research questions on impact of covid 19 on education

COVID Hurt Student Learning: Key Findings From a Year of Research

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Dozens of studies have come out over the past months concluding that the pandemic had a negative—and uneven—effect on student learning.

National analyses have shown that students who were already struggling fell further behind than their peers, and that Black and Latino students experienced greater declines in test scores than their peers.

But taken together, what implications do they have for school and district leaders looking for a path forward?

Here are four questions and answers, based on what we’ve learned from the most salient studies, that dig into the evidence.

Did students who stayed in remote learning longer fare worse than those who learned in person?

Generally, yes—but not in every single instance.

School buildings shut down in spring 2020 . By fall 2021, most students were back learning in person. But schools took a variety of different approaches in the middle, during the 2020-21 school year.

Several studies have attempted to examine the effects of the choices that districts made during that time period. And they found that students who were mostly in-person fared better than students who were mostly remote.

An analysis of 2021 spring state test data across 12 states found that districts that offered more access to in-person options saw smaller declines in math and reading scores than districts that offered less access. In reading, the effect was much larger in districts with a higher share of Black and Hispanic students.

Assessment experts, as well as the researchers, have urged caution about these results, noting that it’s hard to draw conclusions from results on spring 2021 state tests, given low rates of participation and other factors that affected how the tests were administered.

But it wasn’t just state test scores that were affected. Interim test scores—the more-frequent assessments that schools give throughout the year—saw declines too.

Another study examined scores on the Measures of Academic Progress assessment, or MAP , an interim test developed by NWEA, a nonprofit assessment provider. Researchers at NWEA, the American Institutes for Research, and Harvard examined data from 2.1 million students during the 2020-21 school year.

Students in districts that were remote during this period had lower achievement growth than students in districts that offered in-person learning. The effects were most substantial for high-poverty schools in remote learning districts.

Still, other research introduces some caveats.

The Education Recovery Scorecard, a collaboration between researchers at Stanford and Harvard, analyzed states’ scores on the 2022 National Assessment of Educational Progress. They compared these scores to the average amount of time that a district in the state spent in remote learning.

For the most part, this analysis confirmed the findings of previous research: In states where districts were remote longer, student achievement was worse. But there were also some outliers, like California. There, students saw smaller declines in math than average, even though the state had the highest closure rates on average. The researchers also noted that even among districts that spent the same amount of time in 2020-21 in remote learning, there were differences in achievement declines.

Are there other factors that could have contributed to these declines?

It’s probable. Remote learning didn’t take place in a vacuum, as educators and experts have repeatedly pointed out. But there’s not a lot of empirical evidence on this question just yet.

Children switched to virtual instruction as the pandemic unfolded around them—parents lost jobs, family members fell sick and died. In many cases, the school districts that chose remote learning served communities that also suffered some of the highest mortality rates from COVID.

The NWEA, AIR, and Harvard researchers—the group that looked at interim test data—note this. “It is possible that the relationships we have observed are not entirely causal, that family stress in the districts that remained remote both caused the decline in achievement and drove school officials to keep school buildings closed,” they wrote.

The Education Recovery Scorecard team plans to investigate the effects of other factors in future research, “such as COVID death rates, broadband connectivity, the predominant industries of employment and occupations for parents in the school district.”

Most of this data is from the 2020-21 school year. What’s happening now? Are students making progress?

They are—but it’s unevenly distributed.

NWEA, the interim assessment provider, recently analyzed test data from spring 2022 . They found that student academic progress during the 2021-22 school did start to rebound.

But even though students at both ends of the distribution are making academic progress, lower-scoring students are making gains at a slower rate than higher-scoring students.

“It’s kind of a double whammy. Lower-achieving students were harder hit in that initial phase of the pandemic, and they’re not achieving as steadily,” Karyn Lewis, the lead author of the brief, said earlier in November .

What should schools do in response? How can they know where to focus their efforts?

That depends on what your own data show—though it’s a good bet that focusing on math, especially for kids who were already struggling, is a good place to start.

Test results across the board, from the NAEP to interim assessment data, show that declines have been larger in math than in reading . And kids who were already struggling fell further behind than their peers, widening gaps with higher-achieving students.

But these sweeping analyses don’t tell individual teachers, or even districts, what their specific students need. That may look different from school to school.

“One of the things we found is that even within a district, there is variability,” Sean Reardon, a professor of poverty and inequality in education at Stanford University and a researcher on the Education Recovery Scorecard, said in a statement.

“School districts are the first line of action to help children catch up. The better they know about the patterns of learning loss, the more they’re going to be able to target their resources effectively to reduce educational inequality of opportunity and help children and communities thrive,” he said.

Experts have emphasized two main suggestions in interviews with Education Week.

• Figure out where students are. Teachers and school leaders can examine interim test data from classrooms or, for a more real-time analysis, samples of student work. These classroom-level data are more useful for targeting instruction than top-line state test results or NAEP scores, experts say.
• Districts should make sure that the students who have been disproportionately affected by pandemic disruptions are prioritized for support.

“The implication for district leaders isn’t just, ‘am I offering the right kinds of opportunities [for academic recovery]?’” Lewis said earlier this month. “But also, ‘am I offering them to the students who have been harmed most?’”

A version of this article appeared in the December 14, 2022 edition of Education Week as COVID Hurt Student Learning: Four Key Findings from A Year of Research

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Open Access

Peer-reviewed

Research Article

The impact of the COVID-19 pandemic on higher education: Assessment of student performance in computer science

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Computer Science, Lublin University of Technology, Lublin, Poland, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

Roles Conceptualization, Formal analysis, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Computer Science, Lublin University of Technology, Lublin, Poland

Roles Data curation, Software

• Małgorzata Charytanowicz, 
• Magdalena Zoła, 
• Waldemar Suszyński

• Published: August 14, 2024
• https://doi.org/10.1371/journal.pone.0305763
• Reader Comments

The COVID-19 pandemic had radically changed higher education. The sudden transition to online teaching and learning exposed, however, some benefits by enhancing educational flexibility and digitization. The long-term effects of these changes are currently unknown, but a key question concerns their effect on student learning outcomes. This study aims to analyze the impact of the emergence of new models and teaching approaches on the academic performance of Computer Science students in the years 2019–2023. The COVID-19 pandemic created a natural experiment for comparisons in performance during in-person versus synchronous online and hybrid learning mode. We tracked changes in student achievements across the first two years of their engineering studies, using both basic (descriptive statistics, t-Student tests, Mann-Whitney test) and advanced statistical methods (Analysis of variance). The inquiry was conducted on 787 students of the Lublin University of Technology (Poland). Our findings indicated that first semester student scores were significantly higher when taught through online (13.77±2.77) and hybrid (13.7±2.86) approaches than through traditional in-person means as practiced before the pandemic (11.37±3.9, p-value < 0.05). Conversely, third semester student scores were significantly lower when taught through online (12.01±3.14) and hybrid (12.04±3.19) approaches than through traditional in-person means, after the pandemic (13.23±3.01, p-value < 0.05). However, the difference did not exceed 10% of a total score of 20 points. With regard to the statistical data, most of the questions were assessed as being difficult or appropriate, with adequate discrimination index, regardless of the learning mode. Based on the results, we conclude that we did not find clear evidence that pandemic disruption and online learning caused knowledge deficiencies. This critical situation increased students’ academic motivation. Moreover, we conclude that we have developed an effective digital platform for teaching and learning, as well as for a secure and fair student learning outcomes assessment.

Citation: Charytanowicz M, Zoła M, Suszyński W (2024) The impact of the COVID-19 pandemic on higher education: Assessment of student performance in computer science. PLoS ONE 19(8): e0305763. https://doi.org/10.1371/journal.pone.0305763

Editor: Prabhat Mittal, Satyawati College (Eve.), University of Delhi, INDIA

Received: October 15, 2023; Accepted: June 4, 2024; Published: August 14, 2024

Copyright: © 2024 Charytanowicz 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 available at the following link: https://zenodo.org/records/11583297 .

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

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

1. Introduction

The COVID-19 pandemic brought with it a number of health, economic and social consequences. Indeed, the spread of the SARS-CoV-2 virus turned out to be so dangerous that many countries implemented new regulations in the educational field to limit physical contact. The pandemic-induced school shutdowns and sudden transition to remote teaching and learning at all levels of education. This change-over generated a number of technical and social problems [ 1 – 6 ]. These problems had also affected the academic community, although online or blended learning methods were implemented before the COVID-19 pandemic [ 7 ].

On March 12, 2020, a state of epidemic emergency was declared in Poland, and a week later–a state of pandemic. In consequence, the Minister of Science and Higher Education issued a regulation on the temporary suspension of the functioning of education institutes, lasting from March 12 till 25 2020 [ 8 , 9 ]. On March 25, 2020, the education system, including higher education, was switched to online teaching and learning, as necessitated by the need to maintain social distancing measures. Universities had to adapt to the circumstances almost overnight. However, many universities were not fully prepared with regard to technical capabilities, educational resources and the skills of the teaching staff in organizing distance education [ 10 – 12 ]. Before the COVID-19 pandemic, the applicable regulations of the Ministry of Science and Higher Education did not encourage the authorities of most universities to invest in technologies for conducting fully remote studies. Poland was, however, not an exception in this respect. Many old, prestigious universities in Europe were also reserved about remote learning, and the virtual learning environment was mainly used as a teaching aid.

Fortunately, the information revolution had by this time developed more flexible approaches to learning with the form of Information and Communication Technology (ICT). Indeed, it is one of the leading factors that affect current teaching methodology [ 13 – 18 ]. E-learning systems, their accessibility and functionality, have provided new possibilities to acquire knowledge and to ease the burden of learning. As an outcome, remote teaching and learning are often seen as promising solutions that offer high flexibility and a learner-centered approach that enables students to learn at their own pace [ 19 , 20 ]. Thus, the role of the teacher in the classroom has transformed from that of being the font of knowledge, to an instructional manager identifying relevant resources and creating collaborative learning opportunities. Moreover, online assessments have become increasingly important and now represent one of the most critical aspects of the educational process. Unfortunately, the role of ICT in higher education is still somewhat controversial.

The extreme situation caused by the COVID-19 pandemic provided an opportunity to revise our approach both to traditional and online learning, yet also posing challenges for the future of education systems. The main question of our research was whether the sudden transition to online teaching and learning caused by the COVID-19 pandemic had a negative impact on students academic performance and upon the reliability of the assessment process. We believe that our study can help to reduce the controversies related to remote learning and teaching.

2. Related works

Before the year 2020, the principal recipients of remote education were adults participating in professional development courses [ 21 ]. The COVID-19 pandemic outbreak, however, resulted in increased interest in methods of education that do not require physical meeting between students and teachers. The closure of educational institutions to mitigate the spread of COVID-19 compelled schools and universities to find alternative ways of continuing their operations. This led to the widespread adoption of online learning (e-learning).

The use of e-learning platforms has enabled the transformation of the traditional model of education in which the lecturer transmitted knowledge, into a model of supervised self-education. A separate line of research has been dedicated to the impact of remote education on university students, who are predominantly young adults, and, as such, are less subject to parental supervision. Topics under study include student attitudes towards distance learning [ 22 , 23 ], the technologies and learning platforms utilized [ 24 – 26 ], and the impact of network quality on the smoothness of classes [ 22 , 27 ].

A relatively well researched aspect of e-learning is the analysis of its advantages and disadvantages in comparison to traditional learning [ 28 – 30 ], including its application during the COVID-19 pandemic [ 31 – 34 ]. Undoubtedly, remote education has its benefits, among others, flexibility, speed, time savings [ 35 , 36 ], as well as better use of the infrastructure and organizational savings for the institution [ 37 ]. Distance learning in the form of e-learning also comes with drawbacks, for example, limited interpersonal contacts [ 38 ], lack of immediate feedback [ 39 , 40 ], and problems with self-discipline and adaptability [ 41 – 43 ]. Considering its strengths and weaknesses, e-learning can be viewed as either a replacement or augmentation of traditional approaches to education.

An integral part of remote education is the verification of its results. The topic was covered in literature in the pre-COVID era [ 44 – 46 ], but much less so during the pandemic [ 47 , 48 ]. Our work focuses on the analysis of student performance under the e-learning setup during COVID-19 related confinement and afterwards. The differentiating characteristic of this paper is the fact that it covers a longer period of time, unlike some other research focusing only on a single academic semester [ 49 ].

The COVID-19 pandemic has provided the opportunity to advance usage of online platforms and digital media, as well as to create new education strategies. It should be noted that most students (and instructors) adapted successfully to online teaching and learning [ 50 , 51 ]. However, certain studies [ 52 – 54 ] have indicated negative student feedback. In the year 2023, education has returned to more traditional teaching/learning approaches after more than two years of online learning.

The outbreak of COVID-19 presented a serious challenge to academic education by enforcing a drastic change in the teaching methods. For this reason, we formulated the following research questions:

• How had the COVID-19 pandemic change applied teaching and learning strategies?
• Did the COVID-19 pandemic have a disruptive effect on the academic performance of students resulting in knowledge deficiency?
• How did the change from in-person to online learning affect the reliability of student assessment?

The rest of the paper is structured as follows. Section 3 presents the context of the study, materials and methods. Section 4 explains the results obtained. Sections 5 and 6 conclude our work and describe limitations and future scope.

3. Materials and methods

3.1. design and context.

The research was conducted in the Department of Computer Science of the Lublin University of Technology in Poland, the largest public technical university in the Lublin voivodship. This was a cross-sectional study carried out among students who were enrolled in the first semester of engineering studies in the academic years 2019/2020, 2020/2021 and 2021/2022 (from October to July). Because of the COVID-19 pandemic, the courses of interest in this study were conducted in different delivery formats (in-person, synchronous online and hybrid).

Traditional in-person course delivery format included lectures and laboratories. The former involved, primarily, oral presentations given to a group of students. A teacher-centered approach to learning was applied with discussion and multimedia presentation, as well as whiteboard or chalkboard visual aids to emphasize important points in the lecture. Moreover, a Learning Management System (Moodle LMS) was incorporated within the lectures to develop, organize, deliver and manage didactic materials and assess the effectiveness of education via tests, surveys or assignments. This tool was also employed to provide discussion forums. The faculty used the activity Quiz as a student self-assessment tool, as well as to determine knowledge and skills.

With regard to laboratory work, practical classes were conducted in programming laboratories for the selected courses. In such a teaching/learning format, we found that most students preferred working alone or conducting discussions with their partners or their neighbors.

All students used online manuals or didactic materials delivered by Moodle LMS. Final exams were held at the University via Moodle LMS through in-person proctoring, as this approach allowed the introduction of a live person to monitor the activity of students in a testing environment.

In the synchronous online course format, students obtained theoretical and practical education entirely online via Microsoft Teams by way of video meetings and Moodle LMS. Meetings in Teams include audio, video and screen sharing. All lectures were delivered synchronously using MS Teams. Practical sessions were conducted through online synchronous video meetings in small student groups. Interaction occurred via the discussion board, while MS Teams was also employed to enable scheduled online consultations. Supporting materials (videos, presentations, tasks to do, quizzes, and other didactic materials) were provided to the students through the Moodle LMS. Final exams were conducted under controlled conditions via Moodle LMS through online live proctoring by accepting screen, video and audio sharing.

The hybrid course delivery format combined in-person and online strategies. Students obtained theoretical education entirely online as synchronous sessions by way of MS Teams and Moodle LMS, whilst practical education was obtained through the traditional in-person format, in small student groups. Final exams were held at the University via Moodle LMS through in-person proctoring.

