Improving Systems of Education (RISE), May 19, 2021. Across the analyzed time period, schools in sub-Saharan Africa were fully open for more weeks, on average, than schools in any other region. As a result, the pandemic’s impact on learning was relatively muted, even though many of these systems faced challenges with effective remote learning. 16 A report of six countries in Africa, for example, found limited impact of the pandemic on already-low student outcomes. For more information, see “MILO: Monitoring impacts on learning outcomes,” UNESCO, accessed March 11, 2022.

These relatively smaller pandemic learning delays are likely due in part to the limited progress students were making in schools before COVID-19. 17 World Bank blogs , “Harmonized learning outcomes: Transforming learning assessment data into national education policy reforms,” blog entry by Harry A. Patrinos and Noam Angrist, August 12, 2019. If students weren’t progressing scholastically when schools were open, closures were likely to have less impact. In Tanzania before the pandemic, three-quarters of students in grade three could not read a basic sentence. 18 “What did children do during school closures?,” May 19, 2021.

Pandemic-affected middle-income systems. School systems in Latin American and South Asian countries had low to moderate performance before COVID-19. Many middle-income countries in this group did have some capacity to plan and roll out remote-learning options, especially in urban areas. 19 “Responses to Educational Disruption Survey (REDS),” UNESCO, accessed March 11, 2022. However, pandemic-related disruptions caused widespread school closures for extended periods of time—more than 50 weeks in some countries. 20 “Education: From disruption to recovery,” UNESCO, accessed March 11, 2022. The resulting learning delays may represent a true crisis for major economies such as India, Indonesia, and Mexico, where students are more than a year behind, on average.

While some students may have just learned more slowly than they would have absent the pandemic, others in this archetype may have actually slipped backward. A study by the Azim Premji Foundation suggests that as early as January 2021, more than 90 percent of students assessed in India have lost at least one language ability (such as reading words or writing simple sentences), while more than 80 percent lost a math ability (for example, identifying single- and double-digit numbers or naming shapes). 21 Loss of learning during the pandemic , Azim Premji Foundation, February 2021. This pattern could be particularly challenging, since higher-order skills are increasingly important in middle-income countries with rising levels of workplace automation. McKinsey’s “ Jobs lost, jobs gained ” report 22 For more information, see “ Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages ,” McKinsey Global Institute, November 28, 2017. suggests India may need 34 million to 100 million more high school graduates by 2030 to fill workplace demands. The pandemic has put existing high school graduation rates at risk, let alone the vast expansion required to meet future demand for workers.

The pandemic’s effects beyond learning

Much of the dialogue around school systems focuses on educational achievement, but schools offer more than academic instruction. A school system’s contributions may include social interaction; an opportunity for students to build relationships with caring adults; a base for extracurricular activities, from the arts to athletics; an access point for physical- and mental-health services; and a guarantee of balanced meals on a regular basis. The school year may also enable students to track their progress and celebrate milestones. When schools had to close for extended periods of time or move to hybrid learning, students were deprived of many of these benefits.

The pandemic’s impact on the social-emotional and mental and physical health of students has been measured even less than its impact on academic achievement, but early indications are concerning. Save the Children reports that 83 percent of children and 89 percent of parents globally have reported an increase in negative feelings since the pandemic began. 23 The hidden impact of COVID-19 on child protection and wellbeing , Save the Children International, September 2020. In the United States, one in three parents said they were very or extremely worried about their child’s mental health in spring 2021, with rising reported levels of student anxiety, depression, social withdrawal, and lethargy. 24 Emma Dorn, Bryan Hancock, Jimmy Sarakatsannis, and Ellen Viruleg, “ COVID-19 and education: The lingering effects of unfinished learning ,” McKinsey, July 27, 2021. Parents of Black and Hispanic students, the segments most affected by academic unfinished learning, also reported higher rates of concern about their student’s mental health and engagement with school. A UK survey found 53 percent of girls and 44 percent of boys aged 13 to 18 had experienced symptoms or trauma related to COVID-19. 25 Report1: Impact of COVID-19 on young people aged 13-24 in the UK- preliminary findings , PsyArXiv, January 20, 2021. In Bangladesh, a cross-sectional study revealed that 19.3 percent of children suffered moderate mental-health impacts, while 7.2 percent suffered from extreme mental-health effects. 26 Rajon Banik et al., “Impact of COVID-19 pandemic on the mental health of children in Bangladesh: A cross-sectional study,” Children and Youth Services Review , October 2020, Volume 117. Reports of violence against children rose in many countries. 27 “Publications,” Young Lives, accessed March 22, 2022. The pandemic affected physical health as well. Studies from the United States 28 Roger Riddell, “CDC: Child obesity jumped during COVID-19 pandemic,” K-12 Dive , September 24, 2021. and the United Kingdom 29 The annual report of Her Majesty’s chief inspector of education, children’s services and skills 2020/21 , Ofsted, December 7, 2021. show rising rates of childhood obesity. In Latin America and the Caribbean, more than 80 million children stopped receiving hot meals. 30 “We can move to online learning, but not online eating,” United Nations World Food Program, March 26, 2020. In Uganda, a record number of monthly teenage pregnancies—more than 32,000—were recorded from March 2020 to September 2021. 31 “Uganda overwhelmed by 32,000 monthly teen pregnancies,” Yeni Şafak , December 12, 2021.

Some students may never return to formal schooling at all. Even in high-income systems, levels of chronic absenteeism are rising, and some students have not reengaged in school. In the United States, 1.7 million to 3.3 million eighth to 12th graders may drop out of school because of the pandemic. In low- and middle-income countries, the situation could be far worse. Up to one-third of Ugandan students may not return to the classroom. This pattern is in line with past historical crises involving school closures. After the Ebola pandemic, 13 percent of students in Sierra Leone and 25 percent of students in Liberia dropped out of school, with girls and low-income students most affected. 32 The socio-economic impacts of Ebola in Liberia , World Bank, April 15, 2015; The socio-economic impacts of Ebola in Sierra Leone , World Bank, June 15, 2015. Among the poorest primary-school students in Sierra Leone, dropout rates increased by more than 60 percent. 33 William C. Smith, “Consequences of school closure on access to education: Lessons from the 2013-2016 Ebola pandemic,” International Review of Education , April 2021, Volume 67. This may result in reduced employment opportunities and lifelong earnings potential for many of these students.

The potential of long-term economic damage

Education can affect not just an individual’s future earnings and well-being but also a country’s economic growth and vitality. Research suggests higher levels of education lead to increased labor productivity and enhance an economy’s capacity for innovation. Unless the pandemic’s impact on student learning can be mitigated and students can be supported to catch up on missed learning, the global economy could experience lower GDP growth over the lifetime of this generation.

We estimate by 2040, unfinished learning related to COVID-19 could translate to annual losses of $1.6 trillion to the global economy, or 0.9 percent of predicted total GDP (Exhibit 6).

Although the total dollar amount of forgone GDP is highest in the largest economies of the world (encompassing East Asia, Europe, and North America), the relative impact is highest in regions with the greatest learning delays. In Latin America and the Caribbean, pandemic-related school closures could result in losses of more than 2 percent of GDP annually by 2040 and in subsequent years.

Economic impact could be affected further if students don’t return to school and cease learning altogether.

Identifying potential solutions

The response to the learning crisis will likely vary from country to country, based upon preexisting educational performance, the depth and breadth of learning delays, and system resources and capacity to respond. That said, all school systems will likely need to plan across multiple horizons:

As 2022 began, more than 95 percent of school systems around the world were at least partially open for traditional in-person learning. 34 “Responses to Educational Disruption Survey (REDS),” UNESCO, 2022, accessed March 11, 2022. That progress is encouraging but tenuous. Many systems reopened only to close down again when another wave of COVID-19 caused additional disruptions. Even within partially open systems, not all students have access to in-person learning, and many are still attending partial days or weeks. Building resilience could mean ensuring protocols are in place for safe and supportive in-person learning, and ensuring plans are in place to provide remote options that support the whole child at the system, school, and student levels in response to future crises. School systems can also benefit by creating the flexibility to change policies and procedures as new data and circumstances arise.

COVID-19 and education: The lingering effects of unfinished learning

Reenrollment.

Opening buildings and embedding effective safety precautions have been challenging for many systems, but ensuring students and teachers actually turn up and reengage with learning is perhaps even more difficult. Even where in-person learning has resumed, many students have not returned or remain chronically absent. 35 Indira Dammu, Hailly T.N. Korman, and Bonnie O’Keefe, Missing in the margins 2021: Revisiting the COVID-19 attendance crisis , Bellwether Education Partners, October 21, 2021. Families may still have safety worries about in-person learning. Some students may have found jobs and now rely on that income. 36 Elias Biryabarema, “Student joy, dropout heartache as Uganda reopens schools after long COVID-19 shutdown,” Reuters, January 10, 2022. Others may have become pregnant or now act as caregivers at home. 37 Brookings Education Plus Development , “What do we know about the effects of COVID-19 on girls’ return to school?,” blog entry by Erin Ganju, Christina Kwauk, and Dana Schmidt, September 22, 2021. Still others may feel so far behind academically or so disconnected from the school environment at a social level that a return feels impossible. A multipronged approach could be helpful to understand the barriers students may face, how those could differ across student segments, and ways to support all students in continuing their educational journeys.

Systems could consider a tiered approach to support reengagement. Tier-one interventions could be rolled out for all students and include both improving school offerings for families and students and communicating about enhanced services. This might involve back-to-school awareness campaigns at the national and community levels featuring respected community members, clear communication of safety protocols, access to free food and other basic needs on campuses, and the promotion of a positive school climate with deep family engagement.

Tier-two interventions, which could be directed at students who are at heightened risk of not returning to school, may involve more targeted support. These efforts might include community events and canvassing to bring school buses or mobile libraries to historically marginalized neighborhoods, phone- or text-banking aimed at students who have not returned to school, or summer opportunities (including fun reorientation activities) to convince students to return to the school campus. At the student level, it could include providing some groups of students with deeper learning or social-emotional recovery services to help them reintegrate into school.

Tier-three interventions encompass more intensive and specialized support. These efforts may include visits to the homes of individual students or new educational environments tailored to student needs—for example, night schools for students who need to complete high school while working.

Once students are back in school, many may need support to recover from the academic and social-emotional effects of the pandemic. Indeed, while academic recovery seems daunting, supporting the mental-health and social-emotional needs of students may end up being the bigger challenge. 38 Protecting youth mental health: The U.S. surgeon general’s advisory , U.S. Department of Health and Human Services, 2021. This process starts with a recognition that each child is unique and that the pandemic has affected different students in different ways. Understanding each student’s situation, in terms of both learning and well-being, is important at the classroom level, with teachers and administrators trained to interpret cues from students and refer them to more intensive support when necessary. Assessments will likely also be needed at the school and system levels to plan the response.

With an understanding of both the depth and breadth of student needs, systems and schools could consider three levers of academic acceleration: more time, more dedicated attention, and more focused content. Implementation of these levers will likely vary by context, but the overall goals are the same: to overcome both historical gaps and new COVID-19-related losses, and to do so across academic and whole-child indicators.

In high-income countries, digital formative assessments could help determine in real time what students know, where they may have gaps, and what the next step could be for each child. More relational tactics can be incorporated alongside digital assessments, such as teachers taking the time to connect with each child around a simple reading assessment, which may rebuild relationships and connectivity while assessing student capabilities. Schools could also consider universal mental-health diagnostics and screeners, and train teachers and staff to recognize the signs of trauma in students.

Once schools have identified students who need academic support, proven, evidence-based solutions could support acceleration in high-income school systems. High-dosage tutoring, for example, could enable students to learn one to two additional years of mathematics in a single year. Delivered three to five times a week by trained college graduates during the school day on top of regular math instruction, this type of tutoring is labor and capital intensive but has a high return on investment. Acceleration academies, which provide 25 hours of targeted instruction in reading to small groups of eight to 12 students during vacations, have helped students gain three months of reading in just one week. Exposing students to grade-level content and providing them with targeted supports and scaffolds to access this content has improved course completion rates by two to four times over traditional “re-teaching” remediation approaches.

With an understanding of both the depth and breadth of student needs, systems and schools could consider three levers of academic acceleration: more time, more dedicated attention, and more focused content.

In low- and middle-income countries, where learning delays may have been much greater and where the financial and human-capital resources for education can be more limited, different implementation approaches may be required. Simple, fast, inexpensive, and low-stakes evaluations of student learning could be carried out at the classroom level using pen and paper, oral assessments, and mobile data collection, for example.

Solutions for supporting the acceleration of student learning in these contexts could start with ensuring foundational literacy and numeracy (FLN), prioritizing essential standards and content. Evidence-based teaching methods could speed up learning; for example, Pratham’s Teaching at the Right Level (TaRL) approach—which groups children by learning needs, rather than by age or grade, and dedicates time to basic skills with continual reassessment—has led to improvements of more than a year of learning in classrooms and summer camps. 39 Improvements of 0.2 to 0.7 standard deviations; assuming that one year of learning ranges from 0.2 of a standard deviation in low income countries and 0.5 of a standard deviation in high income countries, in accordance with World Bank assumptions:; João Pedro Azevedo et al., Simulating the potential impacts of COVID-19 school closures on schooling and learning outcomes , World Bank working paper 9284, June 2020; David K. Evans and Fei Yuan, Equivalent years of schooling , World Bank working paper 8752, February 2019. Even with the application of existing approaches, more time in class may be required—with options to extend the school year or school day to support students. Widespread tutoring may not be realistic in some countries, but peer-to-peer tutoring and cross-grade mentoring and coaching could supplement in-class efforts. 40 COVID-19 response–remediation: Helping students catch up on lost learning, with a focus on closing equity gaps , UNESCO, July 2020.