We analyzed exam scores across the first two years of the engineering studies using anonymous data from the Moodle. The Research Ethics Committee of Lublin University of Technology approved the study (Ethical Approval Reference: 3/2023).

3.2. Course selection

The following criteria were used to select the courses:

• the courses covered algorithms and programming,
• the courses had unchanged objectives and learning outcomes during the investigated period,
• the courses were conducted by the same instructors using to the same tools and methods.

Two compulsory courses met these criteria: 1 –Introduction to Computer Science and 2 –Numerical Analysis Algorithms. Both courses were conducted in the Polish language and they provided fundamental knowledge for all areas of Computer Science learning and skills development. Enrolled students were obligated to complete 30 lesson hours of theory and 30 lesson hours of practical experience within a course length of 15 weeks. In the full-time option, four hours of classes were given each course week, and were distributed into two two-hour sessions. Herein, the first consisted of a master class lecture and the second consisted of an interactive problem-based learning laboratory. In the part-time option, the number of in-person teaching hours was reduced to half and classes were held, on average, twice a month, on Saturday and Sunday.

The Introduction to Computer Science course is taught in the first year and is covered in the first semester. Students who successfully completed the course gained five credits, according to the European Credit Transfer and Accumulation System (ECTS). The intention of the offered course is to provide students with knowledge of standard algorithms and data structures, and to provide them with the skills to analyze both the theoretical complexity of algorithms and their practical behaviors. The course covers the following topics:

• Introduction to algorithms and problem-solving techniques.
• Basic programming concepts, types, sequential data structures.
• Programming in Python.
• Searching and sorting algorithms.
• Examples of algorithms, algorithmic strategies.
• Testing and documenting programming code.
• Asymptotic notation and complexity analysis.
• Analyzing program code for correctness, efficiency, and errors.
• Automata theory and formal languages. Turing machine.
• Classes P and NP.

The knowledge and skills to implement and solve algorithmic problems using the mentioned algorithms are developed using Python.

The Numerical Analysis Algorithms course is taught in the second year and is covered in the third semester. Successful completion awards students with five credits, according to ECTS. The primary objective of the course is to develop basic understanding of numerical algorithms, as well as the skills to implement algorithms to solve computer-based mathematical problems. The course covers the following topics:

• Basic numerics, floating-point representation, convergence.
• Horner’s scheme.
• The theory of interpolation: Lagrange polynomial, Hermite interpolation, Neville’s iterative formula.
• Least square approximation.
• Numerical integration: Newton-Cotes formulas, Gaussian quadrature.
• Direct methods for solving systems of linear equations: Gaussian elimination, LU factorization, Cholesky decomposition.
• Householder method.
• Solving nonlinear equations and systems of nonlinear equations: Bisection method, fixed-point iteration, Newton’s method.
• Runge-Kutta methods for ordinary differential equations.
• Characteristic polynomial and eigenvalues.

The knowledge and skills to implement and solve algorithmic problems using the mentioned algorithms were developed using C++ due to its object-oriented programming with high performance, efficient memory management, low-level access to hardware and a rich standard library, including mathematical functions commonly used in numerical algorithms. These allow students to write efficient and customizable numerical algorithms. Objective C++ was one of the courses of the first year of studies.

3.3. The study participants

Study participants were selected from Computer Science students who were enrolled in the two mentioned compulsory courses: Introduction to Computer Science (ICS) (first semester) and Numerical Analysis Algorithms (NAA) (third semester). The first group of students began their studies in the academic year 2019/2020 in a traditional in-person course delivery format that was interrupted because of the confinement. They then continued their studies utilizing the synchronous online format. The second group consisted of students who began their studies in academic year 2020/2021 in the synchronous online format and continued these activities in a hybrid format. The third group of students began their studies in academic year 2021/2022 in a hybrid format that returned to an in-person format in the year 2022/2023. Online learning was supported by Moodle and MS Teams.

Only students enrolled in either the ICS and NAA courses participated in our research. Students who interrupted their studies and did not complete the courses were excluded. Thus, the study group included students who were enrolled in both courses and took both final exams. A total of 787 participants were selected. Table 1 summarizes the study participant groups according to education strategy.

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https://doi.org/10.1371/journal.pone.0305763.t001

Males constituted 87.5% of the total study participants, while females constituted 12.5%. Regarding nationality, the majority, i.e. 85.5%, came from Poland, while 14.5% came from other countries, mainly Ukraine.

3.4. Online exam quizzes

In this study, the Moodle platform provided by the Computer Science Department from the Lublin University of Technology was applied to conduct the final exam process. Comparative analysis of student academic performance was anchored on the results obtained in their final exams. Final exams were carried through the Moodle platform using Quiz activity . All exams comprised questions of various types, including Multiple Choice , Short Answer , Numerical and Essay as follows:

• Multiple choice questions were employed for evaluating both theoretical and practical contents. For our purpose, the option Multiple answers are allowed was used. Multiple answers questions enable one or more answers to be chosen by providing check boxes next to the answers. We used a negative grade percentage for wrong answers, so that simply ticking all choices did not necessarily generate a full grade. If the sum of partial grades was negative, then the total grade for this question would be zero [ 55 ].
• Short answer or numerical questions were used to evaluate theoretical and practical contents. In a short answer question, the student types in a word or phrase in response to a question. This must exactly match one of the acceptable answers. Numerical questions resembled short-answer questions. Here, the difference was that numerical answers were allowed to have an accepted error for number.
• Essay questions were used to evaluate practical contents, mainly programming and coding skills. We employed essay-type questions to provide the option of answering by entering text online. The option Require the student to enter text was chosen. The Response format option was set to Plain text , monospaced font to improve the readability of code by ensuring consistent and clear alignment. This is particularly helpful for maintaining an organized layout. The essay questions had to be marked manually by the course instructor.

The number of multiple choice questions and short answer / numerical questions was comparable. One question was an essay question. Questions were created and stored separately in a Question bank and were organized into 10 categories according to the implemented curricula and learning outcomes. Each category consisted of at least 50 questions. Quiz settings were as follows:

• Quizzes included 20 questions worth 20 points. There were two categories of questions: theoretical and practical.
• Students were allowed to have one attempt at each quiz. The time limit option was set to 60 minutes.
• Students were not allowed to open other windows or programs while taking these quizzes.
• A password was required. The option Block concurrent connections was checked.
• The Choose Sequential navigation method was employed to compel the student to progress through the questions in order and not return to a previous question or skip to a later one.
• The timeframe when the students were able to see feedback was set to the option After the quiz is closed and the option Whether correct was checked.
• Employed questions were assessed for quality and modified for re-use in the next academic year.

Students were tested using the same evaluation methods and types of questions in in-person, synchronous online and hybrid groups. The Moodle platform collected assessment data and generated report statistics. The data containing students’ exam results (points) were collected and exported from the Moodle platform as.xlsx files.

3.5. Quiz report statistics

Quiz statistics provided test statistics and quiz structure analysis. The test statistics gave information on how students performed on a quiz, and employed descriptive statistics: average grade, median grade, standard deviation of grades, skewness and kurtosis. A detailed analysis of each question was given in quiz structure analysis, and applied the following measures: facility index, discrimination index and discriminative efficiency. Discriminative efficiency is a measure similar to discrimination index [ 55 ].

Facility index.

In this work, facility index of a question was determined by the average score divided by the maximum score and represented as a percentage. A higher value indicated an easier question. The interpretation of its values is given in Table 2 [ 55 ].

https://doi.org/10.1371/journal.pone.0305763.t002

Discrimination index.

Discrimination index is the correlation between the score for this question and the score for the whole quiz represented as a percentage. If the score for the question and the score for the test are well correlated, the question can be categorized as a question with good discrimination. The maximum discrimination requires a facility index in the range 30%–70%, although this is not tantamount to high discrimination index. Discrimination index values should be interpreted according to Table 3 [ 55 ].

https://doi.org/10.1371/journal.pone.0305763.t003

A negative value of a discrimination index would mean that the best students got this question wrong more often than the worst students. A discrimination index of zero would mean it was a poor discriminator between good and bad students. Discrimination index is considered excellent when the value is higher than 40%, and considered good when it ranges from 20% to 40%.

Discriminative efficiency.

The discriminative efficiency estimates how good the discrimination index is relative to the difficulty of the question. This attempts to discriminate between students of different ability, and the higher the value, the better is the question at discriminating between students of different abilities [ 55 ]. Values between 30%–50% provide adequate discrimination, while those above 50% provide very good discrimination.

3.6. Statistical analysis

Data collected was tabulated, and analysis was carried out by applying simple percentage analysis, as well as descriptive analysis, using mean, standard deviation and inferential analysis such as t-Student tests and ANOVA [ 56 , 57 ]. We performed non-parametric alternatives such as a Mann-Whitney U test and the Kruskal-Wallis test to compare samples that cannot be assumed to be normally distributed [ 58 , 59 ]. Statistical significance was set at p<0.05. Data analysis was performed using the Statistica Package, Version 13 (TIBCO Software Inc.).

Participants’ profile

Our study included 787 Computer Science students, aged 18 to 22 years. The participant background characteristics revealed that most students were male (87.5%) and native (Polish; 85.5%). Furthermore, most of the students were enrolled in full-time studies (85.5%) ( Table 4 ).

https://doi.org/10.1371/journal.pone.0305763.t004

The percentages of the students who began their studies in the academic years 2019/2020, 2020/2021 and 2021/2022 were comparable, around 30%. An important aspect of the analysis was the availability of data from the pre-pandemic period that was relevant for our investigations.

Comparison of in-person, synchronous online and hybrid learning

The comparison of in-person, synchronous online, and hybrid teaching methods in student learning outcomes based on background characteristics is presented in Tables 5 and 6 .

https://doi.org/10.1371/journal.pone.0305763.t005

https://doi.org/10.1371/journal.pone.0305763.t006

The findings indicated that for the first semester course Introduction to Computer Science, the relation between learning outcomes and student gender was insignificant (p = 0.427). Moreover, the relation between learning outcomes and study option was also insignificant (p = 0.223). However, there was statistically significant difference between learning outcomes and residency status (p < 0.001). The findings indicated that during in-person and online studies, native students had significantly higher learning outcomes than did non-native students (p < 0.001). In addition, full-time students of online studies had significantly higher learning outcomes (p = 0.002) than did part-time students.

Regarding the learning outcomes of the students as obtained in the third semester course Numerical Analysis Algorithms, gender and study options were also insignificant (p = 0.834; p = 0.157) in relation to learning outcomes. In contrast, residency status was significant (p < 0.001). The findings indicate that native students had significantly higher learning outcomes than did non-native students (p < 0.001). Moreover, full-time students of online studies had significantly higher learning outcomes as compared to part-time students (p = 0.011).

The comparison of teaching methods in participant performance based on different semesters (courses) is presented in Table 7 .

https://doi.org/10.1371/journal.pone.0305763.t007

The differences in mean scores related to the first semester course Introduction to Computer Science, during online and hybrid studies, were significantly higher compared to in-person studies (LSD post-hoc, p < 0.001). However, mean scores related to the third semester course Numerical Analysis Algorithms, during online and hybrid studies, were significantly lower in comparison to in-person studies (LSD post-hoc, p < 0.001). Switching to traditional in-person studies in the academic year 2022/2023 did not degrade student performance.

Quiz quality assessment

Tables 8 and 9 reveal the facility index, discrimination index and discriminative efficiency values from the final exams held from 2019/2020 to 2022/2023.

https://doi.org/10.1371/journal.pone.0305763.t008

https://doi.org/10.1371/journal.pone.0305763.t009

The lowest mean facility index was 47% ± 25%, while the highest mean facility index was 59% ± 20%. Moreover, the mean discrimination index was located within the range between 31% and 37% and the mean discriminative efficiency was found within the range between 43% and 54%. The results indicate, with regard to facility index, that most of the questions were moderately difficult, yet about right for the average student, and demonstrated adequate discrimination—regardless of the course delivery format.

5. Discussion and conclusions

In our study, we compared the learning outcomes of Computer Science students who were taught through synchronous online and hybrid systems, to those who learned in the traditional in-person system, and this revealed significantly higher learning outcomes when taught through online and hybrid systems versus in-person. It is worth noting that student scores showed an increasing trend in the years 2019–2023. Despite this, the significant difference in the results of the students’ final examination was not too large–as it did not exceed 10% of the maximal score.

A comparison between the student groups demonstrates that utilizing synchronous online learning can result in more enhanced educational opportunities for students. However, our findings indicated that native students had significantly higher learning outcomes than did non-native students. The reason could be that the study courses were held in Polish, which is a difficult language for non-native students to learn and utilize.

Several research studies have shown that online learning and the combination of online and in-person learning systems have positive and powerful roles in enhancing the effectiveness of education [ 19 , 29 , 41 , 47 , 60 ]. However, along with enhanced accessibility and flexibility, pure online learning also has several disadvantages, notably, the lack of interpersonal contacts and student satisfaction. In the hybrid form, however, flexibility and accessibility are enhanced, while human connection occurs.

Our results indicated that synchronous online learning could be appreciated as a successful method of conducting Computer Science education and can be used as a tool supporting traditional in-person methods. Although this approach is a little less flexible for teachers and students, and requires reliable technology, in comparison to asynchronous learning, this allows for more real time engagement and feedback [ 61 ].

As the effective measurement of knowledge acquired is an important component of Computer Science education, the use of the Moodle quizzes activity as a continuous assessment of students was analyzed according to statistical data such as the facility index, discrimination index and discriminative efficiency. Out of the exam tests conducted from the academic year 2019/2020 to 2022/2023, the mean facility index scores ranged from 47% to 59% and the mean discrimination index ranged from 31% to 37%. The statistic results indicated that, regarding facility index, most of the questions were moderately difficult and about right for the average student regardless of the course delivery format, and that a consistent and adequate level of discrimination indices was maintained. In addition, the similar results obtained in our study no matter the year, with three different groups of students, also confirmed the validity and reliability of the designed exam tests.

Although online learning requires extensive self-discipline, it allows universities to integrate new technologies into their offer, and hence, effectively facilitate the student learning process. After the COVID-19 pandemic, there has been a quick transition back to in-person teaching, but still there are many proffered activities being in an online format. At present, many students state that they prefer to learn through hybrid learning methods. Furthermore, several studies have shown that e-learning methods are used widely by students outside of their formal curricula for continuing their professional education [ 62 ]. This indicates that students and professionals appreciate and take advantage of self-paced learning environments in which they control their learning pace, information flow, selection of learning activities, as well as their time management. Thus, the digital transformation of the educational process has become a necessity to meet shifting student demands and seems to be one of the leading factors that affect current teaching methodology.

It is worth noting that the extreme situation caused by the COVID-19 pandemic provided an opportunity to revise our approach, both to traditional and online learning, but also posed challenges for the future of education systems. In conclusion, the results of the analysis allow us to answer the questions formulated before in the following way.

• The COVID-19 confinement caused online education, which previously was mainly used as an addition to traditional learning methods, to become the mainstream, in particular, in Computer Science.
• The COVID-19 pandemic did not have a disruptive effect that resulted in knowledge deficiency with regard to the academic performance of Computer Science students. In contrast, this situation increased student academic motivation. Indeed, students demonstrated higher exam scores during subsequent two academic years.
• Despite the change from in-person to online learning, the reliability of student assessment remained at similar levels.

6. Limitations and future works

Our context is algorithms and programming in the first two years of the engineering studies program. While we believe that the long period under study is an advantage of this work, its limitation is the fact that it focuses only on the students of Computer Science. We based our research on the data comprising the performance of students in only two courses. Moreover, only the exam scores from the 1 st and 3 rd semesters were included in the study. The courses of other semesters were not assessed because they did not meet the required assumptions regarding the course selection. Another limitation of our study was that students could share information about the content of the exam. However, we randomly assigned students to subcategory sets to avoid sharing information. In the future it is worth considering extending the analysis to students of other fields, as well as take into account student performance in more courses.

Acknowledgments

The authors thank Mr Jack Dunster for linguistic improvement of the text.

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The Impact of COVID-19 on Education: A Meta-Narrative Review

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• Published: 05 July 2022
• Volume 66 , pages 883–896, ( 2022 )

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• Aras Bozkurt   ORCID: orcid.org/0000-0002-4520-642X 1 , 2 , 3 ,
• Kadir Karakaya   ORCID: orcid.org/0000-0003-3375-1532 4 ,
• Murat Turk   ORCID: orcid.org/0000-0002-5105-2578 5 ,
• Özlem Karakaya   ORCID: orcid.org/0000-0002-9950-481X 6 &
• Daniela Castellanos-Reyes   ORCID: orcid.org/0000-0002-0183-1549 7  

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The rapid and unexpected onset of the COVID-19 global pandemic has generated a great degree of uncertainty about the future of education and has required teachers and students alike to adapt to a new normal to survive in the new educational ecology. Through this experience of the new educational ecology, educators have learned many lessons, including how to navigate through uncertainty by recognizing their strengths and vulnerabilities. In this context, the aim of this study is to conduct a bibliometric analysis of the publications covering COVID-19 and education to analyze the impact of the pandemic by applying the data mining and analytics techniques of social network analysis and text-mining. From the abstract, title, and keyword analysis of a total of 1150 publications, seven themes were identified: (1) the great reset, (2) shifting educational landscape and emerging educational roles (3) digital pedagogy, (4) emergency remote education, (5) pedagogy of care, (6) social equity, equality, and injustice, and (7) future of education. Moreover, from the citation analysis, two thematic clusters emerged: (1) educational response, emergency remote education affordances, and continuity of education, and (2) psychological impact of COVID-19. The overlap between themes and thematic clusters revealed researchers’ emphasis on guaranteeing continuity of education and supporting the socio-emotional needs of learners. From the results of the study, it is clear that there is a heightened need to develop effective strategies to ensure the continuity of education in the future, and that it is critical to proactively respond to such crises through resilience and flexibility.

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Introduction

The Coronavirus (COVID-19) pandemic has proven to be a massive challenge for the entire world, imposing a radical transformation in many areas of life, including education. It was rapid and unexpected; the world was unprepared and hit hard. The virus is highly contagious, having a pathogenic nature whose effects have not been limited to humans alone, but rather, includes every construct and domain of societies, including education. The education system, which has been affected at all levels, has been required to respond to the crisis, forced to transition into emergency modes, and adapt to the unprecedented impact of the global crisis. Although the beginning of 2021 will mark nearly a year of experience in living through the pandemic, the crisis remains a phenomenon with many unknowns. A deeper and more comprehensive understanding of the changes that have been made in response to the crisis is needed to survive in these hard times. Hence, this study aims to provide a better understanding by examining the scholarly publications on COVID-19 and education. In doing this, we can identify our weaknesses and vulnerabilities, be better prepared for the new normal, and be more fit to survive.

Related Literature

Though the COVID-19 pandemic is not the first major disruption to be experienced in the history of the world, it has been unique due to its scale and the requirements that have been imposed because of it (Guitton, 2020 ). The economies of many countries have greatly suffered from the lockdowns and other restrictive measurements, and people have had to adapt to a new lifestyle, where their primary concern is to survive by keeping themselves safe from contracting the deadly virus. The education system has not been exempt from this series of unfortunate events inflicted by COVID-19. Since brick-and-mortar schools had to be closed due to the pandemic, millions of students, from those in K-12 to those in higher education, were deprived of physical access to their classrooms, peers, and teachers (Bozkurt & Sharma, 2020a , b ). This extraordinary pandemic period has posed arguably the most challenging and complex problems ever for educators, students, schools, educational institutions, parents, governments, and all other educational stakeholders. The closing of brick-and-mortar schools and campuses rendered online teaching and learning the only viable solution to the problem of access-to-education during this emergency period (Hodges et al., 2020 ). Due to the urgency of this move, teachers and instructors were rushed to shift all their face-to-face instruction and instructional materials to online spaces, such as learning management systems or electronic platforms, in order to facilitate teaching virtually at a distance. As a result of this sudden migration to learning and instruction online, the key distinctions between online education and education delivered online during such crisis and emergency circumstances have been obfuscated (Hodges et al., 2020 ).

State of the Current Relevant Literature

Although the scale of the impact of the COVID-19 global pandemic on education overshadows previously experienced nationwide or global crises or disruptions, the phenomenon of schools and higher education institutions having to shift their instruction to online spaces is not totally new to the education community and academia (Johnson et al., 2020 ). Prior literature on this subject indicates that in the past, schools and institutions resorted to online or electronic delivery of instruction in times of serious crises and uncertainties, including but not limited to natural disasters such as floods or earthquakes (e.g., Ayebi-Arthur, 2017 ; Lorenzo, 2008 ; Tull et al., 2017 ), local disruptions such as civil wars and socio-economic events such as political upheavals, social turmoils or economic recessions (e.g., Czerniewicz et al., 2019 ). Nevertheless, the past attempts to move learning and teaching online do not compare to the current efforts that have been implemented during the global COVID-19 pandemic, insofar as the past crisis situations were sporadic events in specific territories, affecting a limited population for relatively short periods of time. In contrast, the COVID-19 pandemic has continued to pose a serious threat to the continuity of education around the globe (Johnson et al., 2020 ).

Considering the scale and severity of the global pandemic, the impacts it has had on education in general and higher education in particular need to be explored and studied empirically so that necessary plans and strategies aimed at reducing its devastating effects can be developed and implemented. Due to the rapid onset and spread of the global pandemic, the current literature on the impact of COVID-19 on education is still limited, including mostly non-academic editorials or non-empirical personal reflections, anecdotes, reports, and stories (e.g., Baker, 2020 ; DePietro, 2020 ). Yet, with that said, empirical research on the impact of the global pandemic on higher education is rapidly growing. For example, Johnson et al. ( 2020 ), in their empirical study, found that faculty members who were struggling with various challenges adopted new instructional methods and strategies and adjusted certain course components to foster emergency remote education (ERE). Unger and Meiran ( 2020 ) observed that the pandemic made students in the US feel anxious about completing online learning tasks. In contrast, Suleri ( 2020 ) reported that a large majority of European higher education students were satisfied with their virtual learning experiences during the pandemic, and that most were willing to continue virtual higher education even after the pandemic (Suleri, 2020 ). The limited empirical research also points to the need for systematically planning and designing online learning experiences in advance in preparation for future outbreaks of such global pandemics and other crises (e.g., Korkmaz & Toraman, 2020 ). Despite the growing literature, the studies provide only fragmentary evidence on the impact of the pandemic on online learning and teaching. For a more thorough understanding of the serious implications the pandemic has for higher education in relation to learning and teaching online, more empirical research is needed.

Unlike previously conducted bibliometric analysis studies on this subject, which have largely involved general analysis of research on health sciences and COVID-19, Aristovnik et al. ( 2020 ) performed an in-depth bibliometric analysis of various science and social science research disciplines by examining a comprehensive database of document and source information. By the final phase of their bibliometric analysis, the authors had analyzed 16,866 documents. They utilized a mix of innovative bibliometric approaches to capture the existing research and assess the state of COVID-19 research across different research landscapes (e.g., health sciences, life sciences, physical sciences, social sciences, and humanities). Their findings showed that most COVID-19 research has been performed in the field of health sciences, followed by life sciences, physical sciences, and social sciences and humanities. Results from the keyword co-occurrence analysis revealed that health sciences research on COVID-19 tended to focus on health consequences, whereas the life sciences research on the subject tended to focus on drug efficiency. Moreover, physical sciences research tended to focus on environmental consequences, and social sciences and humanities research was largely oriented towards socio-economic consequences.

Similarly, Rodrigues et al. ( 2020 ) carried out a bibliometric analysis of COVID-19 related studies from a management perspective in order to elucidate how scientific research and education arrive at solutions to the pandemic crisis and the post-COVID-19 era. In line with Aristovnik et al.’s ( 2020 ) findings, Rodrigues et al. ( 2020 ) reported that most of the published research on this subject has fallen under the field of health sciences, leaving education as an under-researched area of inquiry. The content analysis they performed in their study also found a special emphasis on qualitative research. The descriptive and content analysis yielded two major strands of studies: (1) online education and (2) COVID-19 and education, business, economics, and management. The online education strand focused on the issue of technological anxiety caused by online classes, the feeling of belonging to an academic community, and feedback.

Lastly, Bond ( 2020 ) conducted a rapid review of K-12 research undertaken in the first seven months of the COVID-19 pandemic to identify successes and challenges and to offer recommendations for the future. From a search of K-12 research on the Web of Science, Scopus, EBSCOHost, the Microsoft Academic, and the COVID-19 living systematic map, 90 studies were identified and analyzed. The findings revealed that the reviewed research has focused predominantly on the challenges to shifting to ERE, teacher digital competencies and digital infrastructure, teacher ICT skills, parent engagement in learning, and students’ health and well-being. The review highlighted the need for straightforward communication between schools and families to inform families about learning activities and to promote interactivity between students. Teachers were also encouraged to develop their professional networks to increase motivation and support amongst themselves and to include opportunities for both synchronous and asynchronous interaction for promoting student engagement when using technology. Bond ( 2020 ) reported that the reviewed studies called for providing teachers with opportunities to further develop their digital technical competencies and their distance and online learning pedagogies. In a recent study that examines the impact of COVID-19 at higher education (Bozkurt, 2022 ), three broad themes from the body of research on this subject: (1) educational crisis and higher education in the new normal: resilience, adaptability, and sustainability, (2) psychological pressures, social uncertainty, and mental well-being of learners, and (3) the rise of online distance education and blended-hybrid modes. The findings of this study are similar to Mishra et al. ( 2021 ) who examined the COVID-19 pandemic from the lens of online distance education and noted that technologies for teaching and learning and psychosocial issues were emerging issues.

The aforementioned studies indicate that a great majority of research on COVID-19 has been produced in the field of health sciences, as expected. These studies nonetheless note that there is a noticeable shortage of studies dealing with the effects of the pandemic in the fields of social sciences, humanities, and education. Given the profound impact of the pandemic on learning and teaching, as well as on the related stakeholders in education, now more than ever, a greater amount of research on COVID-19 needs to be conducted in the field of education. The bibliometric studies discussed above have analyzed COVID-19 research across various fields, yielding a comparative snapshot of the research undertaken so far in different research spheres. However, despite being comprehensive, these studies did not appear to have examined a specific discipline or area of research in depth. Therefore, this bibliometric study aims to provide a focused, in-depth analysis of the COVID-19-related research in the field of education. In this regard, the main purpose of this study is to identify research patterns and trends in the field of education by examining COVID-19-related research papers. The study sought to answer the following research questions:

What are the thematic patterns in the title, abstract, and keywords of the publications on COVID-19 and education?

What are the citation trends in the references of the sampled publications on COVID-19 and education?

Methodology

This study used data mining and analytic approaches (Fayyad et al., 2002 ) to examine bibliometric patterns and trends. More specifically, social network analysis (SNA) (Hansen et al., 2020 ) was applied to examine the keywords and references, while text-mining was applied (Aggarwal & Zhai, 2012 ) to examine the titles and abstracts of the research corpus. Keywords represent the essence of an article at a micro level and for the analysis of the keywords, SNA was used. SNA “provides powerful ways to summarize networks and identify key people, [entities], or other objects that occupy strategic locations and positions within a matrix of links” (Hansen et al., 2020 , p. 6). In this regard, the keywords were analyzed based on their co-occurrences and visualized on a network graph by identifying the significant keywords which were demonstrated as nodes and their relationships were demonstrated with ties. For text-mining of the titles and abstracts, the researchers performed a lexical analysis that employs “two stages of co-occurrence information extraction—semantic and relational—using a different algorithm for each stage” (Smith & Humphreys, 2006 , p. 262). Thus, text-mining analysis enabled researchers to identify the hidden patterns and visualize them on a thematic concept map. For the analysis of the references, the researchers further used SNA based on the arguments that “citing articles and cited articles are linked to each other through invisible ties, and they collaboratively and collectively build an intellectual community that can be referred to as a living network, structure, or an ecology” (Bozkurt, 2019 , p. 498). The analysis of the references enabled the researchers to identify pivotal scholarly contributions that guided and shaped the intellectual landscape. The use of multiple approaches enables the study to present a broader view, or a meta-narrative.

Sample and Inclusion Criteria

The publications included in this research met the following inclusion criteria: (1) indexed by the Scopus database, (2) written in English, and (3) had the search queries on their title (Table 1 ). The search query reflects the focus on the impact of COVID-19 on education by including common words in the field like learn , teach , or student . Truncation was also used in the search to capture all relevant literature. Narrowing down the search allowed us to exclude publications that were not education related. Scopus was selected because it is one of the largest scholarly databases, and only publications in English were selected to facilitate identification of meaningful lexical patterns through text-mining and provide a condensed view of the research. The search yielded a total of 1150 papers (articles = 887, editorials = 66, notes = 58, conference papers = 56, letters = 40, review studies = 30, book chapters = 9, short surveys = 3, books = 1).

Data Analysis and Research Procedures

This study has two phases of analysis. In the first phase, text mining was used to analyze titles and abstracts, and SNA was applied to analyze keywords. By using two different analytical approaches, the authors were able to triangulate the research findings (Thurmond, 2001 ). In this phase, using lexical algorithms, text mining analysis enabled visualizing the textual data on a thematic concept map according to semantic relationships and co-occurrences of the words (Fig.  1 ). Text mining generated a machine-based concept map by analyzing the co-occurrences and lexical relationships of textual data. Then, based on the co-occurrences and centrality metrics, SNA enabled visualizing keywords on a network graphic called sociogram (Fig.  2 ). SNA allowed researchers to visually identify the key terms on a connected network graph where keywords are represented as nodes and their relationships are represented as edges. In the first phase of the study, by synthesizing outputs of the data mining and analytic approaches, meaningful patterns of textual data were presented as seven main research themes.

Thematic concept mapping of COVID-19 and education-related papers

Social networks analysis of the keywords in COVID-19 and education-related papers

In the second phase of the study, through the examination of the references and citation patterns (e.g., citing and being cited) of the articles in the research corpus, the citation patterns were visualized on a network graphic by clusters (See Fig.  3 ) showing also chronical relationships which enabled to identify pivotal COVID-19 studies. In the second phase of the study, two new themes were identified which were in line with the themes that emerged in the first phase of the study.

Social networks analysis of the references in COVID-19 and education-related papers 2019–2020 (Only the first authors were labeled – See Appendix Fig. 4 for SNA of references covering pre-COVID-19 period)

Strengths and Limitations

This study is one of the first attempts to use bibliometric approaches benefiting from data mining and analysis techniques to better understand COVID-19 and its consequences on published educational research. By applying such an approach, a large volume of data is able to be visualized and reported. However, besides these strengths, the study also has certain limitations. First, the study uses the Scopus database, which, though being one of the largest databases, does not include all types of publications. Therefore, the publications selected for this study offer only a partial view, as there are many significant publications in gray literature (e.g., reports, briefs, blogs). Second, the study includes only publications written in English, however, with COVID-19 being a global crisis, publications in different languages would provide a complementary view and be helpful in understanding local reflections in the field of education.