Reimagining

In addition to accelerating learning in the short term, systems can also use this moment to consider how to build better systems for the future. This may involve both recommitting to the core fundamentals of educational excellence and reimagining elements of instruction, teaching, and leadership for a post-COVID-19 world. 41 Jake Bryant, Emma Dorn, Stephen Hall, and Frédéric Panier, “ Reimagining a more equitable and resilient K-12 education system ,” McKinsey, September 8, 2020. A lot of ground could be covered by rolling out existing evidence-based interventions at scale—recommitting to core literacy and numeracy skills, high-quality instructional materials, job-embedded teacher coaching, and effective performance management. Recommitting to these basics, however, may not be enough. Systems can also innovate across multiple dimensions: providing whole-child supports, using technology to improve access and quality, moving toward competency-based learning, and rethinking teacher preparation and roles, school structures, and resource allocation.

For example, many systems are reemphasizing the importance of caring for the whole child. Integrating social-emotional learning for all students, providing trauma-informed training for teachers and staff, 42 “Welcome to the trauma-informed educator training series,” Mayerson Center for Safe and Healthy Children, accessed March 22, 2022. and providing counseling and more intensive support on and off campus for some students could provide supportive schooling environments beyond immediate crisis support. 43 “District student wellbeing services reflection tool,” Chiefs for Change, January 2022. A UNESCO survey suggests that 78 percent of countries offered psychosocial and emotional support to teachers as a response to the pandemic. 44 What’s next? Lessons on education recovery , June 2021. Looking forward, the State of California is launching a $3 billion multiyear transition to community schools, taking an integrated approach to students’ academic, health, and social-emotional needs in the context of the broader community in which those students live. 45 John Fensterwald, “California ready to launch $3 billion, multiyear transition to community schools,” EdSource, January 31, 2022.

The role of education technology in instruction is another much-debated element of reimagining. Proponents believe education technology holds promise to overcome human-capital challenges to improved access and quality, especially given the acceleration of digital adoption during the pandemic. Others point out that historical efforts to harness technology in education have not yielded results at scale. 46 Jake Bryant, Felipe Child, Emma Dorn, and Stephen Hall, “ New global data reveal education technology’s impact on learning ,” McKinsey, June 12, 2020.

Numerous experiments are under way in low- and middle-income countries where human capital  challenges are the greatest. Robust solar-powered tablets loaded with the evidence-based literacy and numeracy app one billion led to learning gains of more than four months 47 “Helping children achieve their full potential,” Imagine Worldwide, accessed March 22, 2022. in Malawi, with plans to roll out the program across the country’s 5,300 primary schools. 48 “Partners and projects,” onebillion.org, accessed March 22, 2022. NewGlobe’s digital teacher guides provide scripted lesson plans on devices designed for low-infrastructure environments. In Nigeria, students using these tools progressed twice as fast in numeracy and three times as fast in literacy as their peers. 49 “The EKOEXCEL effect,” NewGlobe Schools, accessed March 22, 2022. As new solutions are rolled out, it will likely be important to continually evaluate their impact compared with existing evidence-based approaches to retain what is working and discard that which is not.

Charting a potential path forward

There is no precedent for global learning delays at this scale, and the increasing automation of the workforce advances the urgency of supporting students to catch up to—and possibly exceed—prepandemic education levels to thrive in the global economy. Systems will likely need resources, knowledge, and organizational capacity to make progress across these priorities.

Even before COVID-19, UNESCO estimated that low- and middle-income countries faced a funding gap of $148 billion a year to reach universal preprimary, primary, and secondary education by 2030 as required by UN Sustainable Development Goal 4. As a result of the pandemic, that gap has widened to $180 billion to $195 billion a year. 50 Act now: Reduce the impact of COVID-19 on the cost of achieving SDG 4 , UNESCO, September 2020. Even if that funding gap were closed, the result would be increased enrollment, not improvements in learning. UNESCO estimates that just 3 percent of global stimulus funds related to COVID-19 have been directed to education , 97 percent of which is concentrated in high-income countries. 51 “Uneven global education stimulus risks widening learning disparities,” UNESCO, October 19, 2021.

In many countries, shortages of teachers and administrators are just as pressing as the lack of funding. Many teachers in Uganda weren’t paid during the pandemic and have found new careers. 52 Alon Mwesigwa, “’I’ll never go back’: Uganda’s schools at risk as teachers find new work during Covid,” Guardian , September 30, 2021. Even high-income countries are grappling with teacher shortages. In the United States, 40 percent of district leaders and principals describe their current staff shortages as “severe” or “very severe.” 53 Mark Lieberman, “How bad are school staffing shortages? What we learned by asking administrators,” EducationWeek , October 12, 2021. Fully addressing pandemic-related learning losses will require a full accounting of the cost and a long-term commitment, recognizing the critical importance of investments in education for future economic growth and stability.

Countries do not need to reinvent the wheel or go it alone. Many existing resources catalog evidence-based practices relevant to different contexts, both historical approaches and those specific to COVID-19 recovery. For high-income countries, the Education Endowment Foundation, Annenberg’s EdResearch for Recovery platform, and the Collaborative for Student Success resources for states and districts in the United States provide research-based guidance on solutions.

In many countries, shortages of teachers and administrators are just as pressing as the lack of funding.

For low- and middle-income countries, materials developed in partnership with UNESCO, UNICEF, and the World Bank include tools to support FLN, Continuous and Accelerated Learning, and teacher capacity (Teach and Coach). UNESCO’s COVID-19 Response Toolkit provides guidance across income levels. Collaboration across schools, regions, and countries could also promote knowledge sharing at a time of evolving needs and practices—from webinars to active communities of practice and shared-learning collaboratives.

Organizing for the response across these multiple levels is a challenge even for the most well-resourced and sophisticated systems. Our recent research found 80 percent of government efforts to transform performance don’t fully meet their objectives. 54 “ Delivering for citizens: How to triple the success rate of government transformations ,” McKinsey, May 31, 2018. Success will likely require a relentless focus on implementation and execution, with multiple feedback loops to achieve continuous learning and improvement.

The COVID-19 pandemic was indisputably a global health and economic crisis. Our research suggests it also caused an education crisis on a scale never seen before.

The pandemic also showed, however, that innovation and collaboration can arise out of hardship. The global education community has an opportunity to come together to respond, bringing evidence-based practices at scale to every classroom. Working together, donors and investors, school systems and districts, principals and teachers, and parents and families can ensure that the students who endured the pandemic are not a lost generation but are instead defined by their resilience.

Jacob Bryant is a partner in McKinsey’s Seattle office; Felipe Child is a partner in the Bogotá office, where Jose Espinosa is an associate partner; Emma Dorn is a senior expert in the Silicon Valley office; Stephen Hall is a partner in the Dubai office, where Dirk Schmautzer is a partner; Topsy Kola-Oyeneyin is a partner in the Lagos office; Cheryl Lim is a partner in the Singapore office; Frédéric Panier is a partner in the Brussels office; Jimmy Sarakatsannis is a senior partner in the Washington, DC, office; and Seckin Ungur is a partner in the Sydney office, where Bart Woord is an associate partner.

The authors wish to thank Annie Chen, Kunal Kamath, An Lanh Le, Sadie Pate, and Ellen Viruleg for their contributions to this article.

Explore a career with us

Related articles.

Reimagining a more equitable and resilient K–12 education system

COVID-19 and education: An emerging K-shaped recovery

Teacher survey: Learning loss is global—and significant

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

Student’s experiences with online teaching following COVID-19 lockdown: A mixed methods explorative study

Roles Conceptualization, Data curation, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation Faculty of Health Sciences, Department of Nursing and Health Promotion, Oslo Metropolitan University, Oslo, Norway

Roles Conceptualization, Formal analysis, Investigation, Methodology, Writing – review & editing

Roles Formal analysis, Investigation, Methodology, Writing – review & editing

Affiliation Department of Primary and Secondary Teacher Education, Faculty of Education and International Studies, Oslo Metropolitan University, Oslo, Norway

Roles Investigation, Methodology, Writing – review & editing

Roles Data curation, Formal analysis, Investigation, Methodology, Writing – review & editing

• Kari Almendingen, 
• Marianne Sandsmark Morseth, 
• Eli Gjølstad, 
• Asgeir Brevik, 
• Christine Tørris

• Published: August 31, 2021
• https://doi.org/10.1371/journal.pone.0250378
• Reader Comments

The COVID-19 pandemic lead to a sudden shift to online teaching and restricted campus access.

To assess how university students experienced the sudden shift to online teaching after closure of campus due to the COVID-19 pandemic.

Material and methods

Students in Public Health Nutrition answered questionnaires two and 12 weeks (N = 79: response rate 20.3% and 26.6%, respectively) after the lockdown in Norway on 12 March 2020 and participated in digital focus group interviews in May 2020 (mixed methods study).

Findings and discussion

Two weeks into the lockdown, 75% of students reported that their life had become more difficult and 50% felt that learning outcomes would be harder to achieve due to the sudden shift to online education. Twelve weeks into the lockdown, the corresponding numbers were 57% and 71%, respectively. The most pressing concerns among students were a lack of social interaction, housing situations that were unfit for home office purposes, including insufficient data bandwidth, and an overall sense of reduced motivation and effort. The students collaborated well in digital groups but wanted smaller groups with students they knew rather than being randomly assigned to groups. Most students agreed that pre-recorded and streamed lectures, frequent virtual meetings and student response systems could improve learning outcomes in future digital courses. The preference for written home exams over online versions of previous on-campus exams was likely influenced by student’s familiarity with the former. The dropout rate remained unchanged compared to previous years.

The sudden shift to digital teaching was challenging for students, but it appears that they adapted quickly to the new situation. A lthough the concerns described by students in this study may only be representative for the period right after campus lockdown, the study provide the student perspective on a unique period of time in higher education.

Citation: Almendingen K, Morseth MS, Gjølstad E, Brevik A, Tørris C (2021) Student’s experiences with online teaching following COVID-19 lockdown: A mixed methods explorative study. PLoS ONE 16(8): e0250378. https://doi.org/10.1371/journal.pone.0250378

Editor: Mohammed Saqr, KTH Royal Institute of Technology, SWEDEN

Received: September 30, 2020; Accepted: April 6, 2021; Published: August 31, 2021

Copyright: © 2021 Almendingen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The Coronavirus 2019 (COVID-19) pandemic has caused extraordinary challenges in the global education sector [ 1 , 2 ]. Most countries temporarily closed educational institutions in an attempt to contain the spread of the virus and reduce infections [ 3 ]. In Norway, the move to online teaching and learning methods accelerated as a consequence of the physical closure of universities and university colleges on 12 March 2020 [ 4 ]. Education is better implemented through active, student-centered learning strategies, as opposed to traditional educator-centered pedagogies [ 5 , 6 ]. At the time of the COVID-19 outbreak, the decision to boost the use of active student-centered learning methods and digitalisation had already been made at both the governmental and institutional levels [ 7 , 8 ] because student-active learning (such as use of student response systems and flipping the classroom) increase motivation and improve learning outcomes [ 5 , 7 , 9 ]. However, the implementation of this insight was lagging behind. Traditional educator-centered pedagogies dominated higher education in Norway prior to the lockdown, and only 30% of academic teachers from higher institutions reported having any previous experience with online teaching [ 4 ]. Due to the COVID-19 lockdown, most educators had to change their approaches to most aspects of their work overnight: teaching, assessment, supervision, research, service and engagement [ 4 , 10 ].

Bachelor’s and master’s in Public Health Nutrition (PHN) represents two small-sized programmes at Oslo Metropolitan University (OsloMet). PHN is defined as ‘the application of nutrition and public health principles to design programs, systems, policies, and environments that aims to improve or maintain the optimal health of populations and targeted groups’ [ 11 , 12 ]. Traditional teaching methods dominated on both programs during winter 2020. Following the lockdown, online learning for the continuation of academic activities and the prevention of dropouts from study programmes in higher education were given the highest priority. Due to an extraordinary effort by both the administrative and academic staff, digital alternatives to the scheduled on-campus academic activities were offered to PHN students already in the first week following lockdown. The scheduled on-campus lectures were mainly offered as live-streamed plenary lectures lasting 30–45 minutes, mainly using the video conferencing tool Zoom. Throughout the spring semester educators received training in digital teaching from the institution and increasingly made use of online student response systems (such as Padlet and Mentimeter) as well as tools to facilitate digital group-work (Zoom/Microsoft Teams). Non-theoretical lectures (e.g. cooking classes), were cancelled, and face-to-face exams were re-organized into digital alternatives in order to ensure normal teaching operations. Several small tweaks were employed to minimize dropout. There was no time for coordinating the different courses with regards to the types of online teaching activities, exams and assessments. Social media, i.e Facebook, and SMS were the primary communication channels the first week after lockdown. The use of learning management systems (LMS) Canvas and digital assessment system, Inspera, remained mainly unchanged. Due to the new situation, the deadline for the submission of bachelor theses was postponed by 48 hours. In addition, bachelor students submitting their thesis where given permission to use the submission deadline for the deferred exam in August as their ordinary exam deadline. The deadline for the submission of master theses was extended by one week, but all planned master exams were completed by the end of June, including oral examinations using Zoom instead of the traditional face-to-face examinations on campus. Even though most of the new online activities where put in place with limited regard for subtle nuances of pedagogical theory, and did not allow for much student involvement, the dropout rate from PHN programs remained unchanged compared to previous years. PHN is a small-sized education with close follow up of students. However, although the students experienced a digital revolution overnight, we know little about how they experienced the situation after the university closed for on-campus activities.

Accordingly, the purpose of this study was to assess how Norwegian PHN students experienced the shift to digital teaching following campus lockdown. Students were also asked to provide feedback on what might improve the learning outcomes in future online lectures and courses.

Design and sampling

This study utilised a mixed methods cross-sectional design, where quantitative and qualitative methods complemented each other. An invitation to participate was sent out to 79 eligible students via multiple channels (Facebook, Teams, Zoom, LMS Canvas, SMS), with several reminders. The only eligibility criteria was being a student in PHN during spring 2020. All students received the quantitative survey. Due to few students eligible for each focus group interview, all who wanted to participate were interviewed/included. The invited students were in their second-year (n = 17) and third-year (n = 28) bachelor’s and first-year (n = 13) and second-year (n = 21) master’s programme at PHN in the Faculty of Health Sciences at OsloMet. The response rate was 16/79 (20.3%) and 21/79 (26.6%). Two focus group interviews were scheduled in each class (a total of 8) but only 4 interviews were conducted. The research team was heterogeneously composed of members with both pedagogical and health professional backgrounds.

Online questionnaire

To the best of our knowledge, this study was the first “corona” study at our Faculty. No suitable national or international questionnaire had been developed and /or validated by March 2020. Hence, online questionnaires for the present study were designed virtually ‘over-night’. The questions were however based on experiences from a large-scale interprofessional learning course using the blended learning approach at OsloMet [ 13 , 14 ] and specific experiences that academic staff in Norway reported during the first week of teaching during the lockdown [ 4 ]. The questionnaires were based on an anonymous self-administrated web survey ‘Nettskjema’ [ 15 ]. ‘Nettskjema’ is a Norwegian tool for designing and conducting online surveys with features that are customised for research purposes. It is easy to use, and the respondents can submit answers from a browser on a computer, mobile phone or tablet. During the first week after lockdown, the questionnaire was sent out to university colleagues and head of studies and revised accordingly. The questionnaires were deliberately kept short because the response rate is generally low in student surveys [ 16 ]. Ideally, we should have pretested and validated the questionnaires, but this was not possible within the short-time frame after lockdown. Items were measured on a five-level ordinal scale (Likert scale 0–5). The two forms contained both numerical and open questions, permitting both quantitative and qualitative analyses. The first questionnaire was sent out to the students on 25 March 2020 (two weeks after the closure of university campus; students were asked to submit their answers during the period from 12 March until the link was closed at Easter Holiday), and the second questionnaire was sent on 3 June 2020 (12 weeks after closure; students were asked to submit their answers during the period after Easter and until the end of the spring semester). The questionnaires were distributed as web links embedded in the LMS Canvas application. Because live-streamed lectures were offered primarily through Zoom during the first weeks, students were not asked about interactive digital teaching and tools in the first questionnaire. At the end of both questionnaires, the students were asked what they believed could improve the learning experience in future online education. The qualitative part consisted of text answers to open questions from the two electronic questionnaires.

Digital focus group interview

To capture meaningful insights into the participants experiences, we conducted digital focus group interviews [ 17 ], aiming to conduct one digital focus group interview in each class. PHN is a small sized education, and the teachers know all the students. The focus group interviews were therefore performed by two external independent researchers (EG and CT) who are not directly involved in the PHN education and had no prior knowledge to the students. The two interviewers (moderators) were middle-aged female teachers working in the university, and both have significant experience in digitalizing education. They were presented to the participants as researchers from the university. The report of this study was guided by the consolidated criteria for reporting qualitative research (COREQ). The interviews were conducted via the video conferencing system Zoom during May 2020, following internal guidelines [ 18 ]. In the focus group interviews, the participants reflected on their own experiences, and the moderator guided the discussion using a semi-structured interview guide. This guide was prepared based on the research questions. One pilot interview was conducted, which resulted in some minor changes to the interview guide. The results from the pilot interview are not included in the results. The focus group interviews lasted for approximately one hour, and five students were invited to each focus group interview. The interviews were not recorded, but the moderator took notes, ensuring that the participants remained anonymised.

Data analysis

Quantitative data are described descriptively with numbers and percentages. Apart from re-categorization of response categories, no statistical analysis was performed. Quantitative data were extracted directly from the survey system. Answers in categories 0 or 1 were categorised as ‘Disagree/slightly agree’, answers in categories 2 or 3 were categorised as ‘Somewhat agree’ and answers in categories 4 or 5 were categorised as ‘Agree’. Qualitative data were analysed using systematic text condensation (STC), inspired by Giorgi’s phenomenological approach and modified by Malterud [ 17 ]. First, the entire texts (from the interviews) were read to get an overall impression, and preliminary themes were derived from the interviews. Then, meaning units, such as sentences and words, were identified and connected with the preliminary theme to elucidate the study question. The meaning units were then coded and systemized into groups, so that meaning could be abstracted from the different code groups. Finally, the meanings of the various units were summarised. The qualitative data from the questionnaire were then extracted by the moderators, and the words and sentences were identified and abstracted. In order to ensure quality, the notes from the focus group interviews and the text answers from the questionnaires were reviewed by both moderators.

Ethical considerations

All participants gave their informed consent. The questionnaires did not include questions about personal health information or sensitive data. The quantitative data were collected through an anonymous web survey using ‘Nettskjema’ [ 15 ]. Internal routines at OsloMet for using Zoom in research interviews were applied [ 18 ]. In the interviews, the participants provided their written consent in the chat without their names and remained anonymous. The data protection was approved by the Norwegian Centre for Research Data (NSD, reference no. 846363), as PHN is a small-sized study programme and because Zoom was used for the digital focus group interviews.

Quantitative data

There were 16 (20.3%) and 21 (26.6%) students who answered the questionnaires two and 12 weeks after lockdown, respectively ( Table 1 ). Both samples had an even distribution of bachelor and master students.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0250378.t001

Among the respondents two and 12 weeks after lockdown, 7/16 students (44%) and 9/21 students (43%) reported having previous experience with online learning, respectively ( Table 1 ). After two weeks of forced online education, 8/16 students (50%) expected that their learning outcomes would be inferior with online education compared to their pre-COVID-19 education at campus. After 12 weeks, 15/ 21 students (71%) expected that their learning outcome would be lower, and, notably, none of the students expected that it would be higher. On both occasions, most students reported that studying had become more difficult compared to the time before the pandemic.

Several of the identified challenges with online education were reported by more than 50% of the students, and there was an uneven spread across categories of answers (Tables 2 and 3 ). Only one of 16 students (6%) agreed that they needed to increase their digital competence, but approximately half reported having technical challenges at home. All of the students agreed that the lack of contact with other students was a challenge. However, after 12 weeks, the lack of contact with academic staff seemed to pose less of a challenge.

https://doi.org/10.1371/journal.pone.0250378.t002

https://doi.org/10.1371/journal.pone.0250378.t003

After 12 weeks, 20/21 students (95%) agreed that their motivation and effort had been reduced. At the same time, all students wanted to return to campus. Only 5/21 (24%) reported that their learning outcomes had not deteriorated.

Suggestions for how to increase learning outcome in future digital courses

Two weeks after lockdown, most students answered that the use of different components of online education would improve the learning outcomes in a future online course ( Table 4 ). Regarding participation in digital group work, there was a nearly even spread across the different categories of answers. Finally, participants preferred written home exams and feedback over the digital options suggested ( Table 5 ).

https://doi.org/10.1371/journal.pone.0250378.t004

https://doi.org/10.1371/journal.pone.0250378.t005

After 12 weeks of (forced) online teaching, more ambivalence toward the use of digital learning tools could be detected ( Table 6 ). However, the proportion of students who agreed that digital group work would increase the learning outcomes seemed unchanged (around 1/3 of both samples). In line with the findings obtained only two weeks after lockdown, written submissions and feedback seemed to be preferable to digital exam options ( Table 7 ).

https://doi.org/10.1371/journal.pone.0250378.t006

https://doi.org/10.1371/journal.pone.0250378.t007

After 12 weeks, 16/21 students (76%) agreed that social interaction plays a role in learning outcomes and well-being ( Table 8 ), and an equal proportion agreed that it was important that everyone had their camera on during teaching.

https://doi.org/10.1371/journal.pone.0250378.t008

There were 15/21 students (71%) who agreed that their digital competence and interest in digital teaching methods had increased while 6/21 students (29%) disagreed with this statement.

Qualitative data

In total, there were four master students who participated in digital focus group interviews (on two different occasions, with three students and one student in the groups, respectively).

Digital lectures.

The students were satisfied with the teaching and reported that the lecturers were competent in arranging online teaching. The lecturers were also good at adapting to the students’ wishes regarding teaching. Lectures that were streamed live (synchronous classes) were preferred over recordings (asynchronous). One student said it was a privilege to still be able to study even though the university campus was closed due to corona and all the lectures were digital. The students expressed that it is an advantage if the lecturer has digital competence to ensure that the lecture runs smoothly without digital/technical problems, or if there is a co-host who can assist. Technical competence is also important when invitation links are sent out. It signals that the student group is well taken care of. The informants described a course co-ordinator as a person with a good overview and sense of responsibility—someone who is good at structure and order. These qualities were highlighted as important in a fully digitalised teaching program.

The students did not support compulsory attendance, as it would reduce the feeling of freedom that most students value. If learning activities were compulsory, students felt it might also present challenges in dealing with their children and part-time work. The students expressed that most of their fellow students were present in lectures that went live on Zoom. One student stated that live digital lectures were best because it was easier to ask questions. When using a flipped classroom or recordings, the questions must be written down and asked afterwards, but both options (flipped classroom and live streaming) were perceived as fine.

Interestingly, the qualitative results from the questionnaire indicated that some students found it easy to ask questions, while others thought it had become more difficult. According to one student, ‘As long as we have the opportunity to ask questions online, I think it will go just fine. I commute three hours per school day to get to and from school, so I feel I have more time to work with school now that the lecture is online’.

One of the informants thought that interaction was challenging, and it did not feel as natural to ask questions in online classes. ‘Raising your hand’ was not perceived to be as easy as in the face-to-face setting on campus, which could mean that the students did not always get answers to their questions.

The students’ indicated that recorded lectures should not be longer than one hour, as it is easy to lose focus, and one must rewind the recordings. For live online lectures, two hours was deemed fine, and they were perceived as fun to watch. However, each session of the live online lectures should not be longer than 45 minutes.

The online teaching (mainly in the form of synchronous plenum lectures originally intended as on-campus lectures) was challenging in the beginning because some students fell out of the digital rooms due to technical reasons, but it got better over time. Some students experienced poor bandwidth, which led to them not being able to turn on their camera and reduced sound quality. One student stated that poor internet quality was something he could not do anything about, but it resulted in a non-optimal learning situation. It was suggested that using a flipped classroom/recorded lectures in the first weeks after lockdown could have solved this problem.

The respondents pointed out that the use of several conference systems/channels in addition to LMS Canvas provided a poor overview and ineffective communication, and they would prefer a single learning platform. The students were unsure how to contact their teachers in the first weeks after lockdown due to the use of several platforms. Even with a single contact channel (LMS), the students found that the threshold barrier for sending questions to the teacher through email was high.

When asked what they thought about ‘black screens’ (students turning off the camera), several answered that this reduced the quality of communication between the lecturer and student. The lecturer missed affirmative nods from students, and the students also likely missed parts of the communication when the camera was turned off. In some of the lectures, all of the students were encouraged to keep the camera on, and some of the lecturers asked the students questions to initiate two-way communication. The students expressed that it was nice to see the other attending students on video. Furthermore, the participants felt that the lecturers mainly engaged the students who had their camera on. However, several students said that they turned off their cameras during the lectures because the session was being recorded. Another stated that having the camera on was particularly useful when having discussions in digital groups. The students who participated in the survey wished for more recorded lectures, indicating that their lecturers did not do this often.

One of the informants assumed that she would have turned off the camera when recording the lecture, and she thought she had not contributed much. She would have to consider whether a question was ‘stupid’ before asking it, and probably she had not asked any questions at all. She thought this was due to habit, and she indicated that one might get used to being recorded. That is, if recording had been the norm and she had become accustomed to it, it would have been easier to relate to.

All of the informants agreed that presentations with audio were useful, as the material could be repeated by rewinding to the desired location. They also reported that it sometimes took a while for the teachers to post such files, even though the students found these learning resources very useful.

They noticed an increased attendance rate among their peers in the online lectures, which they perceived as positive. The reason for the increased attendance, they believed, was that many students have to make a long trip to attend class, and the threshold for participating had become lower now that all teaching was online. This was supported by the qualitative results from the questionnaire, where a student said, ‘I commute several hours per school day to get to and from school, so I feel I have more time to work with school now that the lecture is online’.

However, one of the informants pointed out that it is important for students to be able to talk to each other when the lecturer is not present, that group activities should be arranged and that they should be provided with opportunities for voluntary meetings on campus in their spare time. One of the informants believed it to be important that the students themselves have a responsibility to address the learning environment and initiate meetings in both academic and social arenas. One felt that it was not desirable that the university was responsible for social contact between peers. It was suggested that time could be set aside, for example, after teaching, so that only students could talk together. It was expressed that in order to preserve social aspects in digital teaching and learning, the first meeting should be on campus. A mentor scheme was suggested, where former students could give tips and advice on how to function as a ‘digital student’.

Digital group work.

The students expressed that they mainly collaborated well in digital groups (breakout rooms). Communication usually worked well with both the teacher and peers in these digital rooms. Nevertheless, some students reported that group work was not effective when it was carried out in ‘breakout rooms’. The students felt that the allocated time for group work was too short for collaboration, and some of the time was spent on technical challenges. There were also some students who withdrew from the group work, which the respondents believed was because some were shy. One student said that discussions during group work paid off and that communication worked well, but it was a pity that so few students participated. Getting to know the others in the group well was also deemed to be important for the level of collaboration and professional discussions. The students did not like to be randomly assigned into groups. However, they expressed that it would be advantageous to plan for more group work in smaller groups.

Another positive effect of online teaching the students highlighted was the increased amount of written feedback from lecturers on work submitted voluntarily. The students perceived that this was offered as a compensation for shorter teaching sessions.

One of the respondents thought that it was important to socially interact with peers and missed having lunch with fellow students. Others felt that there had not been many social gatherings in the group previously, and so they did not experience the absence of fellow students as a great loss. They also pointed out that students who had met each other physically at an earlier time had a different starting point in online meetings and for online education. One student stated, ‘Getting to know new peers digitally feels weird’. Furthermore, one of the informants pointed out that most people have a general need for physical contact, and that touching and eye-to-eye contact is important.

Motivation.

Some of the students were more motivated to participate in online learning activities, yet it was perceived to require greater effort to stay motivated and ‘in the course’. Some students work alongside their studies and thus do not attend classes, and others have children who must be tended to. Some indicated that student response systems such as Mentimeter, Quizlet, Padlet, Kahoot! and the use of polls was motivating factors, but it depended on the context in which they were used. Some of the students reported that they especially liked Kahoot, but it was important that the use of such response systems was done in a structured way. They expressed that they liked the teaching programme, which consisted of an introductory video and teaching in which the basics were presented, followed by group work and finally teaching, where the teacher went more in depth. This approach made it easier to follow the teaching and to ask questions.