Findings and Discussion

Sna and text-mining: thematic patterns in the title, abstract, and keywords of the publications.

This section reports the findings based on a thematic concept map and network graphic that were developed through text mining (Fig.  1 —Textual data composed of 186.234 words visualized according to lexical relationships and co-occurrences) and sociograms created using SNA (Fig.  2 —The top 200 keywords with highest betweenness centrality and 1577 connections among them mapped on a network graph) to visualize the data. Accordingly, seven major themes were identified by analyzing the data through text-mining and SNA: (1) the great reset, (2) digital pedagogy, (3) shifting educational landscape and emerging educational roles, (4) emergency remote education, (5) pedagogy of care, (6) social equity, equality, and injustice, and (7) future of education.

Theme 1: The Great Reset (See path Fig.  1 : lockdown  +  emergency  +  community  +  challenges  +  during  >  pandemic and impact  >  outbreak  >  coronavirus  >  pandemic and global  >  crisis  >  pandemic  >  world; See nodes on Fig.  2 : Covid19, pandemic, Coronavirus, lockdown, crisis ). The first theme in the thematic concept map and network graphic is the Great Reset. It has been relatively a short time since the World Health Organization (WHO) declared the COVID-19 a pandemic. Although vaccination had already started, the pandemic continued to have an adverse impact on the world. Ever since the start of the pandemic, people were discussing when there would be a return to normal (Bozkurt & Sharma, 2020a , b ; Xiao, 2021 ); however, as time goes by, this hope has faded, and returning to normal appears to be far into the future (Schwab & Malleret, 2020 ). The pandemic is seen as a major milestone, in the sense that a macro reset in economic, social, geopolitical, environmental, and technological fields will produce multi-faceted changes affecting almost all aspects of life (Schwab & Malleret, 2020 ). The cover of an issue of the international edition of Time Magazine reflected this idea of a great reset and presented the COVID-19 pandemic as an opportunity to transform the way we live and work (Time, 2020 ). It has been argued that the pandemic will generate the emergence of a new era, and that we will have to adapt to the changes it produces (Bozkurt & Sharma, 2020 ). For example, the industrial sector quickly embraced remote work despite its challenges, and it is possible that most industrial companies will not return to the on-site working model even after the pandemic ends (Hern, 2020 ). We can expect a high rate of similar responses in other fields, including education, where COVID-19 has already reshaped our educational systems, the way we deliver education, and pedagogical approaches.

Theme 2: Digital pedagogy (See path on Fig.  1 : distance learning  >  research  >  teacher  >  development  >  need  >  training  +  technology  +  virtual  >  digital  >  communication  >  support  >  process  >  teaching  >  online  >  learning  >  online learning  +  course  >  faculty  >  students  >  experience ; See nodes on Fig.  2 : online learning, distance learning, computer-based learning, elearning, online education, distance education, online teaching, multimedia-based learning, technology, blended learning, online, digital transformation, ICT, online classes, flexible learning, technology-enhanced learning, digitalization ). Owing to the rapid transition to online education as a result of COVID-19, digital pedagogy and teachers’ competencies in information and communication technology (ICT) integration have gained greater prominence with the unprecedented challenges teachers have faced to adapt to remote teaching and learning. The COVID-19 pandemic has unquestionably manifested the need to prepare teachers to teach online, as most of them have been forced to assume ERE roles with inadequate preparation. Studies involving the use of SNA indicate a correspondence between adapting to a digital pedagogy and the need to equip teachers with greater competency in technology and online teaching (e.g., Blume, 2020 ; König et al., 2020 ). König et al. ( 2020 ) conducted a survey-based study investigating how early career teachers have adapted to online teaching during COVID-19 school closures. Their study found that while all the teachers maintained communication with students and their parents, introduced new learning content, and provided feedback, they lacked the ability to respond to challenges requiring ICT integration, such as those related to providing quality online teaching and to conducting assessments. Likewise, Blume ( 2020 ) noted that most teachers need to acquire digital skills to implement digitally-mediated pedagogy and communication more effectively. Both study findings point to the need for building ICT-related teaching and learning competencies in initial teacher education and teacher professional development. The findings from the SNA conducted in the present study are in line with the aforementioned findings in terms of keyword analysis and overlapping themes and nodes.

Theme 3: Shifting educational landscape and emerging educational roles (See path on Fig.  1 : future > education > role > Covid19; See nodes on Fig.  2 : higher education, education, student, curriculum, university, teachers, learning, professional development, teacher education, knowledge, readiness ). The role of technology in education and human learning has been essential during the COVID-19 pandemic. Technology has become a prerequisite for learning and teaching during the pandemic and will likely continue to be so after it. In the rapid shift to an unprecedented mode of learning and teaching, stakeholders have had to assume different roles in the educational landscape of the new normal. For example, in a comprehensive study involving the participation of over 30 K higher education students from 62 countries conducted by Aristovnik et al. ( 2020 ), it was found that students with certain socio-demographic characteristics (male, lower living standard, from Africa or Asia) were significantly less satisfied with the changes to work/life balance created by the COVID-19 pandemic, and that female students who were facing financial problems were generally more affected by COVID-19 in their emotional life and personal circumstances. Despite the challenges posed by the pandemic, there is likely to be carry over in the post-pandemic era of some of the educational changes made during the COVID-19 times. For example, traditional lecture-based teacher-centered classes may be replaced by more student-centered online collaborative classes (Zhu & Liu, 2020 ). This may require the development and proliferation of open educational platforms that allow access to high-quality educational materials (Bozkurt et al., 2020 ) and the adoption of new roles to survive in the learning ecologies informed by digital learning pedagogies. In common with the present study, the aforementioned studies (e.g., Aristovnik et al., 2020 ; König et al., 2020 ) call for more deliberate actions to improve teacher education programs by offering training on various teaching approaches, such as blended, hybrid, flexible, and online learning, to better prepare educators for emerging roles in the post-pandemic era.

Theme 4: Emergency remote education (see path Fig.  1 : higher education  >  university  >  student  >  experience  >  remote; See nodes on Fig.  2 : Covid19, pandemic, Coronavirus, higher education, education, school closure, emergency remote teaching, emergency remote learning ). Educational institutions have undergone a rapid shift to ERE in the wake of COVID-19 (Bozkurt & Sharma, 2020a ; Bozkurt et al., 2020 ; Hodges et al., 2020 ). Although ERE is viewed as similar to distance education, they are essentially different. That is, ERE is a prompt response measure to an emergency situation or unusual circumstances, such as a global pandemic or a civil war, for a temporary period of time, whereas distance education is a planned and systematic approach to instructional design and development grounded in educational theory and practice (Bozkurt & Sharma, 2020b ). Due to the urgent nature of situations requiring ERE, it may fall short in embracing the solid pedagogical learning and teaching principles represented by distance education (Hodges et al., 2020 ). The early implementations of ERE primarily involved synchronous video-conferencing sessions that sought to imitate in-person classroom instruction. It is worth noting that educators may have heavily relied on synchronous communication to overcome certain challenges, such as the lack of available materials and planned activities for asynchronous communication. Lockdowns and school closures, which turned homes into compulsory learning environments, have posed major challenges for families and students, including scheduling, device sharing, and learner engagement in a socially distanced home learning environment (Bond, 2020 ). For example, Shim and Lee ( 2020 ) conducted a qualitative study exploring university students’ ERE experiences and reported that students complained about network instability, unilateral interactions, and reduced levels of concentration. The SNA findings clearly highlight that there has been a focus on ERE due to the school closures during the COVID-19 pandemic. It is key to adopt the best practices of ERE and to utilize them regularly in distance education (Bozkurt, 2022 ). Moreover, it is important to note that unless clear distinctions are drawn between these two different forms of distance education or virtual instruction, a series of unfortunate events in education during these COVID-19 times is very likely to take place and lead to fatal errors in instructional practices and to poor student learning outcomes.

Theme 5: Pedagogy of care (See path Fig.  1 : r ole  >  education  >  Covid19  >  care ; See nodes on Fig.  2 : Stress, anxiety, student wellbeing, coping, care, crisis management, depression ). The thematic concept map and network graphic show the psychological and emotional impact of the COVID-19 pandemic on various stakeholders, revealing that they have experienced anxiety, expressed the need for care, and sought coping strategies. A study by Baloran ( 2020 ), conducted in the southern part of the Philippines to examine college students’ knowledge, attitudes, anxiety, and personal coping strategies during the COVID-19 pandemic, found that the majority of the students experienced anxiety during the lockdown and worried about food security, financial resources, social contact, and large gatherings. It was reported that the students coped with this anxiety by following protective measures, chatting with family members and friends, and motivating themselves to have a positive attitude. In a similar study, Islam et al. ( 2020 ) conducted an investigation to determine whether Bangladeshi college students experienced anxiety and depression and the factors responsible for these emotional responses. Their cross-sectional survey-based study found that a large percentage of the participants had suffered from anxiety and depression during the pandemic. Academic and professional uncertainty, as well as financial insecurity, have been documented as factors contributing to the anxiety and depression among college students. Both studies point to the need for support mechanisms to be established by higher education institutions in order to ensure student wellbeing, provide them with care, and help them to cope with stress, anxiety, and depression. Talidong and Toquero ( 2020 ) reported that, in addition to students’ well-being and care, teachers’ perceptions and experiences of stress and anxiety during the quarantine period need to be taken into account. The authors found that teachers were worried about the safety of their loved ones and were susceptible to anxiety but tended to follow the preventive policies. A pedagogy of care has been presented as an approach that would effectively allow educators to plan more supportive teaching practices during the pandemic by fostering clear and prompt communication with students and their families and taking into consideration learner needs in lesson planning (e.g., Karakaya, 2021 ; Robinson et al., 2020 ). Here it is important to stress that a pedagogy of care is a multifaceted concept, one that involves the concepts of social equity, equality, and injustice.

Theme 6: Social equity, equality, and injustice (See path on Fig.  1 : Impact  >  outbreak  >  coronavirus  >  pandemic  >  social ; See nodes on Fig.  2 : Support, equity, social justice, digital divide, inequality, social support ). One of the more significant impacts of COVID-19 has been the deepening of the existing social injustices around the world (Oldekop et al., 2020 ; Williamson et al., 2020 ). Long-term school closures have deteriorated social bonds and adversely affected health issues, poverty, economy, food insecurity, and digital divide (Van Lancker & Parolin, 2020 ). Regarding the digital divide, there has been a major disparity in access to devices and data connectivity between high-income and low-income populations increasing the digital divide, social injustice, and inequality in the world (Bozkurt et al., 2020 ). In line with the SNA findings, the digital divide, manifesting itself most visibly in the inadequacy and insufficiency of digital devices and lack of high-speed Internet, can easily result in widespread inequalities. As such, the disparities between low and high socio-economic status families and school districts in terms of digital pedagogy inequality may deepen as teachers in affluent schools are more likely to offer a wide range of online learning activities and thereby secure better student engagement, participation, and interaction (Greenhow et al., 2020 ). These findings demonstrate that social inequities have been sharpened by the unfortunate disparities imposed by the COVID-19, thus requiring us to reimagine a future that mitigates such concerns.

Theme 7: Future of education (See word path on Fig.  1 : Future  >  education  >  Covid19  >  pandemic  >  changes and pandemic  >  coronavirus, outbreak, impact  >  world ; See nodes on Fig.  2 : Sustainability, resilience, uncertainty, sdg4). Most significantly, COVID-19 the pandemic has shown the entire world that teachers and schools are invaluable resources and execute critical roles in society. Beyond that, with the compulsory changes resulting from the pandemic, it is evident that teaching and learning environments are not exclusive to brick-and-mortar classrooms. Digital technologies, being at the center of teaching and learning during the pandemic period, have been viewed as a pivotal agent in leveraging how learning takes place beyond the classroom walls (Quilter-Pinner & Ambrose, 2020 ). COVID-19 has made some concerns more visible. For example, the well-being of students, teachers, and society at large has gained more importance in these times of crisis. Furthermore, the need for educational technology and digital devices has compounded and amplified social inequities (Pelletier et al., 2021 ; West & Allen, 2020 ). Despite its global challenges, the need for technology and digital devices has highlighted some advantages that are likely to shape the future of education, particularly those related to the benefits of educational technology. For example, online learning could provide a more flexible, informal, self-paced learning environment for students (Adedoyin & Soykan, 2020 ). However, it also bears the risk of minimizing social interaction, as working in shared office environments has shifted to working alone in home-office settings. In this respect, the transformation of online education must involve a particular emphasis on sustaining interactivity through technology (Dwivedi et al., 2020 ). In view of the findings of the aforementioned studies, our text-mining and SNA findings suggest that the COVID-19 impositions may strongly shape the future of education and how learning takes place.

In summary, these themes extracted from the text-mining and SNA point to a significant milestone in the history of humanity, a multi-faceted reset that will affect many fields of life, from education and economics to sociology and lifestyle. The resulting themes have revealed that our natural response to an emerging worldwide situation shifted the educational landscape. The early response of the educational system was emergency-based and emphasized the continuance of in-person instruction via synchronous learning technologies. The subsequent response foregrounded the significance of digitally mediated learning pedagogy, related teacher competencies, and professional development. As various stakeholders (e.g., students, teachers, parents) have experienced a heightened level of anxiety and stress, an emerging strand of research has highlighted the need for care-based and trauma-informed pedagogies as a response to the side effects of the pandemic. In addition, as the global pandemic has made systemic impairments, such as social injustice and inequity, more visible, an important line of research has emerged on how social justice can be ensured given the challenges caused by the pandemic. Lastly, a sizable amount of research indicates that although the COVID-19 pandemic has imposed unprecedented challenges to our personal, educational, and social lives, it has also taught us how to respond to future crises in a timely, technologically-ready, pedagogically appropriate, and inclusive manner.

SNA: Citation Trends in the References of the Sampled Publications

The trends identified through SNA in citation patterns indicate two lines of thematic clusters (see Fig.  3 -A network graph depicting the citing and being cited patterns in the research corpus. Node sizes were defined by their citation count and betweenness centrality.). These clusters align with the results of the analysis of the titles, abstracts, and keywords of the sampled publications and forge the earlier themes (Theme 4: Emergency remote education and Theme 5: Pedagogy of care).

Thematic Cluster 1: The first cluster centers on the abilities of educational response, emergency remote education affordances, and continuity of education (Bozkurt & Sharma, 2020a ; Crawford et al., 2020 ; Hodges et al., 2020 ) to mitigate the impact of COVID-19 on education, especially for more vulnerable and disadvantaged groups (UNESCO, 2020 ; Viner et al., 2020 ). The thematic cluster one agrees with the theme four emergency remote education . The first trend line (See red line in Fig.  3 ) shows that the education system is vulnerable to external threats. Considering that interruption of education is not exclusive to pandemics – for example, political crises have also caused disruptions (Rapp et al., 2016 ) – it is clear that coping mechanisms are needed to ensure the continuity of education under all conditions. In this case, we need to reimagine and recalibrate education to make it resilient, flexible, and adaptive, not only to ensure the continuity of education, but also to ensure social justice, equity, and equality. Given that online education has its own limitations (e.g., it is restricted to online tools and infrastructures), we need to identify alternative entry points for those who do not have digital devices or lack access to the internet.