The students said it was good for motivation when an overview of the course content was published, as it contributed to predictability and more people participate when they know what is planned.

Nevertheless, the qualitative results from the questionnaire indicated that it was difficult to get an overview of everything that needed to be done. It could be challenging to concentrate and have self-discipline due to many distractions, which reduced the students’ motivation. Several students expressed that they felt alone in their studies, and it was difficult to feel alone with the responsibility for learning the curriculum. One student wrote that there was considerable uncertainty, which negatively affected concentration, and that the COVID-19 crises was a difficult time for everyone.

Overall, these students were satisfied with the ad hoc online teaching after the lockdown, although they experienced self-perceived reduced learning outcomes compared to the pre-pandemic situation. It appears that they adapted quickly to the new situation, but they also reported difficulties with the transition to new teaching methods. Based on both the surveys and interviews, the most pressing concerns among students were a lack of social interaction, housing situations that were unsuitable for home office purposes, including insufficient data bandwidth, and a sense of reduced motivation and effort. PHN is a small sized education which enables close contact between educators and students. The low student volume might explain why the dropout rate from the bachelor and master programs remained unchanged compared to that in previous years.

Receiving teaching, supervision, exams and assessments solely through online solutions was a new experience for these students. Apart from a 15-credit mandatory bachelor course offered as hybrid learning (7), traditional teaching methods still dominated the bachelor and master study programmes of PHN in winter 2020. Importantly, the students evaluated the ad hoc solutions offered during the chaotic spring of 2020 rather than a well-planned, high-quality online education using student-active methods [ 5 ]. Teachers switched to online teaching without any time to learn the technology, or standard quality online teaching practices [ 4 ]. They had many years of experience teaching in -person, and they had arranged their lessons and interactive elements around this mode of learning. Alternatively, they had very little experience teaching online. The students’ experiences in these online learning environments, which were thrown together at the last minute, are not necessarily indicative of students’ experiences in a quality online course based on principles from Quality Matters online education [ 19 ].

Although the students reported reduced learning outcomes after 12 weeks dominated by synchronous live-streamed lectures lasting for 30–45 minutes on Zoom, they had positive attitudes toward use of digital learning materials and tools in future online courses. For asynchronous lectures, the rule of thumb in online education is less than 10–15 minutes [ 19 ]. Although lectures of 45 minute duration is far beyond what is recommended for digital teaching [ 19 ], the students responded based on their recent experiences where many teachers, for reasons of feasibility, conducted their planned on-campus lectures digitally shortly after lockdown. Some of the students also reported that they especially liked Kahoot, however, since we wanted to keep the research questionnaire short, we did not ask more in detail for concrete digital tools. A pre-corona study from OsloMet reported that physiotherapy students’ attitudes toward a flipped classroom intervention were mainly positive, although the academic outcomes from the final exam were similar to those in previous years [ 20 ]. Further, in a recent large-scale pre-COVID-19 blended learning interprofessional course conducted a few weeks ahead of the lockdown, first-year bachelor’s students at OsloMet reported positive perceptions of the blended learning approach, using only short video clips (less than 10 minutes) [ 21 ]. Approximately 3/4 of the students in that study disagreed that virtual group discussions resulted in better learning outcomes than face-to-face group discussions. The present data do not conflict with the findings from that larger-scale study.

The students expressed in various ways that online teaching with a lack of social interaction leads to worse learning outcomes and lower levels of motivation and well-being. Concerns about lack of face-to-face contact may have been aggravated by the stressful situation, and contentment with teaching methods would likely improve if teachers had been able to integrate the appropriate elements in a fully digitalized course. Face-to-face interactions provide the foundation for social communication, the lack of which can be viewed as a critical disadvantage of online learning [ 5 ]. Face-to-face training may be particular crucial for candidates expected to have communication skills, such as nutritionists [ 11 , 12 , 22 – 24 ]. The ad hoc solutions for teaching offered during the 2020 spring term were thus not in agreement with the suggested conceptual dimensions, which allow students to expand their knowledge beyond the intended learning outcome established by the teacher: motivation and attention [ 5 ].

The students expressed concerns that are common in traditional in‐class teaching as well, and such issues should not be overlooked in online teaching [ 25 , 26 ]: insufficient pre‐class study preparation, limited participation and inadequate depth in class discussions. Quality of education lies in the knowledge, skills and expertise that are conveyed as well as in the manner in which they are communicated and learned [ 7 , 26 ]. In different ways, the students’ responses revolved around central quality aspects, such as learning objectives, content, programme design, adaptation, teaching, work methods, supervision and forms of assessment [ 7 ]. These findings are in agreement with other studies on COVID‐19 and education [ 4 , 25 , 27 ].

The students stated that they received insufficient information about the exams. This is understandable because staff initially did not know how the different exams would be digitally transformed in spring term 2020. Asked about exam preferences students said that they preferred longer written exams at home, over old campus-style exams, with short timelines, adapted to an online format. They also preferred multi-day written home exams over potential alternatives such as video or podcasts, which none of them had tried before. It should be noted that they had limited experience with digital options. Student-produced podcast and video have been used as formative assessment forms at our university [ 14 ], but to lesser extent as formative assessment forms. The preference for written home exams over digital options was thus likely influenced by student’s familiarity with the former since no exams during this time-period were in the form of podcast or video. Feedback and guidance from academic staff have been found to be key aspects of study quality, and good feedback contributes to increased motivation and improved learning outcomes (6). Exam uncertainty causes undue stress, and thus a key recommendation during the transition to online learning is to ensure that all information about exams is communicated to the students clearly and in a timely manner [ 27 ].

‘Black screens’ do not necessarily reflect individuals lack of motivation and attention or embarrassment, but they may reflect a lack of digital training among freshmen or technical issues, such as poor bandwidth. Broadband bandwidth overload issues and a lack of suitable equipment will probably not be significant problems in Norway in the future. The students suggested that both flipped classrooms and live streaming should be used in future online courses. Flipping the classroom [ 9 ] ahead of live streaming, with the possibility for the students to write down questions during the live streaming or afterward in a seminar, increases flexibility. Asynchronous tools may be utilised to support students to work at different times. We cannot overlook the possibility that new students might have needs that differ from those of senior students in terms of getting accustomed to online education. Nevertheless, our date indicates that clarification of expectations constitutes an important success criteria for online teaching, especially when it comes to group work and formative and summative assessment [ 4 , 27 ].

The closure of campus may have unknown implications for society in both the short and long term [ 28 – 30 ], including impacts on educational quality and the mental health of students and academic staff [ 31 ]. If students are unable to study effectively for some unknown reason, it will make online learning ineffective, regardless of educational quality. The situation after the lockdown in Norway was confusing, and many students lost their jobs and moved back in with their parents [ 4 ]. We did not collect person-sensitive data, and thus we know little about these students’ circumstances. The dropout rate remained nearly unchanged among these students as compared to previous years. Being a small-sized education, the staff were able to follow-up each student individually using digital videoconference tools, such as Zoom and Teams. In the future, more sustainable approaches should be developed, for example, by increasing peer-to-peer interactions and through mentoring programs [ 1 ]. Reducing dropout and increasing completion rates was a strategic goal for higher education before the lockdown [ 29 ], and we do not know the impact of the lockdown on future dropout and completion rates. The high dropout rate from Massive Open Online Courses (MOOCs) has been a major concern of researchers and educators over the years [ 32 ]. Although some universities worldwide had already started offering MOOC-based undergraduate degrees before the COVID-19 pandemic [ 32 ], most MOOCs do not lead to degrees. The online courses offered in spring 2020 after the lockdown were mandatory courses leading to degrees, and thus they were not directly comparable to the voluntary MOOCs. However, such issues are premature for consideration in the present study. OsloMet is currently participating both in the future ‘The COVID-19 Multi-Country Student Well-being Study’[ 33 ] and the ‘Corona and Campus’ study [ 34 ]. The ‘Corona and Campus’ study has secondary outcomes related to teaching satisfaction and learning outcomes, and such data will have the power to inform future decision-making [ 30 ]. However, the present data were collected shortly after the national lockdown due to the COVID-19 pandemic on aspects of digitalisation relevant to the (post)-pandemic situation.

Strengths and weaknesses of the study

This study has several strengths. The most important strength is data collection shortly after a national lockdown due to the COVID-19 pandemic. The combined use of both quantitative and qualitative approaches enabled different perspectives to be captured and adds strength to the study. The triangulation allowed us to identify aspects more accurately and helped to offset the weaknesses of each approach alone. Group dynamics in focus group interviews can help bring out nuances in the data material beyond the answers to the predefined quantitative questions in the electronic questionnaires [ 17 ]. Another strength was the research team consisting of both external moderators providing objectivity, lack of vested interest and a fresh perspective, and internal evaluators who were familiar with the education and the students. One limitation is using a questionnaire which was not pre-tested or validated. However, due to time constraints shortly after campus lockdown following the COVID-19 outbreak, it was not possible to perform pre-testing or validation of the instruments used in the present study. Many of the necessary ad hoc changes to the course plans and exams (spring semester 2020) had yet to be made and decided upon when the present study was initiated, even when the first questionnaire was sent out before Easter 2020. The candidates actual achieved learning outcomes and working skills are unknown due to limited opportunities to monitor the quality of their work [ 4 ]. We do not consider it to be relevant to repeat the study, or reuse its instruments, since the acute phase after lockdown is over. PHN is a small-sized education, and the total number of students were only 79 individuals. The stress associated with the unprecedented situation may have contributed to a low response rate. Private circumstances such as poor internet connection, children at home, and lack of an adequate home office may also have contributed to a low response rate. A low response rate is also a limitation in studies performed in a normal situation [ 16 ]. We cannot rule out selection bias in the sample. The students who volunteered for the digital focus group interviews were positive and thorough. In particular, they seemed to reflect on a more general level, not restricted to their own personal situations. However, the range in age among the study participants was representative for the age range of all PHN students, and both bachelor and master students participated in the study. Data are collected from one single university, and the results might not be representative for large sized educations. Since the study is exploratory, we had not planned the data collection in order to test hypotheses. The study seeks to provide a snapshot in time of an evolving situation. Even with some limiting factors we believe the explorative study offers value since it provides a student perspective on an unprecedented black-swan event in higher education.

Conclusions

Although they had little previous experience with online education, these students seemed to adapt quickly to the sudden shift to ad hoc online education due to the COVID-19 pandemic. The most pressing concerns among students were a lack of social interaction, a feeling of being alone in their studies, unfit housing situations for home office purposes, including insufficient data bandwidth, and a sense of reduced motivation and effort. Although our data indicate that face-to-face contact was greatly missed during this time-period, a thoroughly planned online course with numerous contact points between teachers and students would likely have been received more favorably. Finally, the students expressed that they wanted more structure in future digital courses. Due to the very unusual circumstances experienced both by students and teachers in the early stages of national lockdown in Norway, we are hesitant to conclude with regards to students preferences for future online courses.

Supporting information

S1 file. spss file questionnaire 1—please see line 154..

https://doi.org/10.1371/journal.pone.0250378.s001

S2 File. SPSS file Norwegian questionnaire 1—please see line 154.

https://doi.org/10.1371/journal.pone.0250378.s002

S3 File. SPSS file questionnaire 2—please see line 154.

https://doi.org/10.1371/journal.pone.0250378.s003

S4 File. SPSS file Norwegian questionnaire 2—please see line 154.

https://doi.org/10.1371/journal.pone.0250378.s004

S5 File. Structured interview guide–please see line 145.

https://doi.org/10.1371/journal.pone.0250378.s005

Acknowledgments

The authors would like to thank the participating students and the academic and administrative staff at Oslo Metropolitan University for their contributions.

• View Article
• Google Scholar
• 2. UNESCO. Education: From disruption to recovery 2020 [09/09/2020]. Available from: https://en.unesco.org/covid19/educationresponse .
• 3. Tria JZ. The COVID-19 Pandemic through the Lens of Education in the Philippines: The New Normal. International Journal of Pedagogical Development and Lifelong Learning. 2020;1. https://doi.org/10.30935/ijpdll/8311 .
• 4. Langford M, Damşa C. Online Teaching in the Time of COVID-19: Academic Teachers’ Experience in Norway Centre for Experiential Legal Learning (CELL), University of Oslo2020 [cited 2020].
• 5. Lillejord S, Børte K. Learning and Teaching With Technology in Higher Education—a systematic review. 2018.
• 6. Vygotsky LS. Mind in society: the development of higher psychological processes. London: Harvard University Press UK: Gyldendal Akademisk; 1978.
• 7. Ministry of Education and Research. Quality Culture in Higher Education 2017.
• 8. Oslo Metropolitian University. The digital university of the future: Strategy for digital transformation 2018–2024 2018 [17/11/2019]. Available from: https://ansatt.oslomet.no/documents/585743/77463421/Strategy+for+digital+transformation.pdf .
• PubMed/NCBI
• 11. Sisk K CA, Cullinen K Guide for Developing and Enhancing Skills in Public Health and Community Nutrition. Definitions Related to Public Health Nutrition and Community Nutrition 2018 [09/09/2020]. 3rd Ed:[Available from: https://asphn.org/wp-content/uploads/2018/12/Guide-for-Developing-and-Enhancing-Skills-in-Public-Health-and-Community-Nutrition.pdf .
• 12. Academy of Nutrition and Dietetics Academy of Nutrition and Dietetics Definition of Terms List. Approved by Definition of Terms Task Force Quality Management Committee 2020 May 8, 2020 Report No.
• 13. Almendingen K, Saltyte-Benth J., Molin M. Large Scale Blended Learning Design in an Interprofessional Undergraduate Course in Norway: Context Description and Supervisors’ Perspective. The Journal of Research in Interprofessional Practice and Education (JRIPE) 2021;In press.
• 14. Almendingen K, Molin M, Šaltytė Benth J. Large-scale Blended Learning Design in an Undergraduate Interprofessional Course in Norway: Students’ Perspectives from an exploratory study The Journal of Research in Interprofessional Practice and Education (JRIPE) 2021;In press.
• 15. Nettskjema: University of Oslo; 2020. Available from: https://www.uio.no/english/services/it/adm-services/nettskjema/ .
• 16. The Norwegian Agency for Quality Assurance in Education. The students’ judgement 2018 [09/09/2019]. Available from: https://www.nokut.no/en/news/the-students-judgement/ .
• 18. Rutine for bruk av Zoom i forskningsintervjuer (in Norwegian) Oslo Metropolitian University2020 [10/09/2020].
• 19. Quality Matters online education 2021 [09/02/2021]. Available from: https://www.qualitymatters.org/index.php/ .
• 24. Ministry of Health and Care Services. The primary health and care services of tomorrow–localised and integrated. Oslo: Ministry of Health and Care Services; 2015.
• 27. Hjelsvold R, Lorås M, Bahmani A, Nykvist SS, Krokan A. First impressions from educators as NTNU transitions to an online only mode of learning 2020 [20/02/2021]. Available from: https://www.researchgate.net/project/Research-on-Learning-Activities-During-the-Covid-19-Pandemic .
• 30. McCartney M. BMJ Opinion2020. [cited 2020]. Available from: https://blogs.bmj.com/bmj/2020/08/28/margaret-mccartney-we-need-better-evidence-on-non-drug-interventions-for-covid-19/?fbclid=IwAR1jFbFk7lKcrOxIkxo7gaNJM3II6nDia_W6hXs4VWF_DI2vllS9jEqJ-vI .
• 33. University of Antwerpen. The COVID-19 Multi-Country Student Well-being Study Netherlands2020 [29/08/2020]. Available from: https://www.uantwerpen.be/en/research-groups/centre-population-family-health/research2/covid-19-internation/ .
• 34. ClinicalTrials.gov. Assocation Between In-person Instruction and COVID-19 Risk (Campus&Corona) ClinicalTrials.gov2020 [30/8/2020].

• Our Mission

Covid-19’s Impact on Students’ Academic and Mental Well-Being

The pandemic has revealed—and exacerbated—inequities that hold many students back. Here’s how teachers can help.

The pandemic has shone a spotlight on inequality in America: School closures and social isolation have affected all students, but particularly those living in poverty. Adding to the damage to their learning, a mental health crisis is emerging as many students have lost access to services that were offered by schools.

No matter what form school takes when the new year begins—whether students and teachers are back in the school building together or still at home—teachers will face a pressing issue: How can they help students recover and stay on track throughout the year even as their lives are likely to continue to be disrupted by the pandemic?

New research provides insights about the scope of the problem—as well as potential solutions.

The Achievement Gap Is Likely to Widen

A new study suggests that the coronavirus will undo months of academic gains, leaving many students behind. The study authors project that students will start the new school year with an average of 66 percent of the learning gains in reading and 44 percent of the learning gains in math, relative to the gains for a typical school year. But the situation is worse on the reading front, as the researchers also predict that the top third of students will make gains, possibly because they’re likely to continue reading with their families while schools are closed, thus widening the achievement gap.

To make matters worse, “few school systems provide plans to support students who need accommodations or other special populations,” the researchers point out in the study, potentially impacting students with special needs and English language learners.

Of course, the idea that over the summer students forget some of what they learned in school isn’t new. But there’s a big difference between summer learning loss and pandemic-related learning loss: During the summer, formal schooling stops, and learning loss happens at roughly the same rate for all students, the researchers point out. But instruction has been uneven during the pandemic, as some students have been able to participate fully in online learning while others have faced obstacles—such as lack of internet access—that have hindered their progress.

In the study, researchers analyzed a national sample of 5 million students in grades 3–8 who took the MAP Growth test, a tool schools use to assess students’ reading and math growth throughout the school year. The researchers compared typical growth in a standard-length school year to projections based on students being out of school from mid-March on. To make those projections, they looked at research on the summer slide, weather- and disaster-related closures (such as New Orleans after Hurricane Katrina), and absenteeism.

The researchers predict that, on average, students will experience substantial drops in reading and math, losing roughly three months’ worth of gains in reading and five months’ worth of gains in math. For Megan Kuhfeld, the lead author of the study, the biggest takeaway isn’t that learning loss will happen—that’s a given by this point—but that students will come back to school having declined at vastly different rates.

“We might be facing unprecedented levels of variability come fall,” Kuhfeld told me. “Especially in school districts that serve families with lots of different needs and resources. Instead of having students reading at a grade level above or below in their classroom, teachers might have kids who slipped back a lot versus kids who have moved forward.” 

Disproportionate Impact on Students Living in Poverty and Students of Color

Horace Mann once referred to schools as the “great equalizers,” yet the pandemic threatens to expose the underlying inequities of remote learning. According to a 2015 Pew Research Center analysis , 17 percent of teenagers have difficulty completing homework assignments because they do not have reliable access to a computer or internet connection. For Black students, the number spikes to 25 percent.

“There are many reasons to believe the Covid-19 impacts might be larger for children in poverty and children of color,” Kuhfeld wrote in the study. Their families suffer higher rates of infection, and the economic burden disproportionately falls on Black and Hispanic parents, who are less likely to be able to work from home during the pandemic.

Although children are less likely to become infected with Covid-19, the adult mortality rates, coupled with the devastating economic consequences of the pandemic, will likely have an indelible impact on their well-being.

Impacts on Students’ Mental Health

That impact on well-being may be magnified by another effect of school closures: Schools are “the de facto mental health system for many children and adolescents,” providing mental health services to 57 percent of adolescents who need care, according to the authors of a recent study published in JAMA Pediatrics . School closures may be especially disruptive for children from lower-income families, who are disproportionately likely to receive mental health services exclusively from schools.

“The Covid-19 pandemic may worsen existing mental health problems and lead to more cases among children and adolescents because of the unique combination of the public health crisis, social isolation, and economic recession,” write the authors of that study.

A major concern the researchers point to: Since most mental health disorders begin in childhood, it is essential that any mental health issues be identified early and treated. Left untreated, they can lead to serious health and emotional problems. In the short term, video conferencing may be an effective way to deliver mental health services to children.

Mental health and academic achievement are linked, research shows. Chronic stress changes the chemical and physical structure of the brain, impairing cognitive skills like attention, concentration, memory, and creativity. “You see deficits in your ability to regulate emotions in adaptive ways as a result of stress,” said Cara Wellman, a professor of neuroscience and psychology at Indiana University in a 2014 interview . In her research, Wellman discovered that chronic stress causes the connections between brain cells to shrink in mice, leading to cognitive deficiencies in the prefrontal cortex. 

While trauma-informed practices were widely used before the pandemic, they’re likely to be even more integral as students experience economic hardships and grieve the loss of family and friends. Teachers can look to schools like Fall-Hamilton Elementary in Nashville, Tennessee, as a model for trauma-informed practices . 

3 Ways Teachers Can Prepare

When schools reopen, many students may be behind, compared to a typical school year, so teachers will need to be very methodical about checking in on their students—not just academically but also emotionally. Some may feel prepared to tackle the new school year head-on, but others will still be recovering from the pandemic and may still be reeling from trauma, grief, and anxiety. 

Here are a few strategies teachers can prioritize when the new school year begins:

• Focus on relationships first. Fear and anxiety about the pandemic—coupled with uncertainty about the future—can be disruptive to a student’s ability to come to school ready to learn. Teachers can act as a powerful buffer against the adverse effects of trauma by helping to establish a safe and supportive environment for learning. From morning meetings to regular check-ins with students, strategies that center around relationship-building will be needed in the fall.
• Strengthen diagnostic testing. Educators should prepare for a greater range of variability in student learning than they would expect in a typical school year. Low-stakes assessments such as exit tickets and quizzes can help teachers gauge how much extra support students will need, how much time should be spent reviewing last year’s material, and what new topics can be covered.
• Differentiate instruction—particularly for vulnerable students. For the vast majority of schools, the abrupt transition to online learning left little time to plan a strategy that could adequately meet every student’s needs—in a recent survey by the Education Trust, only 24 percent of parents said that their child’s school was providing materials and other resources to support students with disabilities, and a quarter of non-English-speaking students were unable to obtain materials in their own language. Teachers can work to ensure that the students on the margins get the support they need by taking stock of students’ knowledge and skills, and differentiating instruction by giving them choices, connecting the curriculum to their interests, and providing them multiple opportunities to demonstrate their learning.

The pandemic has had devastating impacts on learning. What will it take to help students catch up?

Subscribe to the brown center on education policy newsletter, megan kuhfeld , megan kuhfeld senior research scientist - nwea jim soland , jim soland assistant professor, school of education and human development - university of virginia, affiliated research fellow - nwea karyn lewis , and karyn lewis director, center for school and student progress - nwea emily morton emily morton research scientist - nwea.

March 3, 2022

As we reach the two-year mark of the initial wave of pandemic-induced school shutdowns, academic normalcy remains out of reach for many students, educators, and parents. In addition to surging COVID-19 cases at the end of 2021, schools have faced severe staff shortages , high rates of absenteeism and quarantines , and rolling school closures . Furthermore, students and educators continue to struggle with mental health challenges , higher rates of violence and misbehavior , and concerns about lost instructional time .

As we outline in our new research study released in January, the cumulative impact of the COVID-19 pandemic on students’ academic achievement has been large. We tracked changes in math and reading test scores across the first two years of the pandemic using data from 5.4 million U.S. students in grades 3-8. We focused on test scores from immediately before the pandemic (fall 2019), following the initial onset (fall 2020), and more than one year into pandemic disruptions (fall 2021).

Average fall 2021 math test scores in grades 3-8 were 0.20-0.27 standard deviations (SDs) lower relative to same-grade peers in fall 2019, while reading test scores were 0.09-0.18 SDs lower. This is a sizable drop. For context, the math drops are significantly larger than estimated impacts from other large-scale school disruptions, such as after Hurricane Katrina—math scores dropped 0.17 SDs in one year for New Orleans evacuees .

Even more concerning, test-score gaps between students in low-poverty and high-poverty elementary schools grew by approximately 20% in math (corresponding to 0.20 SDs) and 15% in reading (0.13 SDs), primarily during the 2020-21 school year. Further, achievement tended to drop more between fall 2020 and 2021 than between fall 2019 and 2020 (both overall and differentially by school poverty), indicating that disruptions to learning have continued to negatively impact students well past the initial hits following the spring 2020 school closures.

These numbers are alarming and potentially demoralizing, especially given the heroic efforts of students to learn and educators to teach in incredibly trying times. From our perspective, these test-score drops in no way indicate that these students represent a “ lost generation ” or that we should give up hope. Most of us have never lived through a pandemic, and there is so much we don’t know about students’ capacity for resiliency in these circumstances and what a timeline for recovery will look like. Nor are we suggesting that teachers are somehow at fault given the achievement drops that occurred between 2020 and 2021; rather, educators had difficult jobs before the pandemic, and now are contending with huge new challenges, many outside their control.

Clearly, however, there’s work to do. School districts and states are currently making important decisions about which interventions and strategies to implement to mitigate the learning declines during the last two years. Elementary and Secondary School Emergency Relief (ESSER) investments from the American Rescue Plan provided nearly $200 billion to public schools to spend on COVID-19-related needs. Of that sum, $22 billion is dedicated specifically to addressing learning loss using “evidence-based interventions” focused on the “ disproportionate impact of COVID-19 on underrepresented student subgroups. ” Reviews of district and state spending plans (see Future Ed , EduRecoveryHub , and RAND’s American School District Panel for more details) indicate that districts are spending their ESSER dollars designated for academic recovery on a wide variety of strategies, with summer learning, tutoring, after-school programs, and extended school-day and school-year initiatives rising to the top.

Comparing the negative impacts from learning disruptions to the positive impacts from interventions

To help contextualize the magnitude of the impacts of COVID-19, we situate test-score drops during the pandemic relative to the test-score gains associated with common interventions being employed by districts as part of pandemic recovery efforts. If we assume that such interventions will continue to be as successful in a COVID-19 school environment, can we expect that these strategies will be effective enough to help students catch up? To answer this question, we draw from recent reviews of research on high-dosage tutoring , summer learning programs , reductions in class size , and extending the school day (specifically for literacy instruction) . We report effect sizes for each intervention specific to a grade span and subject wherever possible (e.g., tutoring has been found to have larger effects in elementary math than in reading).

Figure 1 shows the standardized drops in math test scores between students testing in fall 2019 and fall 2021 (separately by elementary and middle school grades) relative to the average effect size of various educational interventions. The average effect size for math tutoring matches or exceeds the average COVID-19 score drop in math. Research on tutoring indicates that it often works best in younger grades, and when provided by a teacher rather than, say, a parent. Further, some of the tutoring programs that produce the biggest effects can be quite intensive (and likely expensive), including having full-time tutors supporting all students (not just those needing remediation) in one-on-one settings during the school day. Meanwhile, the average effect of reducing class size is negative but not significant, with high variability in the impact across different studies. Summer programs in math have been found to be effective (average effect size of .10 SDs), though these programs in isolation likely would not eliminate the COVID-19 test-score drops.

Figure 1: Math COVID-19 test-score drops compared to the effect sizes of various educational interventions

Source: COVID-19 score drops are pulled from Kuhfeld et al. (2022) Table 5; reduction-in-class-size results are from pg. 10 of Figles et al. (2018) Table 2; summer program results are pulled from Lynch et al (2021) Table 2; and tutoring estimates are pulled from Nictow et al (2020) Table 3B. Ninety-five percent confidence intervals are shown with vertical lines on each bar.

Notes: Kuhfeld et al. and Nictow et al. reported effect sizes separately by grade span; Figles et al. and Lynch et al. report an overall effect size across elementary and middle grades. We were unable to find a rigorous study that reported effect sizes for extending the school day/year on math performance. Nictow et al. and Kraft & Falken (2021) also note large variations in tutoring effects depending on the type of tutor, with larger effects for teacher and paraprofessional tutoring programs than for nonprofessional and parent tutoring. Class-size reductions included in the Figles meta-analysis ranged from a minimum of one to minimum of eight students per class.