Thematic Cluster 2: The second cluster centers on the psychological impact of COVID-19 on learners, who during these times suffered a sense of uncertainty (Bozkurt, & Sharma, 2021 ; Cao et al., 2020 ; Rose, 2020 ; Sahu, 2020 ) which suggest that learners are experiencing difficult times that can result in psychological and mental problems. The thematic cluster two agrees with theme five which is pedagogy of care . Therefore, it can be argued that learners' psychological and emotional states should be a top priority. Brooks et al. ( 2020 ) reported the potential of post-traumatic issues with long-lasting effects, on top of the trauma that has already been suffered during the COVID-19 pandemic. In other words, the effects of the COVID-19 crisis may prove to extend beyond their current state and add long-term challenges. Additionally, it has further been reported that the socio-economic effects of the pandemic (Nicola et al., 2020 ) may cause inequality and inequity in educational communities (Beaunoyer et al., 2020 ). The research also shows that learners’ achievement gaps are positively associated with psychological issues, while support and care are negatively associated with their traumatic states (Cao et al., 2020 ). In this context, the second thematic cluster reveals that researchers have seriously considered the psychological and emotional needs of learners in their publications. Care (Noddings, 1984 ) and that trauma-informed pedagogy (Imad, 2020 ) can be a guideline during and after the COVID-19 pandemic. It is quite clear that learners have experienced educational loss (e.g., drop-outs, achievement gaps, academic procrastination, etc.), as well as social and emotional impairments (e.g., fear, frustration, confusion, anxiety, sense of isolation, death of loved ones, etc.). Therefore, we need to critically approach the situation, focusing first on healing our social and emotional losses, and then, on the educational losses. As Bozkurt and Sharma ( 2020a ) put it:

“What we teach in these times can have secondary importance. We have to keep in mind that students will remember not the educational content delivered, but how they felt during these hard times. With an empathetic approach, the story will not center on how to successfully deliver educational content, but it will be on how learners narrate these times” (p. iv).

Conclusion and Suggestions

The results from this study indicate that quick adaptability and flexibility have been key to surviving the substantial challenges generated by COVID-19. However, extreme demands on flexibility have taken a toll on human well-being and have exacerbated systemic issues like inequity and inequality. Using data mining that involved network analysis and text mining as analytical tools, this research provides a panoramic picture of the COVID-19-related themes educational researchers have addressed in their work. A sample of 1150 references yielded seven themes, which served to provide a comprehensive meta-narrative about COVID-19 and its impact on education.

A portion of the sampled publications focused on what we refer to as the great reset , highlighting the challenges that the emergency lockdown brought to the world. A publication pattern centered around digital pedagogy posited distance and online learning as key components and identified the need for teacher training. Given the need for adaptability, a third theme revealed the demand for professional development in higher education and a future shift in educational roles. It can be recommended that future research investigate institutional policy changes and the adaptation to these changes in renewed educational roles. The ERE theme centered on the lack of preparation in instituting the forced changes brought about by the COVID-19 pandemic. The publications related to this theme revealed that the COVID-19 pandemic uncovered silent threads in educational environments, like depression, inequality, and injustice. A pedagogy of care has been developed with the aim of reducing anxiety and providing support through coping strategies. These research patterns indicate that the future of education demands sustainability and resilience in the face of uncertainty.

Results of the thematic analysis of citation patterns (Fig.  3 ) overlapped with two of the themes found in our thematic concept map (Fig.  1 ) and network graphic (Fig.  2 ). It was shown that researchers have emphasized the continuity of education and the psychological effects of the COVID-19 crisis on learners. Creating coping strategies to deal with global crises (e.g., pandemics, political upheavals, natural disasters) has been shown to be a priority for educational researchers. The pedagogy of resilience (Purdue University Innovative learning, n.d. ) provides governments, institutions, and instructors with an alternative tool to applying to their contexts in the face of hardship. Furthermore, prioritizing the psychological long-term effects of the crisis in learners could alleviate achievement gaps. We recommend that researchers support grieving learners through care (Noddings, 1984 ) and trauma-informed pedagogy (Imad, 2020 ). Our resilience and empathy will reflect our preparedness for impending crises. The thematic analysis of citation patterns (1: educational response, emergency remote education affordances, and continuity of education; 2: psychological impact of COVID-19) further indicates suggestions for future instructional/learning designers. Freire ( 1985 ) argues that to transform the world we need to humanize it. Supporting that argument, the need for human-centered pedagogical approaches (Robinson et al., 2020 ) by considering learning a multifaceted process (Hodges et al., 2021 ) for well-designed learning experiences (Moore et al., 2021 ) is a requirement and instructional/learning designers have an important responsibility not only to design courses but an entire learning ecosystem where diversity, sensitivity, and inclusivity are prioritized.

ERE is not a representative feature in the field of online education or distance education but rather, a forced reaction to extraordinary circumstances in education. The increasing confusion between the practice of ERE and online learning could have catastrophic consequences in learners' outcomes, teachers' instructional practices, and institutional policies. Researchers, educators, and policymakers must work cooperatively and be guided by sound work in the field of distance learning to design nourishing educational environments that serve students’ best interests.

In this study, text mining and social network analysis were demonstrated to be powerful tools for exploring and visualizing patterns in COVID-19-related educational research. However, a more in-depth examination is still needed to synthesize effective strategies that can be used to support us in future crises. Systematic reviews that use classical manual coding techniques may take more time but increase our understanding of a phenomenon and help us to develop specific action plans. Future systematic reviews can use the seven themes identified in this study to analyze primary studies and find strategies that counteract the survival of the fittest mindset to ensure that no student is left behind.

Data Availability

The dataset is available from the authors upon request.

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Acknowledgements

This paper is dedicated to all educators and instructional/learning designers who ensured the continuity of education during the tough times of the COVID-19 pandemic.

This article is produced as a part of the 2020 AECT Mentoring Program.

This paper is supported by Anadolu University, Scientific Research Commission with grant no: 2106E084.

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Aras Bozkurt

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Bozkurt, A., Karakaya, K., Turk, M. et al. The Impact of COVID-19 on Education: A Meta-Narrative Review. TechTrends 66 , 883–896 (2022). https://doi.org/10.1007/s11528-022-00759-0

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How is COVID-19 affecting student learning?

Subscribe to the brown center on education policy newsletter, initial findings from fall 2020, 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 beth tarasawa , bt beth tarasawa executive vice president of research - nwea angela johnson , aj angela johnson research scientist - nwea erik ruzek , and er erik ruzek research assistant professor, curry school of education - university of virginia karyn lewis karyn lewis director, center for school and student progress - nwea.

December 3, 2020

The COVID-19 pandemic has introduced uncertainty into major aspects of national and global society, including for schools. For example, there is uncertainty about how school closures last spring impacted student achievement, as well as how the rapid conversion of most instruction to an online platform this academic year will continue to affect achievement. Without data on how the virus impacts student learning, making informed decisions about whether and when to return to in-person instruction remains difficult. Even now, education leaders must grapple with seemingly impossible choices that balance health risks associated with in-person learning against the educational needs of children, which may be better served when kids are in their physical schools.

Amidst all this uncertainty, there is growing consensus that school closures in spring 2020 likely had negative effects on student learning. For example, in an earlier post for this blog , we presented our research forecasting the possible impact of school closures on achievement. Based on historical learning trends and prior research on how out-of-school-time affects learning, we estimated that students would potentially begin fall 2020 with roughly 70% of the learning gains in reading relative to a typical school year. In mathematics, students were predicted to show even smaller learning gains from the previous year, returning with less than 50% of typical gains. While these and other similar forecasts presented a grim portrait of the challenges facing students and educators this fall, they were nonetheless projections. The question remained: What would learning trends in actual data from the 2020-21 school year really look like?

With fall 2020 data now in hand , we can move beyond forecasting and begin to describe what did happen. While the closures last spring left most schools without assessment data from that time, thousands of schools began testing this fall, making it possible to compare learning gains in a typical, pre-COVID-19 year to those same gains during the COVID-19 pandemic. Using data from nearly 4.4 million students in grades 3-8 who took MAP ® Growth™ reading and math assessments in fall 2020, we examined two primary research questions:

• How did students perform in fall 2020 relative to a typical school year (specifically, fall 2019)?
• Have students made learning gains since schools physically closed in March 2020?

To answer these questions, we compared students’ academic achievement and growth during the COVID-19 pandemic to the achievement and growth patterns observed in 2019. We report student achievement as a percentile rank, which is a normative measure of a student’s achievement in a given grade/subject relative to the MAP Growth national norms (reflecting pre-COVID-19 achievement levels).

To make sure the students who took the tests before and after COVID-19 school closures were demographically similar, all analyses were limited to a sample of 8,000 schools that tested students in both fall 2019 and fall 2020. Compared to all public schools in the nation, schools in the sample had slightly larger total enrollment, a lower percentage of low-income students, and a higher percentage of white students. Since our sample includes both in-person and remote testers in fall 2020, we conducted an initial comparability study of remote and in-person testing in fall 2020. We found consistent psychometric characteristics and trends in test scores for remote and in-person tests for students in grades 3-8, but caution that remote testing conditions may be qualitatively different for K-2 students. For more details on the sample and methodology, please see the technical report accompanying this study.

In some cases, our results tell a more optimistic story than what we feared. In others, the results are as deeply concerning as we expected based on our projections.

Question 1: How did students perform in fall 2020 relative to a typical school year?

When comparing students’ median percentile rank for fall 2020 to those for fall 2019, there is good news to share: Students in grades 3-8 performed similarly in reading to same-grade students in fall 2019. While the reason for the stability of these achievement results cannot be easily pinned down, possible explanations are that students read more on their own, and parents are better equipped to support learning in reading compared to other subjects that require more formal instruction.

The news in math, however, is more worrying. The figure below shows the median percentile rank in math by grade level in fall 2019 and fall 2020. As the figure indicates, the math achievement of students in 2020 was about 5 to 10 percentile points lower compared to same-grade students the prior year.

Figure 1: MAP Growth Percentiles in Math by Grade Level in Fall 2019 and Fall 2020

Source: Author calculations with MAP Growth data. Notes: Each bar represents the median percentile rank in a given grade/term.

Question 2: Have students made learning gains since schools physically closed, and how do these gains compare to gains in a more typical year?

To answer this question, we examined learning gains/losses between winter 2020 (January through early March) and fall 2020 relative to those same gains in a pre-COVID-19 period (between winter 2019 and fall 2019). We did not examine spring-to-fall changes because so few students tested in spring 2020 (after the pandemic began). In almost all grades, the majority of students made some learning gains in both reading and math since the COVID-19 pandemic started, though gains were smaller in math in 2020 relative to the gains students in the same grades made in the winter 2019-fall 2019 period.

Figure 2 shows the distribution of change in reading scores by grade for the winter 2020 to fall 2020 period (light blue) as compared to same-grade students in the pre-pandemic span of winter 2019 to fall 2019 (dark blue). The 2019 and 2020 distributions largely overlapped, suggesting similar amounts of within-student change from one grade to the next.

Figure 2: Distribution of Within-student Change from Winter 2019-Fall 2019 vs Winter 2020-Fall 2020 in Reading

Source: Author calculations with MAP Growth data. Notes: The dashed line represents zero growth (e.g., winter and fall test scores were equivalent). A positive value indicates that a student scored higher in the fall than their prior winter score; a negative value indicates a student scored lower in the fall than their prior winter score.

Meanwhile, Figure 3 shows the distribution of change for students in different grade levels for the winter 2020 to fall 2020 period in math. In contrast to reading, these results show a downward shift: A smaller proportion of students demonstrated positive math growth in the 2020 period than in the 2019 period for all grades. For example, 79% of students switching from 3 rd to 4 th grade made academic gains between winter 2019 and fall 2019, relative to 57% of students in the same grade range in 2020.

Figure 3: Distribution of Within-student Change from Winter 2019-Fall 2019 vs. Winter 2020-Fall 2020 in Math

It was widely speculated that the COVID-19 pandemic would lead to very unequal opportunities for learning depending on whether students had access to technology and parental support during the school closures, which would result in greater heterogeneity in terms of learning gains/losses in 2020. Notably, however, we do not see evidence that within-student change is more spread out this year relative to the pre-pandemic 2019 distribution.

The long-term effects of COVID-19 are still unknown

In some ways, our findings show an optimistic picture: In reading, on average, the achievement percentiles of students in fall 2020 were similar to those of same-grade students in fall 2019, and in almost all grades, most students made some learning gains since the COVID-19 pandemic started. In math, however, the results tell a less rosy story: Student achievement was lower than the pre-COVID-19 performance by same-grade students in fall 2019, and students showed lower growth in math across grades 3 to 8 relative to peers in the previous, more typical year. Schools will need clear local data to understand if these national trends are reflective of their students. Additional resources and supports should be deployed in math specifically to get students back on track.

In this study, we limited our analyses to a consistent set of schools between fall 2019 and fall 2020. However, approximately one in four students who tested within these schools in fall 2019 are no longer in our sample in fall 2020. This is a sizeable increase from the 15% attrition from fall 2018 to fall 2019. One possible explanation is that some students lacked reliable technology. A second is that they disengaged from school due to economic, health, or other factors. More coordinated efforts are required to establish communication with students who are not attending school or disengaging from instruction to get them back on track, especially our most vulnerable students.

Finally, we are only scratching the surface in quantifying the short-term and long-term academic and non-academic impacts of COVID-19. While more students are back in schools now and educators have more experience with remote instruction than when the pandemic forced schools to close in spring 2020, the collective shock we are experiencing is ongoing. We will continue to examine students’ academic progress throughout the 2020-21 school year to understand how recovery and growth unfold amid an ongoing pandemic.

Thankfully, we know much more about the impact the pandemic has had on student learning than we did even a few months ago. However, that knowledge makes clear that there is work to be done to help many students get back on track in math, and that the long-term ramifications of COVID-19 for student learning—especially among underserved communities—remain unknown.

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Greater Good Science Center • Magazine • In Action • In Education

11 Questions to Ask About COVID-19 Research

Debates have raged on social media, around dinner tables, on TV, and in Congress about the science of COVID-19. Is it really worse than the flu? How necessary are lockdowns? Do masks work to prevent infection? What kinds of masks work best? Is the new vaccine safe?

You might see friends, relatives, and coworkers offer competing answers, often brandishing studies or citing individual doctors and scientists to support their positions. With so much disagreement—and with such high stakes—how can we use science to make the best decisions?

Here at Greater Good , we cover research into social and emotional well-being, and we try to help people apply findings to their personal and professional lives. We are well aware that our business is a tricky one.

Summarizing scientific studies and distilling the key insights that people can apply to their lives isn’t just difficult for the obvious reasons, like understanding and then explaining formal science terms or rigorous empirical and analytic methods to non-specialists. It’s also the case that context gets lost when we translate findings into stories, tips, and tools, especially when we push it all through the nuance-squashing machine of the Internet. Many people rarely read past the headlines, which intrinsically aim to be relatable and provoke interest in as many people as possible. Because our articles can never be as comprehensive as the original studies, they almost always omit some crucial caveats, such as limitations acknowledged by the researchers. To get those, you need access to the studies themselves.

And it’s very common for findings and scientists to seem to contradict each other. For example, there were many contradictory findings and recommendations about the use of masks, especially at the beginning of the pandemic—though as we’ll discuss, it’s important to understand that a scientific consensus did emerge.

Given the complexities and ambiguities of the scientific endeavor, is it possible for a non-scientist to strike a balance between wholesale dismissal and uncritical belief? Are there red flags to look for when you read about a study on a site like Greater Good or hear about one on a Fox News program? If you do read an original source study, how should you, as a non-scientist, gauge its credibility?

Here are 11 questions you might ask when you read about the latest scientific findings about the pandemic, based on our own work here at Greater Good.