Figure 2 displays a similar comparison using effect sizes from reading interventions. The average effect of tutoring programs on reading achievement is larger than the effects found for the other interventions, though summer reading programs and class size reduction both produced average effect sizes in the ballpark of the COVID-19 reading score drops.

Figure 2: Reading COVID-19 test-score drops compared to the effect sizes of various educational interventions

Source: COVID-19 score drops are pulled from Kuhfeld et al. (2022) Table 5; extended-school-day results are from Figlio et al. (2018) Table 2; reduction-in-class-size results are from pg. 10 of Figles et al. (2018) ; summer program results are pulled from Kim & Quinn (2013) Table 3; and tutoring estimates are pulled from Nictow et al (2020) Table 3B. Ninety-five percent confidence intervals are shown with vertical lines on each bar.

Notes: While Kuhfeld et al. and Nictow et al. reported effect sizes separately by grade span, Figlio et al. and Kim & Quinn report an overall effect size across elementary and middle grades. Class-size reductions included in the Figles meta-analysis ranged from a minimum of one to minimum of eight students per class.

There are some limitations of drawing on research conducted prior to the pandemic to understand our ability to address the COVID-19 test-score drops. First, these studies were conducted under conditions that are very different from what schools currently face, and it is an open question whether the effectiveness of these interventions during the pandemic will be as consistent as they were before the pandemic. Second, we have little evidence and guidance about the efficacy of these interventions at the unprecedented scale that they are now being considered. For example, many school districts are expanding summer learning programs, but school districts have struggled to find staff interested in teaching summer school to meet the increased demand. Finally, given the widening test-score gaps between low- and high-poverty schools, it’s uncertain whether these interventions can actually combat the range of new challenges educators are facing in order to narrow these gaps. That is, students could catch up overall, yet the pandemic might still have lasting, negative effects on educational equality in this country.

Given that the current initiatives are unlikely to be implemented consistently across (and sometimes within) districts, timely feedback on the effects of initiatives and any needed adjustments will be crucial to districts’ success. The Road to COVID Recovery project and the National Student Support Accelerator are two such large-scale evaluation studies that aim to produce this type of evidence while providing resources for districts to track and evaluate their own programming. Additionally, a growing number of resources have been produced with recommendations on how to best implement recovery programs, including scaling up tutoring , summer learning programs , and expanded learning time .

Ultimately, there is much work to be done, and the challenges for students, educators, and parents are considerable. But this may be a moment when decades of educational reform, intervention, and research pay off. Relying on what we have learned could show the way forward.

Related Content

Megan Kuhfeld, Jim Soland, Beth Tarasawa, Angela Johnson, Erik Ruzek, Karyn Lewis

December 3, 2020

Lindsay Dworkin, Karyn Lewis

October 13, 2021

Early Childhood Education Education Access & Equity Education Policy K-12 Education

Governance Studies

U.S. States and Territories

Brown Center on Education Policy

Magdalena Rodríguez Romero

September 10, 2024

Tom Swiderski, Sarah Crittenden Fuller, Kevin C. Bastian

September 9, 2024

Julien Lafortune, Barbara Biasi, David Schönholzer

September 6, 2024

• Utility Menu

• Get Involved
• News & Events

qualtrics survey

New research finds that pandemic learning loss impacted whole communities, regardless of student race or income.

Analysis of prior decade shows that learning loss will become permanent if schools and parents do not expand learning time this summer and next year

(May 11, 2023) – Today, The Education Recovery Scorecard , a collaboration with researchers at the Center for Education Policy Research at Harvard University (CEPR) and Stanford University’s Educational Opportunity Project, released 12 new state reports and a research brief to provide the most comprehensive picture yet of how the pandemic affected student learning. Building on their previous work, their findings reveal how school closures and local conditions exacerbated inequality between communities — and how little time school leaders have to help students catch up.

The research team reviewed data from 8,000 communities in 40 states and Washington, D.C., including 2022 NAEP scores and Spring 2022 assessments, COVID death rates, voting rates and trust in government, patterns of social activity and survey data from Facebook/Meta on family activities and mental health during the pandemic.

They found that where children lived during the pandemic mattered more to their academic progress than their family background, income, or internet speed.  Moreover, after studying instances where test scores rose or fell in the decade before the pandemic, the researchers found that the impacts lingered for years. 

“Children have resumed learning, but largely at the same pace as before the pandemic. There’s no hurrying up teaching fractions or the Pythagorean theorem,” said CEPR faculty director Thomas Kane. “The hardest hit communities—like Richmond, VA, St. Louis, MO, and New Haven, CT, where students fell behind by more than 1.5 years in math—would have to teach 150 percent of a typical year’s worth of material for three years in a row—just to catch up. That is simply not going to happen without a major increase in instructional time.  Any district that lost more than a year of learning should be required to revisit their recovery plans and add instructional time—summer school, extended school year, tutoring, etc.—so that students are made whole. ”

“It’s not readily visible to parents when their children have fallen behind earlier cohorts, but the data from 7,800 school districts show clearly that this is the case,” said Sean Reardon, Professor of Poverty and Inequality, Stanford Graduate School of Education. “The educational impacts of the pandemic were not only historically large, but were disproportionately visited on communities with many low-income and minority students. Our research shows that schools were far from the only cause of decreased learning—the pandemic affected children through many ways – but they are the institution best suited to remedy the unequal impacts of the pandemic.”

The new research includes:

• A research brief that offers insights into why students in some communities fared worse than others.
• An update to the Education Recovery Scorecard, including data from 12 additional states whose 2022 scores were not available in October. The project now includes a district-level view of the pandemic’s effects in 40 states (plus DC).
• A new interactive map  that highlights examples of inequity between neighboring school districts.

Among the key findings:

• Within the typical school district, the declines in test scores were similar for all groups of students, rich and poor, white, Black, Hispanic. And the extent to which schools were closed appears to have had the same effect on all students in a community, regardless of income or race.
• Test scores declined more in places where the COVID death rate was higher, in communities where adults reported feeling more depression and anxiety during the pandemic, and where daily routines of families were most significantly restricted. This is true even in places where schools closed only very briefly at the start of the pandemic.
• Test score declines were smaller in communities with high voting rates and high Census response rates—indicators of what sociologists call “institutional trust.” Moreover, remote learning was less harmful in such places. Living in a community where more people trusted the government appears to have been an asset to children during the pandemic.
• The average U.S. public school student in grades 3-8 lost the equivalent of a half year of learning in math and a quarter of a year in reading.

The researchers also looked at data from the decade prior to the pandemic to see how students bounced back after significant learning loss due to disruption in their schooling. The evidence shows that schools do not naturally bounce back: Affected students recovered 20-30% of the lost ground in the first year, but then made no further recovery in the subsequent 3-4 years.  

“Schools were not the sole cause of achievement losses,” Kane said. “Nor will they be the sole solution. As enticing as it might be to get back to normal, doing so will just leave the devastating increase in inequality caused by the pandemic in place.   We must create learning opportunities for students outside of the normal school calendar, by adding academic content to summer camps and after-school programs and adding an optional 13th year of schooling.”

The Education Recovery Scorecard is supported by funds from Citadel founder and CEO Kenneth C. Griffin , Carnegie Corporation of New York, and the Walton Family Foundation.

About the Center for Education Policy Research at Harvard University The Center for Education Policy Research at Harvard University, based at the Harvard Graduate School of Education, seeks to transform education through quality research and evidence. CEPR and its partners believe all students will learn and thrive when education leaders make decisions using facts and findings, rather than untested assumptions. Learn more at cepr.harvard.edu.

Contact: Jeff Frantz, [email protected] , 614-204-7438 (mobile)

News by Focus Area

• COVID-19 Impact (72)
• Postsecondary Access & Success (31)
• School Improvement & Redesign (65)
• Teacher Effectiveness (57)

News by Type

• Newsletters (5)
• Press Releases (43)
• Announcements (6)
• In the News (228)

News by Project

News by year.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Int J Environ Res Public Health

Impact of COVID-19 on University Students: An Analysis of Its Influence on Psychological and Academic Factors †

Gerardo gómez-garcía.

1 Department of Didactics and School Organisation, Faculty of Education Science, Campus Universitario de Cartuja, University of Granada, 18071 Granada, Spain

Magdalena Ramos-Navas-Parejo

2 Department of Didactics and School Organization, Faculty of Education and Sport Sciences, Campus Universitario de Melilla, University of Granada, 52071 Melilla, Spain

Juan-Carlos de la Cruz-Campos

Carmen rodríguez-jiménez, associated data.

The datasets generated and analyzed during the current study are available from G.G.-G. on reasonable request.

The irruption of COVID-19 has had different consequences on mental health in the youth population. Specifically, the sector made up of university students has suffered an abrupt change of teaching modality because of the pandemic. As such, this paper aims to analyze the impact that COVID-19 has had on different personal factors of students: (i) satisfaction with life; (ii) lived uncertainty; (iii) depression, anxiety, and stress, as well as factors related to academic development; (iv) motivation and the creation of teaching and learning strategies during this period; and (v) the perception of the degree of adaptability to the new scenario brought about by the university system. For this purpose, a cross-sectional quantitative design was advocated through the elaboration of an SEM model, which included 1873 university students from Andalusian Universities (Spain). The results reflected the strong negative impact that the pandemic had, especially on the levels of life satisfaction and the indices of depression, anxiety, and stress of the students. Likewise, the findings reflected the relevance of the correct adaptability on the part of the university to these new circumstances. It is necessary for university institutions to focus their efforts on quality attention to students, in order to establish fluid communication with them and to adapt to their academic and personal needs.

1. Introduction

The World Health Organization declared in March 2020 that COVID-19 was a pandemic that affected all areas of society worldwide without exception. So much so that even today, different countries and societies are still fighting against it and establishing different measures in many areas to mitigate its effects and consequences. The rapid expansion of COVID-19 and all of the tremendously negative effects it has had on the health of the world’s population and on the economy at both the macro and micro levels has generated great levels of insecurity and stress in a large part of the population.

The pandemic brought with it major restrictions that persist to this day. These restrictions on mobility, the closure of non-essential businesses, and the limitation of social relationships have led to mental health consequences such as those noted above. In addition, unemployment rates have increased since the onset of the pandemic [ 1 ]. Job insecurity is an experience that has been associated with distress and negative feelings [ 2 , 3 ]. Throughout history, during pandemics or major crises, it has been shown that it is at these times that psychological problems in the population increase, as well as levels of anxiety, depression, and stress [ 4 , 5 ].

The extent of these problems is not yet fully known [ 6 ]. It is at present that studies are beginning to be carried out on these consequences in certain sectors of the population such as healthcare workers, analyzing the impacts of COVID-19 on their mental health—including insomnia, anxiety, and depression—and what other risk factors increase the probability of suffering from these diseases [ 7 , 8 , 9 ], or analyzing COVID-19 patients who also suffer from these mental disorders depending on certain demographic factors, such as older age, lower educational level or less physical activity [ 10 ].

Some population groups are more vulnerable than others to the psychosocial effects of pandemics [ 11 ]. Existing research focuses on the mental health problems of frontline medical personnel. The samples analyzed show that within this population group, it is women, nurses and those health professionals who diagnose, treat or provide nursing care to COVID patients who show more symptoms of distress, depression, stress or insomnia [ 12 , 13 ].

On the other hand, existing research also focuses on how individuals have lived with uncertainty throughout this period of the pandemic, and even today, they are still in this situation. Both the media and social networks have often contributed to this uncertainty due to the amount of information and data provided, which is an element that clearly influences people’s mental health [ 14 ]. The media can also provoke certain doubts among the population, along with changes in public attitudes and behavior. In contrast, sharing information in real time, with official data and analysis, will improve the ability of public health agencies and relevant stakeholders to respond to and understand the social dynamics of the rapidly increasing and changing dissemination of information and misinformation regarding the coronavirus and the outbreak and control measures. It will also reduce community panic and futile measures disproportionate to the cause [ 15 ].

Because of these processes, there is a more-than-palpable psychological burden on the population. A recently published study investigated the impact of the COVID-19 pandemic on the mental health burden of the Chinese public [ 16 ]. This study shows a high prevalence of generalized anxiety, depressive symptoms, and poor sleep quality due to stress during the COVID-19 pandemic. Thus, it is easy to conclude that this turbulent time in which we are immersed affects everyone’s mental health in some way or another, as all aspects of what was meant by everyday life have changed in some way or another.

2. Impact of COVID-19 on the Educational Scenario

The irruption of COVID-19 provoked, among many other things, the total closure of educational centers at all levels, meaning that teaching went from being face-to-face to online. The challenges that this has caused for students, having to deal with new, strange, and sometimes complicated situations, are remarkable for the consequences that have resulted from them.

Confinement, as an urgent measure to contain the virus, took place in March 2020, and involved an accelerated deployment of solutions for education to try to ensure academic continuity [ 17 , 18 ], along with a psychological impact for students and teachers [ 19 ].

Schools and universities were unprepared to deal with this unprecedented situation, which affected 1.57 billion students in 191 countries [ 20 ]. Therefore, they were faced with the challenge of dealing with the reorganization of their activities with immediacy and creativity, in order to avoid a negative outcome for students’ education [ 21 ]. In addition, they had a series of obstacles, such as low connectivity, a lack of online content, teachers who did not have the appropriate training for this type of distance learning led by ICT, and lack of technological resources and connectivity on the part of the students, among others [ 22 ]. Educational inequalities were particularly affected, as the exclusion of the most disadvantaged students increased, making it impossible for them to continue their education.

The compulsory and massive use of all kinds of ICT platforms and resources to guarantee the continuity of learning has been a great experiment in the implementation of educational technology. However, by being carried out in such an abrupt manner, these have generated unease among educational agents [ 23 ]. According to [ 24 ], university students were greatly harmed by the change from face-to-face to virtual classes, as communication with faculty was insufficient; they encountered connectivity problems, and were overloaded with homework and demotivated, which increased the level of anxiety and stress [ 25 , 26 , 27 , 28 ]. Teachers, took the situation as an opportunity to learn other didactic methodologies and, on the other hand, felt the stress of uncertainty and the workload. Resistance to change and the lack of digital competence of teachers have been the major impediments to distance education. Higher Education students feel that universities have not adapted to e-learning and assessments [ 29 ]. Because the measures adopted have not been sufficient, this has had an impact on a low level of learning and academic performance, affecting the average grades and jeopardizing students’ future employment.

Students have seen their motivation for learning diminished due to the fear of illness, the deprivation of liberty, difficulties in accessing the internet in some cases, and economic and family factors, etc. However, in most cases, they managed to achieve their academic goals [ 30 , 31 ]. Ref. [ 32 ] states that the effects of COVID-19 on university students have generated the following main difficulties: social isolation, anxiety, depression related to the situation generated by the pandemic, difficulty in adapting to ICT, maintaining a schedule and scenario to work continuously, economic aspects, accessibility to technological resources, and the poor planning of teachers [ 33 , 34 , 35 , 36 ]. A study carried out by [ 37 ] emphasized these negative aspects that students have experienced with the arrival of the pandemic, and that have negatively affected their life satisfaction in all of its dimensions, both personal and social. They conclude that for female university students, the emotional impact has been more acute; they have developed higher levels of fear and anxiety. These are aspects directly related to the difficulty of making decisions and looking to the future with optimism, generating situations that increase uncertainty [ 38 ].

After the cessation of the state of alarm, the result has been an increase in cases of anxiety and depression among university students due to the emotional changes produced by the disruption of daily routines and the reduction of physical contact [ 39 ]. Ref. [ 40 ] also reiterates that some of the negative consequences on students’ mental health are increased levels of anxiety, worry and fear, often leading to depression.

Students have generally taken the transition to virtuality negatively, which has led to behavioural and emotional changes that have affected wellbeing and academic performance [ 41 ]. Educational spaces have highlighted the satisfaction of learning needs, leading to the possibility of depressive symptoms [ 42 ].

Therefore, in terms of mental health, university students have been considered a vulnerable population, where resilience has played a fundamental role in maintaining emotional stability. Refs. [ 25 , 43 ] state that universities have the power to prevent and mitigate these negative effects on the mental health of their students.

According to [ 42 ], through self-determination theory, the causes influencing students’ motivation during this emergency situation have been related to a too-rapid transition between traditional face-to-face learning and digital learning. This theory details how socio-contextual factors affect student motivation through the satisfaction of their basic psychological needs: autonomy, competence, and affinity. When these three needs are met, students’ motivation to learn and engagement increase [ 44 ]. Autonomy refers to the self-regulation of particular actions and commitments. Competence is understood as the ability to effectively perform the given tasks. Moreover, affinity has to do with connection with others. Virtual or distance learning can satisfy the needs of autonomy and competence, but it does not attend to the need to relate, or to create this affinity with the rest of the educational agents, students, and teachers. During the pandemic, many students have felt isolated and disconnected [ 45 ].

In higher education, this situation caused by COVID-19 has increased anxiety levels due to the uncertainty generated in the labour market, especially in final year students [ 46 ], and has worsened the economic crisis and the income level of families [ 47 ]. Living in urban areas, having financial stability at home, living with family and having social support have been found to be protective factors against anxiety [ 48 ].

Women, on the other hand, have shown higher levels of anxiety than men [ 49 ]; however, men have stood out as suffering more depression than women [ 50 ]. In terms of age, higher measures of stress, anxiety and depression are found in younger students than in older ones [ 51 ].

3. Current Study and Research Objectives

This study also focuses on the configuration of a model ( Figure 1 ) that investigates the relationship between the fear of COVID-19, life satisfaction, uncertainty, depression, anxiety and stress, motivation towards the learning process, and acceptance to the new technological scenario. Based on this idea, the following hypotheses are put forward:

Theoretical model to determine the level of dependence between latent variables. Note: Own production.

Fear of COVID-19 has a negative influence on levels of life satisfaction due to the possible influence on the perception of quality of life and the need to include changes in participants’ lives.

Fear of COVID-19 has a positive influence on uncertainty indices due to the possible influence of COVID-19 on participants’ insecurity.

Fear of COVID-19 has a positive influence on depression, anxiety and stress due to the possible influence on mental health states .

Fear of COVID-19 has a negative influence on motivation towards teaching–learning processes due to the possible decrease in academic performance.

Fear of COVID-19 has a negative influence on perceptions of the university’s adaptability to the new scenario due to participants’ facing unfamiliar academic scenarios during the pandemic.

Life satisfaction indices are positively associated with the adaptive conditions of the university system, as they allow for the successful completion of academic processes.

Life satisfaction scores are negatively related to depression, anxiety and stress scores because of their possible influence on participants’ health status.

Life satisfaction scores are negatively related to uncertainty because of the possible influence on the prospects of future academic grades.

Life satisfaction is negatively related to the motivation towards the new teaching–learning process because of the possible influence of the teaching–learning methods used during the pandemic.

Indices of experienced uncertainty are associated with levels of depression and anxiety and stress because of the possible influence of uncertainty on students’ mental health.

The uncertainty experienced is negatively related to the indexes of motivation towards the teaching–learning processes because of its possible relationship with the teaching–learning methods used during the pandemic.

The uncertainty indexes are inversely related to the perception of adaptability to the new training scenario proposed by the university due to its possible influence of the teaching–learning methods used during the pandemic.

Levels of depression, anxiety and experienced stress are negatively linked to motivation and the search for new learning strategies due to the possible influence of the students’ mental states on the teaching methods used during the pandemic.

The levels of depression, anxiety and stress experienced are negatively associated with the level of adaptability to the teaching promoted by the university because of the possible influence of students’ mental health status on teaching processes.

Indices of motivation and the search for new learning strategies are negatively related to the perception of adaptability to the new training scenario proposed by the university due to the possible influence that the pandemic exerted on motivation and attachment to teaching techniques during COVID-19.

The use of a quantitative methodology was advocated to answer the research questions posed, and to satisfy the initially projected objectives [ 52 ].

4.1. Sample and Procedure

A cross-sectional study design was advocated by means of a self-administered survey in a sample of Spanish university students. Specifically, the study used a sample of 1873 students from the autonomous community of Andalusia, located in the southern part of Spain ( n = 1873). The survey was disseminated via Google Forms through different official university channels of each of the Andalusian universities until a significant sample size was reached. The sampling criteria consisted of a convenience sample, which was sent to students enrolled in the eight universities of the single Andalusian district.

Likewise, the study participants responded to a series of questions referring to different sociodemographic variables, as well as to different standardised scales that determine the fear of COVID-19, current life satisfaction, depression, self-perceived stress and anxiety, uncertainty, and current academic motivation. Prior to completion, all of the participants gave informed consent. Likewise, all of the subjects were provided with information about the purpose of the research and the anonymous treatment of the data.

Table 1 presents the sociodemographic data of the participants. The sample consisted of 457 males and 1415 females, ranging in age from 17 to 59 (M = 22.42; SD = 4.451). This is a group of students in which most of their parents were working before the pandemic, and the effects of the pandemic caused many of them to lose their jobs. Likewise, a large percentage of the parents were on temporary lay-offs (ERTE, Expediente de Regulación Temporal de Empleo; Temporary Employment Adjustment Plan) during the period of the greatest incidence of the pandemic in the country. Regarding housing conditions while studying, the vast majority of students were living in a rented flat (58.8%), for which they had to terminate their contract due to the pandemic. As a result, most of them (80.9%) had to return to their family home ( Table 2 ).

Gender and age.

Note: Own production.

Descriptive statistics.

The study was applied at the end of June 2020. The State of Alarm protocol in Spain began on 14 March 2020, and from that date until 9 May there was house confinement in Andalusia. From this date, the de-escalation process took place in the country. In addition, this was the time when the final evaluation period of the university course was taking place; as such, we considered it appropriate to carry out the study in this period, as it would be a point of reflection for students on this atypical academic year in which they could thoroughly assess the course, and the possible impacts caused.

The study was conducted according to the guidelines of the Declaration of Helsinki, and was approved by the Ethics Committee of the University of Granada (REF:0706/2020).

4.2. Measures

The scales are standardized, and can be accessed through the citations provided in the description of each of the constructs.

4.2.1. COVID-19 Fear Scale

The COVID-19 Fear Scale was developed by [ 53 ]. It is composed of 7 items that follow the 5-point Likert format (1 = strongly disagree; 5 = strongly agree). It is responsible for measuring the indices of fear and anxiety produced in people because of COVID-19. The Cronbach’s alpha coefficient obtained in this study was 0.929.

4.2.2. The Life Satisfaction Scale

The life satisfaction scale was developed by [ 54 ]. The scale has five items in the form of a 7-point Likert scale (1 = Not at all agree; 7 = Strongly agree). The scale has only one dimension. It is intended to analyse the students’ levels of life satisfaction during this complex period. The Cronbach’s alpha coefficient obtained in this study was 0.936.

4.2.3. Intolerance of Uncertainly Scale (IUS-12)

The Intolerance of Uncertainly Scale is an abbreviated version of the IUS [ 55 ] developed by [ 56 ], and is based on 12 items with a 5-point Likert scale (1 = not at all; 5 = very much). It measures intolerance to uncertainty as the tendency to react negatively on an emotional, cognitive, and behavioural level to uncertain situations and events. It is configured around two dimensions: prospective anxiety, which measures fear and anxiety related to the future, and inhibitory anxiety, which measures the inhibitory action or experience of uncertainty. The Cronbach’s alpha coefficient obtained in this study was 0.934.

4.2.4. Depression Anxiety Stress Scale-21 (DASS-21)

The DASS-21 scale, developed by Lovibond and recommended by the Australian Psychological Association, consists of three self-report scales designed to measure the emotional states of depression, anxiety and stress [ 57 ]. Each of the three scales contains 7 items, divided into subscales of similar content. The scale is a 4-point Likert scale (0 = has not happened to me; 3 = has happened to me a lot, or most of the time). This instrument is used to determine the level of specified negative emotional states. In the current research, the use of its validated version in the Spanish language was advocated [ 58 ]. The purpose of its application is to indicate the psychological state of university students during the pandemic. The Cronbach’s alpha coefficient obtained in this study was 0.902.

4.2.5. Motivated Strategies for Learning Questionnaire (MLSQ-SF)

The Motivational Strategies for Learning Questionnaire–Short Form (MSLQ-SF) was developed by [ 59 ]. It consists of 40 questions grouped around three dimensions: (i) Motivation scale, items linked to task evaluation and task anxiety; (ii) Learning strategies, made up of developmental strategies, critical thinking, and self-regulation of learning; and (iii) Resource management strategies, structured according to time and study habits, self-regulatory effort, and intrinsic goal-setting orientation. The scale is Likert type 5 (1 = never; 5 = always). This scale was chosen to find out the levels of motivation, as well as the students’ strategies to promote learning in the new scenario during the home confinement and the academic course that took place virtually. The Cronbach’s alpha coefficient obtained in this study was 0.948.

4.2.6. Unified Theory of Acceptance and Use of Technology (UTAUT)—Facilitating Conditions (FC)

Facilitating conditions are defined as the “degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system” [ 60 ]. This construct is considered to be one of the strongest predictors in the behavioural intention to use a technology [ 61 ], and presents a significant influence [ 62 ]. In the educational context, facilitating conditions refers to human, organizational, and technical support for using technology [ 63 ]. This construct is measured through a 7-point Likert scale. This dimension was added with the aim of analysing the degree of adaptation that students perceive that universities have had when adapting to the virtual mode of teaching, and what their degree of acceptance is. The Cronbach’s alpha coefficient obtained in this study was 0.907.

4.2.7. Statistical Analyses

Firstly, descriptive statistics were calculated to evaluate the self-perception of the students in terms of their expressed fear of COVID-19, levels of depression, satisfaction with life, and uncertainty experienced so far.

Finally, a structural equation model (SEM) was set up to establish the correlation coefficients between the measured constructs.

The data were analysed using the statistical programs IBM SPSS version 25 and IBM SPSS Amos, version 24.

The descriptive statistics shown in Table 2 reflect indices of fear of COVID close to the average, as well as levels of life satisfaction in students which were slightly above the standard. With respect to the perceived level of uncertainty, this is slightly above average, along with the levels of motivation and learning strategies. The high values for the depression, anxiety, and stress constructs, as well as the facilitating conditions, stand out.

On the other hand, the level of variability among the responses is high, as indicated by the standard deviation coefficients, such that it is likely that there are outliers in the data distribution. This statement is confirmed when visualizing the coefficients of asymmetry and kurtosis, which are mostly negative, which determines that most of the participants’ answers are below the arithmetic mean indicated.

Subsequently, structural equation modelling (SEM) was used to check whether the hypothesized model ( Figure 1 ) coincided with the data collected. The correlations between the different constructs are presented in Table 3 , with all of them being statistically significant ( p < 0.001). The coefficients obtained highlighted moderate–strong relationships between the constructs. In the first place, the strong positive relationships between SAT and FC, COVID and UNC, and COVID and DAS exceed more than half of the dependence index. On the other hand, negative correlation relationships were also elucidated, such as those found between COVID and FC, COVID and SAT, SAT and UNC, and SAT and DAS, for which the coefficients indicate a medium non-linear dependence relationship.

Covariance relationships between the constructs.

Note: Own production. *** denotes significance at p < 0.001.

After this, the SEM model was set up. In it, relationships of influence between the different latent variables were observed. Associations between variables such as FC and SAT, DAS, and UNC, and COVID and UNC stand out for the strong linearity links they present. In contrast, non-linear relationships were found, as was the case of COVID and FC, COVID and SAT, and SAT and UNC. Regarding the goodness-of-fit indices, the results showed a relatively good fit between our model and the data (χ 2 /df = 1.761, p = 0.000; RMSEA = 0.0079; NFI = 0.959 CFI = 0.976; GFI = 0.967; AGFI = 0.951). If we look at the configured model ( Figure 2 ), relationships were observed. All of the relationships obtained were statistically significant.

Estimations of the structural equation model. The relations were significant at p < 0.001. Note: Own production.