1. Did the study appear in a peer-reviewed journal?

In peer review, submitted articles are sent to other experts for detailed critical input that often must be addressed in a revision prior to being accepted and published. This remains one of the best ways we have for ascertaining the rigor of the study and rationale for its conclusions. Many scientists describe peer review as a truly humbling crucible. If a study didn’t go through this process, for whatever reason, it should be taken with a much bigger grain of salt. 

“When thinking about the coronavirus studies, it is important to note that things were happening so fast that in the beginning people were releasing non-peer reviewed, observational studies,” says Dr. Leif Hass, a family medicine doctor and hospitalist at Sutter Health’s Alta Bates Summit Medical Center in Oakland, California. “This is what we typically do as hypothesis-generating but given the crisis, we started acting on them.”

In a confusing, time-pressed, fluid situation like the one COVID-19 presented, people without medical training have often been forced to simply defer to expertise in making individual and collective decisions, turning to culturally vetted institutions like the Centers for Disease Control (CDC). Is that wise? Read on.

2. Who conducted the study, and where did it appear?

“I try to listen to the opinion of people who are deep in the field being addressed and assess their response to the study at hand,” says Hass. “With the MRNA coronavirus vaccines, I heard Paul Offit from UPenn at a UCSF Grand Rounds talk about it. He literally wrote the book on vaccines. He reviewed what we know and gave the vaccine a big thumbs up. I was sold.”

From a scientific perspective, individual expertise and accomplishment matters—but so does institutional affiliation.

Why? Because institutions provide a framework for individual accountability as well as safety guidelines. At UC Berkeley, for example , research involving human subjects during COVID-19 must submit a Human Subjects Proposal Supplement Form , and follow a standard protocol and rigorous guidelines . Is this process perfect? No. It’s run by humans and humans are imperfect. However, the conclusions are far more reliable than opinions offered by someone’s favorite YouTuber .

Recommendations coming from institutions like the CDC should not be accepted uncritically. At the same time, however, all of us—including individuals sporting a “Ph.D.” or “M.D.” after their names—must be humble in the face of them. The CDC represents a formidable concentration of scientific talent and knowledge that dwarfs the perspective of any one individual. In a crisis like COVID-19, we need to defer to that expertise, at least conditionally.

“If we look at social media, things could look frightening,” says Hass. When hundreds of millions of people are vaccinated, millions of them will be afflicted anyway, in the course of life, by conditions like strokes, anaphylaxis, and Bell’s palsy. “We have to have faith that people collecting the data will let us know if we are seeing those things above the baseline rate.”

3. Who was studied, and where?

Animal experiments tell scientists a lot, but their applicability to our daily human lives will be limited. Similarly, if researchers only studied men, the conclusions might not be relevant to women, and vice versa.

Many psychology studies rely on WEIRD (Western, educated, industrialized, rich and democratic) participants, mainly college students, which creates an in-built bias in the discipline’s conclusions. Historically, biomedical studies also bias toward gathering measures from white male study participants, which again, limits generalizability of findings. Does that mean you should dismiss Western science? Of course not. It’s just the equivalent of a “Caution,” “Yield,” or “Roadwork Ahead” sign on the road to understanding.

This applies to the coronavirus vaccines now being distributed and administered around the world. The vaccines will have side effects; all medicines do. Those side effects will be worse for some people than others, depending on their genetic inheritance, medical status, age, upbringing, current living conditions, and other factors.

For Hass, it amounts to this question: Will those side effects be worse, on balance, than COVID-19, for most people?

“When I hear that four in 100,000 [of people in the vaccine trials] had Bell’s palsy, I know that it would have been a heck of a lot worse if 100,000 people had COVID. Three hundred people would have died and many others been stuck with chronic health problems.”

4. How big was the sample?

In general, the more participants in a study, the more valid its results. That said, a large sample is sometimes impossible or even undesirable for certain kinds of studies. During COVID-19, limited time has constrained the sample sizes.

However, that acknowledged, it’s still the case that some studies have been much larger than others—and the sample sizes of the vaccine trials can still provide us with enough information to make informed decisions. Doctors and nurses on the front lines of COVID-19—who are now the very first people being injected with the vaccine—think in terms of “biological plausibility,” as Hass says.

Did the admittedly rushed FDA approval of the Pfizer-BioNTech vaccine make sense, given what we already know? Tens of thousands of doctors who have been grappling with COVID-19 are voting with their arms, in effect volunteering to be a sample for their patients. If they didn’t think the vaccine was safe, you can bet they’d resist it. When the vaccine becomes available to ordinary people, we’ll know a lot more about its effects than we do today, thanks to health care providers paving the way.

5. Did the researchers control for key differences, and do those differences apply to you?

Diversity or gender balance aren’t necessarily virtues in experimental research, though ideally a study sample is as representative of the overall population as possible. However, many studies use intentionally homogenous groups, because this allows the researchers to limit the number of different factors that might affect the result.

While good researchers try to compare apples to apples, and control for as many differences as possible in their analyses, running a study always involves trade-offs between what can be accomplished as a function of study design, and how generalizable the findings can be.

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You also need to ask if the specific population studied even applies to you. For example, when one study found that cloth masks didn’t work in “high-risk situations,” it was sometimes used as evidence against mask mandates.

However, a look beyond the headlines revealed that the study was of health care workers treating COVID-19 patients, which is a vastly more dangerous situation than, say, going to the grocery store. Doctors who must intubate patients can end up being splattered with saliva. In that circumstance, one cloth mask won’t cut it. They also need an N95, a face shield, two layers of gloves, and two layers of gown. For the rest of us in ordinary life, masks do greatly reduce community spread, if as many people as possible are wearing them.

6. Was there a control group?

One of the first things to look for in methodology is whether the population tested was randomly selected, whether there was a control group, and whether people were randomly assigned to either group without knowing which one they were in. This is especially important if a study aims to suggest that a certain experience or treatment might actually cause a specific outcome, rather than just reporting a correlation between two variables (see next point).

For example, were some people randomly assigned a specific meditation practice while others engaged in a comparable activity or exercise? If the sample is large enough, randomized trials can produce solid conclusions. But, sometimes, a study will not have a control group because it’s ethically impossible. We can’t, for example, let sick people go untreated just to see what would happen. Biomedical research often makes use of standard “treatment as usual” or placebos in control groups. They also follow careful ethical guidelines to protect patients from both maltreatment and being deprived necessary treatment. When you’re reading about studies of masks, social distancing, and treatments during the COVID-19, you can partially gauge the reliability and validity of the study by first checking if it had a control group. If it didn’t, the findings should be taken as preliminary.

7. Did the researchers establish causality, correlation, dependence, or some other kind of relationship?

We often hear “Correlation is not causation” shouted as a kind of battle cry, to try to discredit a study. But correlation—the degree to which two or more measurements seem connected—is important, and can be a step toward eventually finding causation—that is, establishing a change in one variable directly triggers a change in another. Until then, however, there is no way to ascertain the direction of a correlational relationship (does A change B, or does B change A), or to eliminate the possibility that a third, unmeasured factor is behind the pattern of both variables without further analysis.

In the end, the important thing is to accurately identify the relationship. This has been crucial in understanding steps to counter the spread of COVID-19 like shelter-in-place orders. Just showing that greater compliance with shelter-in-place mandates was associated with lower hospitalization rates is not as conclusive as showing that one community that enacted shelter-in-place mandates had lower hospitalization rates than a different community of similar size and population density that elected not to do so.

We are not the first people to face an infection without understanding the relationships between factors that would lead to more of it. During the bubonic plague, cities would order rodents killed to control infection. They were onto something: Fleas that lived on rodents were indeed responsible. But then human cases would skyrocket.

Why? Because the fleas would migrate off the rodent corpses onto humans, which would worsen infection. Rodent control only reduces bubonic plague if it’s done proactively; once the outbreak starts, killing rats can actually make it worse. Similarly, we can’t jump to conclusions during the COVID-19 pandemic when we see correlations.

8. Are journalists and politicians, or even scientists, overstating the result?

Language that suggests a fact is “proven” by one study or which promotes one solution for all people is most likely overstating the case. Sweeping generalizations of any kind often indicate a lack of humility that should be a red flag to readers. A study may very well “suggest” a certain conclusion but it rarely, if ever, “proves” it.

This is why we use a lot of cautious, hedging language in Greater Good , like “might” or “implies.” This applies to COVID-19 as well. In fact, this understanding could save your life.

When President Trump touted the advantages of hydroxychloroquine as a way to prevent and treat COVID-19, he was dramatically overstating the results of one observational study. Later studies with control groups showed that it did not work—and, in fact, it didn’t work as a preventative for President Trump and others in the White House who contracted COVID-19. Most survived that outbreak, but hydroxychloroquine was not one of the treatments that saved their lives. This example demonstrates how misleading and even harmful overstated results can be, in a global pandemic.

9. Is there any conflict of interest suggested by the funding or the researchers’ affiliations?

A 2015 study found that you could drink lots of sugary beverages without fear of getting fat, as long as you exercised. The funder? Coca Cola, which eagerly promoted the results. This doesn’t mean the results are wrong. But it does suggest you should seek a second opinion : Has anyone else studied the effects of sugary drinks on obesity? What did they find?

It’s possible to take this insight too far. Conspiracy theorists have suggested that “Big Pharma” invented COVID-19 for the purpose of selling vaccines. Thus, we should not trust their own trials showing that the vaccine is safe and effective.

But, in addition to the fact that there is no compelling investigative evidence that pharmaceutical companies created the virus, we need to bear in mind that their trials didn’t unfold in a vacuum. Clinical trials were rigorously monitored and independently reviewed by third-party entities like the World Health Organization and government organizations around the world, like the FDA in the United States.

Does that completely eliminate any risk? Absolutely not. It does mean, however, that conflicts of interest are being very closely monitored by many, many expert eyes. This greatly reduces the probability and potential corruptive influence of conflicts of interest.

10. Do the authors reference preceding findings and original sources?

The scientific method is based on iterative progress, and grounded in coordinating discoveries over time. Researchers study what others have done and use prior findings to guide their own study approaches; every study builds on generations of precedent, and every scientist expects their own discoveries to be usurped by more sophisticated future work. In the study you are reading, do the researchers adequately describe and acknowledge earlier findings, or other key contributions from other fields or disciplines that inform aspects of the research, or the way that they interpret their results?

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This was crucial for the debates that have raged around mask mandates and social distancing. We already knew quite a bit about the efficacy of both in preventing infections, informed by centuries of practical experience and research.

When COVID-19 hit American shores, researchers and doctors did not question the necessity of masks in clinical settings. Here’s what we didn’t know: What kinds of masks would work best for the general public, who should wear them, when should we wear them, were there enough masks to go around, and could we get enough people to adopt best mask practices to make a difference in the specific context of COVID-19 ?

Over time, after a period of confusion and contradictory evidence, those questions have been answered . The very few studies that have suggested masks don’t work in stopping COVID-19 have almost all failed to account for other work on preventing the disease, and had results that simply didn’t hold up. Some were even retracted .

So, when someone shares a coronavirus study with you, it’s important to check the date. The implications of studies published early in the pandemic might be more limited and less conclusive than those published later, because the later studies could lean on and learn from previously published work. Which leads us to the next question you should ask in hearing about coronavirus research…

11. Do researchers, journalists, and politicians acknowledge limitations and entertain alternative explanations?

Is the study focused on only one side of the story or one interpretation of the data? Has it failed to consider or refute alternative explanations? Do they demonstrate awareness of which questions are answered and which aren’t by their methods? Do the journalists and politicians communicating the study know and understand these limitations?

When the Annals of Internal Medicine published a Danish study last month on the efficacy of cloth masks, some suggested that it showed masks “make no difference” against COVID-19.

The study was a good one by the standards spelled out in this article. The researchers and the journal were both credible, the study was randomized and controlled, and the sample size (4,862 people) was fairly large. Even better, the scientists went out of their way to acknowledge the limits of their work: “Inconclusive results, missing data, variable adherence, patient-reported findings on home tests, no blinding, and no assessment of whether masks could decrease disease transmission from mask wearers to others.”

Unfortunately, their scientific integrity was not reflected in the ways the study was used by some journalists, politicians, and people on social media. The study did not show that masks were useless. What it did show—and what it was designed to find out—was how much protection masks offered to the wearer under the conditions at the time in Denmark. In fact, the amount of protection for the wearer was not large, but that’s not the whole picture: We don’t wear masks mainly to protect ourselves, but to protect others from infection. Public-health recommendations have stressed that everyone needs to wear a mask to slow the spread of infection.

“We get vaccinated for the greater good, not just to protect ourselves ”

As the authors write in the paper, we need to look to other research to understand the context for their narrow results. In an editorial accompanying the paper in Annals of Internal Medicine , the editors argue that the results, together with existing data in support of masks, “should motivate widespread mask wearing to protect our communities and thereby ourselves.”

Something similar can be said of the new vaccine. “We get vaccinated for the greater good, not just to protect ourselves,” says Hass. “Being vaccinated prevents other people from getting sick. We get vaccinated for the more vulnerable in our community in addition for ourselves.”

Ultimately, the approach we should take to all new studies is a curious but skeptical one. We should take it all seriously and we should take it all with a grain of salt. You can judge a study against your experience, but you need to remember that your experience creates bias. You should try to cultivate humility, doubt, and patience. You might not always succeed; when you fail, try to admit fault and forgive yourself.

Above all, we need to try to remember that science is a process, and that conclusions always raise more questions for us to answer. That doesn’t mean we never have answers; we do. As the pandemic rages and the scientific process unfolds, we as individuals need to make the best decisions we can, with the information we have.

This article was revised and updated from a piece published by Greater Good in 2015, “ 10 Questions to Ask About Scientific Studies .”

About the Authors

Jeremy Adam Smith

Uc berkeley.

Jeremy Adam Smith edits the GGSC’s online magazine, Greater Good . He is also the author or coeditor of five books, including The Daddy Shift , Are We Born Racist? , and (most recently) The Gratitude Project: How the Science of Thankfulness Can Rewire Our Brains for Resilience, Optimism, and the Greater Good . Before joining the GGSC, Jeremy was a John S. Knight Journalism Fellow at Stanford University.

Emiliana R. Simon-Thomas

Emiliana R. Simon-Thomas, Ph.D. , is the science director of the Greater Good Science Center, where she directs the GGSC’s research fellowship program and serves as a co-instructor of its Science of Happiness and Science of Happiness at Work online courses.

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COVID-19 and its impact on education, social life and mental health of students: A survey

The outbreak of COVID-19 affected the lives of all sections of society as people were asked to self-quarantine in their homes to prevent the spread of the virus. The lockdown had serious implications on mental health, resulting in psychological problems including frustration, stress, and depression. In order to explore the impacts of this pandemic on the lives of students, we conducted a survey of a total of 1182 individuals of different age groups from various educational institutes in Delhi - National Capital Region (NCR), India. The article identified the following as the impact of COVID-19 on the students of different age groups: time spent on online classes and self-study, medium used for learning, sleeping habits, daily fitness routine, and the subsequent effects on weight, social life, and mental health. Moreover, our research found that in order to deal with stress and anxiety, participants adopted different coping mechanisms and also sought help from their near ones. Further, the research examined the student’s engagement on social media platforms among different age categories. This study suggests that public authorities should take all the necessary measures to enhance the learning experience by mitigating the negative impacts caused due to the COVID-19 outbreak.