6. Discussion

The evidence presented in this paper reflects the clear impact that COVID-19 has had on the participating university students, a sector of the population that has been greatly affected in terms of mental health by the pandemic [ 51 ]. In this study, we examined the impact that this has caused (COVID-19) in different personal factors: life satisfaction (SAT), depression, anxiety, stress (DAS), and uncertainty (UNC); as well as factors with respect to their training: the motivation and configuration of teaching–learning strategies (MOT), and perceptions regarding the degree of adaptability of the university to the new scenario that has occurred (FC). Likewise, a structural model was presented that elucidated the unobserved interactions between the different personal and academic factors that may have affected university students during this stage.

The results of the study indicated that the students presented an average degree of fear towards COVID-19 and a high value of uncertainty, while high levels of depression, anxiety and stress were observed during this period. This is in line with different studies that conclude that COVID-19 mainly has a strong impact on stress and anxiety indexes [ 7 , 16 ], as well as depressive disorders of different natures [ 8 ]. However, and in the face of this situation, the students determined to a degree that we can consider appropriate that they found new teaching–learning strategies, as well as that their motivation towards their formative process prevailed. On the other hand, although it is true that high results were obtained in terms of the facilitating conditions proposed by the university, as well as a value close to the average in life satisfaction, we cannot consider it transcendental due to the high degree of variability found in the answers. In any case, we could affirm that, despite the high coefficients for these constructs, they have not had a positive effect on the indices of depression, anxiety, and stress of the participating university students, in contrast to what has been affirmed by studies in this sense [ 25 ]. This could be due to the notorious economic impact that students claim that COVID-19 has triggered in their lives, either because of their own work situation or that suffered by their families, which is a conclusion that coincides with that obtained by [ 47 ].

In addition, the significance of the structural model obtained invites us to make a series of reflections regarding the different findings that it presents, and the hypotheses raised at the beginning of the research: the adverse relationship between the fear of COVID and life satisfaction (H1), the growth of uncertainty (H2), or the statistically strong significant association between the fear of COVID-19 and the growth of stress, anxiety, and depression (H3). Regarding the first statement, it is obvious to link the occurrence of the disease with the decrease in the quality of life of students [ 9 ]. In the same way, the growth of uncertainty, the misinformative phenomena surrounding the virus, its nature, its effects, and possible ways of resolution, along with the possible consequences on their future education and work, promote a greater sense of panic towards the virus and its phenomenology. In relation to this evidence, it would also be related to the weight of uncertainty in the life satisfaction of students (H8), which is in line with previous studies [ 14 ]. Likewise, there is the incidence of uncertainty in anxiety, stress, and depression (H10), to which we could add the feeling of panic and dissatisfaction (H7), as stated in the scientific literature [ 15 ]. In sum, the uncertainty that existed during the change of educational scenario, and the accelerated solutions that the educational system had to implement at the beginning and during the confinement had a negative impact on the academic motivation indexes (H11), which is a statement that we share with previous works that turn in this sense [ 17 , 18 ].

While exposure to COVID-19 in general could lead to a decrease in positive perceptions of the academic process (H4), the results of the present study found a strong statistically significant association between the proliferation of fear of the virus and the pursuit of new teaching and learning strategies, the development of self-regulation towards learning, and an increase in motivation to achieve academic goals; this is a result which is in line with [ 44 ]. Likewise, preserving this academic motivation turned out to be a clear indicator for reducing depression, anxiety, and stress (H13). In order to promote this, we consider it necessary that the teacher communicates fluidly with students, provides continuous feedback on academic progress, and prevents the student from having the perception of isolation while following the virtual modality [ 45 ]. However, the adverse relationship found between motivation and the search for new strategies and the indices of life satisfaction is surprising, being the opposite of the hypothesis proposed at the beginning of the research (H9).

The majority presence of women (75.6%) in the study is consistent with their greater presence in degrees such as Educational Sciences or Psychopedagogy, the percentages of which can be over 90% [ 64 ]. In general, women mainly choose degrees in the Humanities, Experimental Sciences, Social Sciences, Law and Health because they like it, for their vocation, or to help other people [ 65 ]. This greater representation of women is not a limitation but a mirror of the situation of universities in Spain and the increase in female representation in higher education. Future studies would need to determine the mental health status prior to the COVID-19 pandemic, but this retrospective study seems very difficult, if not impossible, to carry out on the same sample. In the pre-pandemic state, university women have shown higher scores on depression and anxiety tests [ 66 ] although the interrelation of eating disorders and depression, which are more frequent in university women, should be taken into account in the future [ 67 ].

A lack of communication between teachers and students may be linked to the need to maintain social ties with others and participate in social activities, which, without them, may have led to the development of a sense of insecurity during the pandemic. During this time, other populations had difficulty accessing basic goods and services, and a greater number of mental health problems developed [ 68 ]. We speculate that the different containment policies between countries, greater access to online services, and different demands and expectations may have reduced mental health problems in our sample.

Finally, COVID-19 has had a negative repercussion on the students’ perception of the abrupt change that has taken place in the educational process (H5), which is an idea already reflected by other authors [ 23 ]. Likewise, the perception of adaptability to the new educational scenario that university students have is a strong dependency factor in the promotion of higher rates of life satisfaction (H6). It is a key factor, the development of which implies a lower index of stress, anxiety, and depression in the student body (H14), decreases uncertainty (H12), and creates a greater motivation towards academic progress (H15). Knowing the guidelines according to which distance learning is going to take place, the possible methods of evaluation during this period or mastering the technological resources with which the training process takes place are some of the possible indicators that promote an improvement in the personal factors of students, and it is necessary for universities to work on them [ 22 ].

7. Limitations and Future Research Directions

The main limitation observed is that the study followed a cross-sectional design and, therefore, the results are limited to the specific moment in which the data were collected, rather than representing the entire period in which the students were subjected to quarantine or confinement as a much longer period in which the change of teaching modality took place. Likewise, the results are limited to the specific sample studied, such that they cannot be generalized to the entire Spanish university population, as they only describe the moment of that reality, in this case, of the students enrolled at Andalusian Universities.

On the other hand, in terms of future lines of research, our work opens up the possibility of carrying out studies that deal with predictors of the different constructs we are talking about, as well as studies that propose more factors linked to the mental health of university students. These studies could address the medium- to long-term consequences of the pandemic if they are carried out in the post-pandemic period, and may offer the option of making comparisons with other universities in Spain, or even other countries.

8. Conclusions

The predictive power of the SEM model designed is sensitive to the determination of the influences between the different variables that compose it: fear of COVID-19, life satisfaction, uncertainty, anxiety and stress, motivation and configuration of new teaching–learning strategies, and perceptions of the degree of adaptability of the university to the new scenario, observing positive and negative relationships of influence between the different latent variables.

Both the pandemic and the confinement measures have had a strong negative impact on students’ levels of life satisfaction, depression, anxiety and stress. In order to face these challenges, students and universities themselves have shown great adaptability to these new circumstances by promoting personal protection measures and academic adaptations, but it is still necessary that university institutions continue to strengthen the attention to the student body, establishing fluid communications with them in order to adapt to emerging academic and personal needs.

Our study indicates that the outbreak of COVID-19 has had an influence on the mental health of university students, who have undergone an abrupt change in teaching methods because of the pandemic. Because the mental health of students is related to their academic performance, and even to university dropout, it is necessary that academic institutions themselves face measures that attempt to mitigate this influence, and that they carry out pragmatic studies to evaluate the effectiveness of these interventions in reducing the deterioration of academic function.

The results suggest that mental health problems may represent a much higher proportion than expected, and may lead to a deterioration of the academic role among university students. The incidence of mental health problems derived from the pandemic could emerge in the coming years with greater intensity, such that it is necessary to establish both academic and institutional anticipatory guidelines, including the recognition of mental health problems, the requests for mental healthcare by the student body, the social awareness of mental health problems, and the identification of mental health problems that may underlie poor academic performance.

As colleges and universities begin to grapple with the growing recognition of the important role that mental health plays in student success, especially in relation to the effects of the pandemic, more attention will need to be paid to broad-based interventions designed to improve the mental health of the student body. Given the magnitude of the problem, multidisciplinary solutions, more research to evaluate the effects of innovative and scalable mental health interventions, and the development of methods to triage college students in need of treatment are needed.

However, and despite having lived through a formative period that we can describe as extraordinary in nature, we cannot ignore the need for pedagogical teaching strategies and digital training to promote quality teaching. This emergency situation has highlighted the need for the future of transforming traditional education systems, the importance of promoting an immersion of technological resources in the ordinary teaching of students, and the promotion of fluid and continuous communication with students.

Acknowledgments

We thank the university students for their collaboration and participation in the study.

Funding Statement

This paper was funded by the Dirección General de Investigación y Transferencia del Conocimiento de la Junta de Andalucía (Spain), in the competitive call for research projects on SARS-CoV-2 and COVID-19 disease, co-financed with European FEDER public funds (Project I+D+i, Ref. CV20-01248).

Author Contributions

Conceptualization, G.G.-G. and J.-C.d.l.C.-C.; methodology, G.G.-G.; software, G.G.-G.; validation, G.G.-G.; formal analysis, C.R.-J.; investigation, M.R.-N.-P.; resources, C.R.-J.; data curation, J.-C.d.l.C.-C.; writing—original draft preparation, M.R.-N.-P.; writing—review and editing, J.-C.d.l.C.-C. and C.R.-J.; visualization, M.R.-N.-P.; supervision, G.G.-G.; project administration, J.-C.d.l.C.-C.; funding acquisition, G.G.-G. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of University of Granada (REF:0706/2020).

Informed Consent Statement

Informed consent was obtained from all of the subjects involved in the study. No individual or identifiable data were published as part of this manuscript.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Pandemic stress may have contributed to permanent changes in teen brains

dmbaker / iStock

A study published yesterday in Proceedings of the National Academy of Sciences, suggests that lockdowns and school closures may have prematurely aged the brains of adolescents—especially girls— who experienced significant stressors and changes in the early months of the COVID-19 pandemic.

The study came from researchers at the University of Washington who began a longitudinal study of magnetic resonance imaging (MRI) of the brain in 160 teens between 9 and 17 years in 2018. The study was originally meant to document age-related structural changes during adolescence. Participants were meant to undergo MRI brain scans every 2 years.  

But the study halted in 2020 when the pandemic began. Soon, however, researchers began to see value in looking at the brain during the pandemic, and in 2021, 3 years after the first images, 81% of the original cohort returned for another MRI.  

"Once the pandemic was underway, we started to think about which brain measures would allow us to estimate what the pandemic lockdown had done to the brain," said Neva Corrigan, PhD,   lead author and research scientist at the University of Washington’s Institute for Learning & Brain Sciences in a press release from that university. "What did it mean for our teens to be at home rather than in their social groups—not at school, not playing sports, not hanging out?"

They built a model based on 2018 images of what brains scans should have shown in 2021, then compared that result to images taken.  

Cortical thinning, especially in females  

The authors found significant evidence of excessive and premature cortical thinning, which occurs with age and is accelerated by stress. When compared to the models built using 2018 images, the thinning showed that the first year of the pandemic aged teen brains by 4.2 years for   girls and 1.4 years for boys.

The difference in the mean acceleration between girls and boys was 2.8 years.  

"Whereas this thinning was found to be widespread throughout the female brain, occurring in 30 brain regions across both hemispheres and all lobes of the brain, we found it to be limited to only two regions in the male brain, both located in the occipital lobe," the authors wrote.  

Girls' brains showed significant thinning in the bilateral fusiform, the left insula, and the left superior temporal cortex—all areas of the brain associated with social cognition. The authors speculate that social isolation during the early months of the pandemic hit girls the hardest.

"What the pandemic really seems to have done is to isolate girls. All teenagers got isolated, but girls suffered more. It affected their brains much more dramatically," said Patrica Kuhl, PhD, from the University of Washington.

What the pandemic really seems to have done is to isolate girls.

The cortical thinning, which is associated with depression and anxiety, is unlikely to correct or re-thicken. "It is possible that there might be some recovery," Kuhl said. "On the other hand, it’s also possible to imagine that brain maturation will remain accelerated in these teens."

Related news

Hospital caseload strain may have contributed to 1 in 5 covid deaths.

Cancer diagnoses lagged into year 2 of pandemic

New report: COVID more severe, longer-lasting than other respiratory diseases

Long-COVID rate among disabled people double that of able-bodied

Offices, long-distance shared transport, some activities tied to COVID spread

Study puts understanding of long COVID and vaccination into question

Study: COVID increased gender mortality gaps in wealthy countries

Weight-loss drug tied to lower risk of death from COVID, heart disease, all causes

This week's top reads

Seven percent of patients were diagnosed as having long COVID.

Higher-risk activities included carpooling with relatives and attending concerts.

COVID-19 participants most often reported fatigue, muscle aches, headache, and loss of taste and/or smell, consistent with the more extensive systemic COVID-19 effects.

Officials await testing clues from Missouri H5 avian flu case as Michigan reports more affected cows

CDC lab experts are working on sequencing to identify the neuraminidase and detail the genome, which could yield clues about the source.

Wearable activity trackers could offer early clues on COVID-19

For COVID-19 diagnosis, wearables were accurate 88% of the time.

A commentator likened the drug's effects to those of a vaccine against the indirect effects of a pathogen, without waning over time.

US COVID activity remains elevated as some indicators decline

Though most indicators showed downward trends, deaths were up compared to the previous week. 

Cambodia's recent H5N1 case involved novel reassortant

Earlier this year, animal health officials warned that the reassortant is spreading in the Greater Mekong subregion.

Mpox escalates in Africa as officials launch response plan

In Burundi's worsening outbreak, kids younger than 15 are the most affected group, similar to the DR Congo.

Saline drops reduce duration of common cold in kids, study finds

Fewer households reported family members catching a cold (46% vs 61% for usual care) when kids were given saline drops.  

Our underwriters

Unrestricted financial support provided by.

• Antimicrobial Resistance
• Chronic Wasting Disease
• All Topics A-Z
• Resilient Drug Supply
• Influenza Vaccines Roadmap
• CIDRAP Leadership Forum
• Roadmap Development
• Coronavirus Vaccines Roadmap
• Antimicrobial Stewardship
• Osterholm Update
• Newsletters
• About CIDRAP
• CIDRAP in the News
• Our Director
• Osterholm in the Press
• Shop Merchandise