1. Introduction

The emergence of Corona Virus disease (COVID-19) has led the world to an unprecedented public health crisis. Emergency protocols were implemented in India to control the spread of the virus which resulted in restrictions on all non-essential public movements ( Saha et al. 2020 ). With the closure of educational institutions, the need for a rapid transition from physical learning to the digital sphere of learning emerged ( Kapasia et al. 2020 ). Online learning has been observed as a possible alternative to conventional learning ( Adnan and Anwar 2020 ). However, according to a meta-analysis on e-learning ( Cook 2009 ), it is reported that online learning is better than nothing and similar to conventional learning. To improve the e-learning experience, the education institutions are required to comply with the guidelines and recommendations by government agencies, while keeping students encouraged to continue learning remotely in this tough environment ( Aucejo et al. 2020 ). Bao (2020 ) addresses five high-impact guidelines for the efficient conduct of online education.

This rapid evolution at such a large scale has influenced the students of all age groups ( Hasan and Bao 2020 ). It is expected that the continued spread of the disease, travel restrictions and the closure of educational institutions across the country would have a significant effect on the education, social life, and mental health of students ( Odriozola-gonzález et al. 2020 ). The students from the less privileged backgrounds have experienced larger negative impacts due to the Covid-19 outbreak ( Aucejo et al. 2020 ). Reduction in family income, limited access to digital resources, and the high cost of internet connectivity have disrupted the academic life of the students. Moreover, 1.5 billion students across the world are now deprived of basic education ( Lee 2020 ) leading to a serious psychological impact on their health. Moreover, changes in daily routine including lack of outdoor activity, disturbed sleeping patterns, social distancing have affected the mental well-being of the students. ( Cao et al. 2020 ) uses 7-item Generalized Anxiety Disorder Scale (GAD-7) as a diagnostic tool for the assessment of anxiety disorders, panic disorders, and social phobia. Further, ( Ye et al. 2020 ) analyses mediating roles of resilience, coping, and social support to deal with psychological symptoms.

In this paper, we investigated and analyzed the potential consequences of the COVID-19 pandemic on the life of students. Our research shows that there is a wide gap between the government's policy aspirations and the implementation of these online education policies at the grassroots level. Moreover, our study attempts to assess the mental situation of students of different age groups using different parameters including sleeping habits, daily fitness routine, and social support. Further, we analyse different coping mechanisms used by students to deal with the current situation.

2. Objective and methods

A 19-set questionnaire was developed, which included a variety of multiple-choice questions, Likert scale and for a few questions, the respondents were allowed to enter free texts. The survey was administered using the Google Forms platform, which requires subjects to be logged in to an e-mail account to participate in the survey, it restricted multiple entries from an individual account. The distribution of the questionnaire was conducted through the outreach of social media platforms, e-mail, and standard messaging services. Clear instructions with the google form were provided to ensure the respondent must be a student.

2.1. Study design

A web-based survey was conducted to students through the medium of Google online platforms from July 13 to July 17, 2020. The online survey questionnaire contained four subgroups:

• (a) Participants were asked to describe their general demographics, such as age, the region of residence.
• (b) Information about the daily online learning routine following the transition from offline learning in educational institutions in India: average time spent for online study (hours) /day; medium for online study; average time spent for self-study (hours)/day.
• (c) Assessment of the experience of online learning to evaluate the levels of satisfaction among students.
• (d) Assessment of health due to the change in lifestyle: average time spent on sleep (hours)/day; change in weight; average time spent on fitness (hours)/day; the number of meals/days; also, we considered further questions about the medium of stress busters during the pandemic, cohesion with family members, etc.

The aim of this survey study is to investigate the impact of the COVID-19 pandemic on the education, health, and lifestyle of students from different age-groups.

2.2. Statistical analysis

In this study, we conducted a cross-sectional survey with a sample size of 1182 students from different educational institutions. A summary of demographic details in the form of numbers and percentages is provided. Mean at 95% Confidence Interval limit was calculated for learning hours for online classes and self-study, duration of sleep, time spent on fitness and sleep. Kruskal Wallis test, a non-parametric test was used to assess the significant difference in the time spent on the aforementioned activities among different age distributions. Fisher’s exact test was performed to assess the differences between respondent’s health with the variables of interest. In order to analyse the association between age categories and different variables such as change in weight, health issues faced, stress busters, etc, the Pearson Chi Square test was used. JMP Version 15.2.1 from SAS was used for analysis. A statistically significant value of P < 0.05 was considered.

2.3. Ethical consideration

The following survey was done in a properly informed set up and consent from the individuals was taken for the participation. No individual was forced against their will and no identifying information was collected.

3.1. Participants characteristics

A total of 1182 subjects from different educational institutions including schools, colleges, and universities in the Delhi-National Capital Region (NCR) participated in the online questionnaire. The demographic detail of the participants is shown in Table 1 . The mean age is 20.16 years (95% confidence interval (CI), 19.8–20.4) (range, 7–59). The age of the participants was normally distributed (‘7–17’ year old, 303; ‘18–22’ year old, 694; ‘23–59’ year old, 185). 728 (61.62%) of the respondents lived in Delhi-NCR and the rest were living outside of Delhi-NCR during the period of the pandemic.

Demographic data of the respondents to the online survey questionnaire.

3.2. Assessment of online learning

According to Table 2 , the Kruskal Wallis test was used to assess the difference in the time spent by different age categories for daily routine activities. The average time spent on online classes for students was 3.20 h/day (95% confidence interval (CI), 3.08–3.32). However, the average time spent on online classes was significantly higher for students with age group ‘7–17’ years (3.69 h/day), and lower for students with age groups, ‘18–22’ years (2.98 h/day) and ‘23–59’ years (2.66 h/day) (P < 0.0001*). Further, respondents were asked about the time they allot per day for self-study, however, there was no significant difference among different age group categories (P = 0.106). Overall, 2.91 h/day (95% CI, 2.78–3.03) was the average time spent on self-study. According to the assessment of satisfaction level among students (see Fig. 1 .a), 38.3% of students had negative response towards online classes (2.6% poor and 35.7% very poor), 33.4% considered it average while 28.4% (19.9% good and 8.5% excellent) gave a positive review. Surprisingly, the in-depth analysis showed the satisfaction levels varied significantly with different age groups. There were 51.6% (48.6% very poor and 3% poor) negative online class reviews from subjects in the ‘18–22’ age group, compared to 31.5% (29.1% very poor and 2.4% poor) negative reviews from subjects in the ‘7–17’ age group who spent more time on online classes.

Table showing how different variables (time spent on online class, self-study, fitness, sleep, and social media) changes with different age distributions.

Kruskal Wallis test was used to produce a P-value that analyzes significant difference between different age distributions. *Statistically significant (P < 0.05).

Visualizations demonstrate a) Likert analysis of Online classes for the sample and for different age categories b) Medium for the online classes b) Learning medium used by different age categories.

The respondents were further asked about the medium of their online learning (see Fig. 1 .b), 57.3% in the age group ‘7–17’ used smartphones while the majority of students from age group ‘18–22’ (56.4%) and age group ‘23–59’ (57.8%) used laptop/desktop for study. However, only a small portion of the total students (3.1%, n = 37) used tablet. With regard to the time spent in online classes, there was a statistically significant difference between the various mediums used (P = 0.0002). As shown in Table 3 , 4.29 h/day (95% CI, 3.63–4.96) was the average time spent on online classes using tablets, 3.43 h/day (95% CI, 3.25–3.61) when using laptop/desktop, and 3.06 h/day (95% CI, 2.90–3.23) when using smartphones.

Time spent on online classes using different learning medium.

3.3. Assessment of health in educational institutions

Among the respondents from different age groups (see Fig. 2 ), 13.6% (n = 160) faced health-related issues during the period of nationwide travel restrictions. Further respondents were asked about the change in body weight within this period, 37.1% reported an increase in weight, 17.7% reported a decrease in weight, and 45.3% reported no change in weight. When asked whether they are satisfied with their utilization of time, the majority of respondents (51.4%, n = 608) answered in ‘NO’, and the rest (n = 575) answered with ‘YES’. Also, 70.3% of the respondents stated that they were socially connected with their family members.

Visualizations demonstrate a) Pie Chart for Likert questions: whether the respondent faced health issues; whether the respondent utilized the time efficiently; whether the respondent is socially well connected. b) Stacked bar chart to analyze the change in weight during the period of lockdown.

According to Table 4 , fisher’s exact test indicated that the respondents who were not socially well connected and believed that they did not utilize their time in lockdown, had a significant impact on their state of health. Also, in Table 5 , the Pearson Chi Square test for Likert analysis on ‘time utilized’ (P < 0.0001*), ‘health issue faced’ (P < 0.0001*), and ‘socially well connected’ (P = 0.0002*) rejected the null hypothesis that there is no association between these variables with the different distribution of age groups. To maintain a state of health and well-being, it is necessary to perform a certain amount of exercise daily. The findings of Table 2 showed that the time spent on fitness was statistically different for different age groups (P = 0.039*, Kruskal Wallis test). And, the average time spent on sleep was 7.87 h/day (95% Confidence Interval, 7.77–7.96). The differences between the age groups in terms of duration of sleep were statistically significant.

Fisher’s exact test to analyse the effect of multiple factors on health.

*Statistically significant (P < 0.05).

Pearson Chi Square test for the association between different variables and age distribution.

Further, respondents were questioned about the measures adopted to cope with the rising stress levels during the pandemic. According to the Pearson Chi Square test in Table 4 , there was a significant difference in the measures used by the different age categories. Fig. 3 shows the detailed distribution of different stress reliever activities used among different age categories.

Visualization demonstrate the distribution of stress relieving activities among different age categories.

3.4. Social media

According to Fig. 3 , a significant number of individuals from different age categories used social media as a medium for stress reliever. Further in Fig. 4 . a, the findings provide the distribution of the sample for the use of different platforms. While the majority of respondents used social media, 1.44% did not have an account on any platform. Fig. 4 . b gives the detailed distribution of platforms for age-wise groups. YouTube (39%) was the preferred platform for the age group '7–17,' followed by Whatsapp (35%) and Instagram (17%). Most of the social networking sites in India restricts individuals below 13 years of age to have an account on their platforms. However, some individuals under 13 years of age used Instagram (n = 2), Whatsapp (n = 16), and Snapchat (n = 1). For the age group ‘18-22’, Instagram (39%) was the most preferred networking site, and the respondents in the age-group ‘23-59’ preferred WhatsApp (38%).

Visualization demonstrate the distribution of preferred social media platform for a) the sample and b) among different age categories.

As shown in Table 2 , the average time spent on social media for the age group ‘7-17’ was 1.68 h/day (95% Confidence Interval, 1.52–1.85), 2.64 h/day (95% Confidence Interval, 2.50–2.78) for the age group ‘18-22’, and for the age group ‘23-59’, it was 2.37 h/day (95% Confidence Interval, 2.14–2.61). The difference between the groups was statistically different (P < 0.0001*).

4. Discussion

The outbreak of Covid-19 has upended the lives of all parts of the society. One of the most immediate changes introduced was the closure of educational institutions to slow the transmission of the virus. In order to prevent further interruption of studies, new teaching methods for the online delivery of education were introduced ( Johnson et al., 2020 , Di Pietro et al., 2020 ). However, these measures can have long-term consequences on the lives of students ( Cohen et al. 2020 ). Therefore, there is a strong need to record and study the effects of the changes being made. In this study, our aim is to analyze the impact of the COVID-19 pandemic on the education, health, social life of the students, and demonstrate results about its subsequent effect on their daily routine amid travel restrictions. The findings indicate that the time spent by students on online classes did not comply with the guidelines issued by the Ministry of Human Resources Development (MHRD) ( Department of School Education & Literacy Ministry of Human Resource Development 2020 ). Limited class interaction and inefficient time table significantly affected the satisfaction levels among students. The peer-to-peer impact in the school environment motivates individuals to work hard and learn social skills, which may not be possible in an online setting. Moreover, the biggest challenge for online learning is the requirement of efficient digital infrastructure and digital skillset for both students and teachers.

Further, this study analyses the impact of different factors to measure stress levels among students. Alarmingly, 51.4% of respondents reported that they did not utilize their time during the period of lockdown. Furthermore, sleeping habits, daily fitness routines, and social interaction significantly affected their health conditions. The government agencies imposed measures such as social distancing and restrictions on travel but they did not take into account the health implications. Although, these measures are necessary to regulate safe conditions, there is no strategy to safeguard the psychological impact due to the Covid-19 pandemic. Our research also explores the different coping mechanisms used by students of different age groups. Moreover, we analyzed various digital social media tools used by students as a self-management strategy for mental health. Our statistical analysis addresses key concerns related to online education and health due to the Covid-19 pandemic.

5. Opinions and recommendations

Once the COVID-19 pandemic ends and educational institutions re-open, the concerned authorities should continue to invest in online education to enhance learning experience. They should carefully analyze the issues experienced during sudden transition to online learning and prepare for any future situations. Proper training of educators for the digital skills and improved student-teacher interaction must be conducted. For disadvantaged students, availability of digital infrastructure with proper internet availability and access to gadgets must be ensured to avoid any disruption to their study.

Due to the situation in Covid-19, many students are likely to suffer from stress, anxiety, and depression, so it is necessary to provide emotional support to students. Future work in this direction could be to analyze the association of different stress busters on the mental health of the students. Moreover, guidelines should be created to anticipate the needs of the vulnerable student population. Improved healthcare management would ensure the delivery of mental health support.

6. Limitations

There are some limitations to our study that should be noted. The first limitation is the sampling technique used. It relies on digital infrastructure and voluntary participation that increases selection bias. The imposed travel restrictions limited the outreach to students who do not have access to online learning. Second, the study is obtained from one specific area, given the lockdown orders and the online medium of classes, we expect these results to be fairly generalizable for schools and universities nationwide. Another limitation of this study is the cross-sectional design of the survey, there was no follow-up period for the participants.

7. Conclusion

In this study, our findings indicated that the Covid-19 outbreak has made a significant impact on the mental health, education, and daily routine of students. The Covid-19 related interruptions highlight key challenges and provide an opportunity to further evaluate alternate measures in the education sector. The new policies and guidelines in this direction would help mitigate some of the negative effects and prepare educators and students for the future health crisis.

Declaration of Competing Interest

There is no conflict of interest.

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COVID-19 and the Educational Response: New Educational and Social Realities

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This research topic inquires into multiple and diverse impacts of the Covid-19 pandemic on education within various international contexts as billions navigate new educational and social realities. This crisis has led educators at all levels of PreK-20 and their stakeholders to question basic ...

Keywords : pandemic, education, social disruption, teaching, covid-19, coronavirus

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New UNESCO global survey reveals impact of COVID-19 on higher education

In the wake of the unprecedented COVID-19 education disruptions which affected more than 220 million tertiary-level students around the world, UNESCO conducted a global survey aimed at providing an evidence-based overview of the current situation of the higher education system at national and global levels.

The results provide insights on how some countries were able to transform challenges, brought by the rapid digitalization of education, into opportunities through strong government support and international cooperation.

The survey attempts to assess the varying impact the pandemic had on higher education systems in terms of access, equity and quality of teaching and learning, university operation, national challenges, emerging issues, and strategic responses.

 The key findings for the various assessment dimensions are:

 Mode of teaching and learning: The major impact of COVID-19 on teaching and learning is the increase in online education. The hybrid mode of teaching has become the most popular form. 

• Access : The impact of COVID-19 on enrollment varies by regional and income levels. High income and Europe and North American countries are better able to cope with the disruption due to government funding support and increase in domestic enrollment.
• International mobility : Mobility took a major hit, affecting international students significantly, but virtual mobility could compensate or even replace physical mobility. 
• University staff : Despite the closure of many universities, the impact of COVID-19 on university staff compared to the previous academic year is limited.  
• Disruption of research and extension activities : COVID-19 caused suspension and cancellation of teaching and research activities globally. 
• Widening inequality : The mixed impact of the pandemic on university finance shed a light on the exacerbation of inequality in higher education. Financial support from the government and external sources are crucial to the survival of HEIs. 
• University operations : The strong impact of the pandemic on HEIs operations caused reduced maintenance and services on campus and campuses closures worldwide.
• National challenges : Health and adaptation to new modes and models of teaching are the top concerns for students and institutions. 
• Transition from higher education to work : The significant reduction of job opportunities makes the transition from higher education to the labor market more difficult. Employers are also seeking applicants with higher technology skills. 
• National priority : Strategic options for country-specific response are to improve infrastructure and availability of digital devices for online or distance learning as well as support for teachers and more international collaboration in research and policy dialogues.

The global survey was addressed to the 193 UNESCO Member States and 11 Associate Members. Sixty-five countries submitted responses, fifty-seven of which were used for the analysis that informed the report.

• Access the full report
• More on UNESCO’s work in higher education

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• Published: 07 August 2024

Well-being among university students in the post-COVID-19 era: a cross-country survey

• M. Bersia 1 ,
• L. Charrier 1 ,
• G. Zanaga 1 , 2 ,
• T. Gaspar 3 ,
• C. Moreno-Maldonado 4 ,
• P. Grimaldi 1 , 2 ,
• E. Koumantakis 1 , 2 ,
• P. Dalmasso 1 &
• R. I. Comoretto 1  

Scientific Reports volume  14 , Article number:  18296 ( 2024 ) Cite this article

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University students have to handle crucial challenges for their future lives, such as succeeding in academic studies and finding attachment figures. These processes could potentially involve their well-being and mental health, with possible sociocultural differences based on the country of study. In order to explore such potential differences, a cross-sectional, multi-center survey was performed involving students from the University of Torino (Italy), Sevilla (Spain), and Lusòfona (Portugal). The survey, conducted from May to November 2023, investigated students’ demographic and educational details, socioeconomic status, social support, mental health, academic environment, perceived COVID-19 pandemic impact, and future plans. Demographic profiles showed a predominance of female participants and straight sexual orientation, followed by bisexuality. Italian students showed the lowest levels of mental well-being and the highest rates of mental problems (anxiety and depression) and suicidal risk across the three countries despite the relatively similar profiles of social support. The prevalence of the students’ confidence in their professional future is higher in Spain than in Italy and Portugal. This study provides a comprehensive examination of university students’ mental health and well-being in three Southern European countries, addressing the major mental health challenges among university students and offering valuable insights for public health purposes.

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Mental health prevalence and predictors among university students in nine countries during the COVID-19 pandemic: a cross-national study

Introduction.

The university years represent an intriguing life period with plenty of challenges, including academic issues, emotional delusions, and problems related to the transition between the end of adolescence and the beginning of adulthood 1 . The interplay of academic pressures, social dynamics, and developmental transitions provides a delicate balance in which mental vulnerabilities can easily thrive 2 , 3 , 4 . Furthermore, university experience can move the needle: indeed, college students are at higher risk of developing a mental condition compared to their non-college peers 5 , 6 . In particular, Beiter pinpointed three college-related individual concerns that may heighten mental risk: struggles with academic performance, intense pressure to succeed, and uncertainty about post-graduation life 7 . Furthermore, academic environments themselves, demanding high effort and commitment, could play a role in impairing the university experience 8 , 9 , 10 . All these elements could synergically stimulate the onset of both burnout and several mental conditions, such as anxiety, depression, and suicidality 8 , 9 , 10 , 11 . In this regard, a prevalence of about 30% % of depressive and anxiety symptoms among university students has been estimated 12 . In particular, the female gender, the pre-existing mental health conditions, and the lower socioeconomic status seem to be additional risk factors across multiple studies 13 , 14 , 15 . On the other hand, good social support can mitigate the above-mentioned risk factors for mental health, playing a crucial protective role as a source of motivation and promoting healthier lifestyles 16 . Further, the perceived social support could also represent a relevant individual background, capable of encouraging students’ resilience and having beneficial effects on academic performance 16 .

Beyond the well-known influential factors, the COVID-19 pandemic profoundly impacted students’ mental health worldwide in both the short- and long term. In the immediate phase after the COVID-19 pandemic eruption, the impairment was observed mainly in terms of difficulties concentrating, disruptions of sleep patterns, concerns about academic performance, and increased anxiety and depression 17 , 18 , 19 , 20 . Furthermore, several researchers assessed the impact of prolonged exposure to the pandemic on cognitive and affective processing among students, observing an increase in the prevalence and severity of conditions such as anxiety, depression, suicidality, chronic sleeping difficulties, appetite changes, and health-related anxiety 21 , 22 , 23 . More specifically, the pandemic could have contributed to impaired mental health also among college students through the implementation of distancing measures leading to distance learning modalities, social isolation, lack of access to traditional support services, and family financial difficulties 24 , 25 . Additionally, research suggests that female students and those residing in lower-quality housing during lockdowns displayed exacerbated declines in mental health 25 , 26 .

In May 2022, the WHO Director-General declared the global emergence related to the COVID-19 pandemic concluded 27 . However, the pandemic long-term consequences on youths’ mental health are still a relevant public concern, and they still deserve careful surveillance over time to address targeted mitigation policies. The still scarce literature on the topic mainly relies on data from national-level surveys, hampering the adoption of a transcultural approach 28 , 29 , 30 , 31 , 32 .

To our knowledge, literature still lacks studies assessing and comparing college students’ mental health and well-being across different environments in the delicate post-pandemic phase. In order to address these research gaps, the present study describes the main findings of an international project that explored university students' mental health and well-being in three universities in Italy, Spain, and Portugal. These Mediterranean countries share cultural and environmental similarities (e.g. dietary habits, natural environment, social bounds) 33 , 34 , 35 , despite the societal peculiarities (e.g. financial situation, physical activity habits) and the adoption of different pandemic-related measures potentially influencing mental health and well-being outcomes 36 , 37 , 38 , 39 . More specifically, the aim was to discern commonalities and differences in students’ characteristics and experiences across these countries through a comparative approach, trying to offer a more detailed understanding of well-being patterns among college students in the post-COVID-19 era.

Survey design

A cross-sectional and multi-center survey was conducted between May and November 2023 in three European universities, the University of Torino (Italy), Sevilla (Spain), and Lusòfona (Portugal).

Participants

Students were eligible for enrollment in the study if they were (1) between 18 and 35 years old and (2) attending a bachelor's or master’s degree program. Those who declined to provide informed consent were excluded from the study. All the eligible students (about 79,000 students in Italy, 60,000 in Spain, and 15,000 in Portugal) received an institutional email with a link to an anonymous online questionnaire. Students could agree to participate in the study by checking the box at the bottom of the personal data treatment information sheet on the first page of the online questionnaire. There was also a section explaining the study’s goals, clarifying that there was no obligation to complete the questionnaire and assuring confidentiality and anonymity of the collected data. Finally, the research team did not offer any incentives to increase recruitment nor played an active role in selecting and/or targeting specific subpopulations of students. Participation was entirely voluntary, with students having the option to opt-out at any stage. Informed consent was obtained from all subjects.

Ethical considerations

Data was collected anonymously, no personal identifiers were collected, and the IP address was not registered. Approval for this study has been obtained from the institutional ethics boards of the participating universities (Prot. no. 0059546 of 30 January 2023, for the University of Torino; approval no. 20/23 of 16 May 2023 obtained by the Comité de Ética en la Investigación de Sevilla; approval no. 9 of 8 March 2023 received by the Ethics and Deontology Commission For Scientific Research (CEDIC) for the Lusofona University). The study was conducted in accordance with the international guidelines and regulations and the Declaration of Helsinki.

Questionnaire

A multi-language online survey (i.e., in English, Italian, Spanish, and Portuguese) was implemented on the REDCap platform of the University of Torino 40 , 41 . Overall, we adopted standardized scales validated in English. When available, we used the validated versions of the scales in Italian, Spanish, and Portuguese; otherwise, the English scales underwent the forward–backward translation process. The specific process for each scale, with the relevant validation work, can be found in the Supplementary file, Table S1 . Respondents could choose the language in which they would fill out the questionnaire. The survey encompassed the following key components: demographic details (e.g., age, sex, sexual orientation), educational profile (course area, year of study, progress), socioeconomic status, social support, mental health and well-being, perceived COVID-19 impact, academic stress, and future perspectives information.

In particular, information related to sex at birth and sexual orientation was assessed following the GeniuSS Group guidelines 42 . Sexual orientation was asked as follows: ‘How do you identify yourself?’, adopting as possible answers: ‘straight’, ‘lesbian’, ‘gay’, ‘bisexual’, ‘queer’, ‘pansexual’, ‘asexual’, ‘unlabelled’, ‘questioning’, ‘other’.

Socioeconomic status (SES)

The students’ socioeconomic status was investigated using the MacArthur Scale of Subjective Social Status 43 . The scale visually represented a ladder in which steps were associated with numbers ranging from 1 (low perceived SES) to 10 (high perceived SES). Respondents were then asked to place themselves on the ladder compared to their peers. The personal financial situation was evaluated through one further question with four possible answers: ‘dependent on family’, ‘work’, ‘scholarship’, or ‘other’.

Social support

Social support was assessed using a well-known validated psychometric tool, the Multidimensional Scale of Perceived Social Support (MSPSS) 44 . The scale consists of 12 items exploring an individual's perceived social support distributed across three subscales: Family, Friends, and Significant Other Support. Individuals rated their agreement with each item on a 7-point Likert scale ranging from ’strongly disagree’ to ’strongly agree’. The scores for each subscale are added up and then divided by 4, while for the overall support, the sum score is divided by 12. Both the overall and subscales scores (ranging from 1 to 7) provide a measure of the individual’s perceived social support. Low, medium, and high social support are defined based on the overall score (i.e. 1–2.9, 3–5, and 5.1–7, respectively). An excellent internal consistency was found for the overall scale (α > 0.92), and the three subscales, consistently in the three countries.

Mental health

Mental health was evaluated using different validated tools based on the specific characteristics under investigation. Depression and anxiety were assessed through the Patient Health Questionnaire-2 (PHQ-2) 45 and the Generalized Anxiety Disorder-2 (GAD-2) 46 , respectively. These two brief self-report instruments derived from the longer Patient Health Questionnaire-9 (PHQ-9) 47 and the Generalized Anxiety Disorder-7 (GAD-7) 48 questionnaire, both commonly used tools in mental health assessments. Participants were asked to indicate the frequency of presentation of each symptom using a 4-point scale ranging from 0, ’not at all’, to 3, ‘nearly every day’. A total score ≥ 3 on the PHQ-2 assessment suggests the presence of anxiety symptoms, while a score ≥ 3 on the GAD-2 evaluation indicates the occurrence of depressive traits. The PHQ-2 and the GAD-2 scales showed good internal consistency (α = 0.80 and α = 0.85, respectively), consistently in the three countries.

Suicidal behaviors and ideation were evaluated with the Suicide Behaviors Questionnaire-Revised (SBQ-R) 49 . This self-report validated questionnaire includes four items inquiring about different aspects related to suicidal risk (suicidal ideation, past suicide attempts, and the likelihood of engaging in future suicidal behavior). SBQ-R can help identify individuals who may be at risk for suicidal behavior or who have a history of suicidal thoughts or attempts. Total scores (ranging from 3 to 18) have been categorized identifying groups with low (total score less than 7) and high risk (total score equal to or higher than 7) of suicidal behavior 49 . A good internal consistency was found in our sample (α = 0.82), independently by country. Before the SBQ-R questionnaire, participants were warned of questions about a particularly sensitive topic, and the section was optional.

Well-being was investigated through the Mental Health Continuum-Short Form (MHC-SF) 50 . The self-report validated scale consists of 14 items measuring the degree of several aspects of well-being: (a) Overall well-being (items 1–14); (b) Emotional well-being (items 1–3), defined in terms of positive affect and satisfaction with life; (c) Social well-being (items 4–8), as described in Keyes’ model of social well-being 51 ; and (d) Psychological well-being (items 9–14). The MHC–SF asks individuals how frequently they felt in a specific aptitude, from 0 (none of the time) to 5 (all of the time): the higher the overall score, the higher the level of well-being. In our sample, an excellent internal consistency (α > 0.90) was found referring to Overall and Emotional well-being, while a good internal consistency was shown for both Social, and Psychological well-being (α = 0.82, and α = 0.87, respectively), consistently in the three countries.

Perceived COVID-19 impact

A 10 items scale from the 2021/2022 Health Behavior in School-Aged Children was used to evaluate the subjective impact of COVID-19-related measures on various aspects of individuals’ lives: life in general, overall and mental health, relationships with family and friends, school performance, physical activity, eating behaviors, future expectations, financial situation 52 . Respondents were asked to assess the extent of the impact by selecting one of the following options on a five-point Likert scale: 1 = ‘’very negative’, 2 = ’somewhat negative’, 3 = ’neither positive nor negative’, 4 = somewhat positive’, or 5 = ’very positive’. Collapsing some response options, a three-level variable was obtained for each item, identifying negative (options 1 and 2), neutral (option 3), and positive (options 4 and 5) COVID-19 impact groups 53 .

• Academic stress

The Academic stress was evaluated using the Effort-Reward Imbalance—Student Questionnaire (ERI-SQ) 54 , a self-reported validated questionnaire based on the Effort-Reward Imbalance (ERI) theoretical framework 55 . The tool includes three subscales: the Effort (from items 1 to 3), the Reward (from items 4 to 9), and the Overcommitment dimensions (from items 10 to 14). The Effort score identifies the intensity and amount of effort an individual perceives in academic activities. It is calculated based on participants' responses to items regarding the study load, time pressure, and interruptions in doing the academic tasks. The Reward score reflects the perceived level of rewards gained in exchange for the efforts made. Rewards encompass social recognition, career advancement, job security, or other positive outcomes associated with academic accomplishments. In addition, the ERI-SQ incorporates a measure of Overcommitment, which denotes a personality trait characterized by an excessive dedication to work or academic tasks, regardless of the balance between effort and reward. From the previous measures, the Effort-Reward Imbalance (ERI) ratio is computed by dividing the Effort score by the Reward score multiplied by a correction factor 54 , 56 . The ERI ratio suggests a possible imbalance between the effort and the reward. For ERI ratio equal to 1, the student reports equal levels of effort and reward, an ERI ratio < 1 indicates less effort than rewards, while an ERI ratio > 1 indicates that the perceived effort is greater than the rewards, suggesting a greater likelihood of negative health outcomes due to stressors in the academic environment. Similarly, a high overcommitment score implies a propensity to invest excessive effort, even when the corresponding rewards are perceived as inadequate. The 14-item scale showed good internal consistency (overall α = 0.83), in contrast, independently by country, lower internal consistency levels were registered for Effort, Reward, and Overcommitment scales (α = 0.66, α = 0.69, and α = 0.80, respectively).

Future perspectives

Some further questions were asked about students’ future professional perspectives: (1) Plans for the future after completing higher education (the possible answers were pursuing further studies (post-graduate, master's, or Ph.D.), getting a job, working in another country, starting a business, or not having a specific plan); (2) Professional future: two questions with response options ranging from 1 (‘strongly disagree’) to 5 (‘strongly agree’) were provided to explore the readiness to manage and build the professional future after completing higher education and confidence in professional future. Dichotomized variables were then created based on high (options 4 or 5) or medium/low (equal or lower than 3) agreement. Furthermore, one further question exploring overall future expectations was provided. In this regard, subjects were asked to rate their expectations for the future on a scale from 0 to 10, where 0 represents poor expectations and 10 excellent ones. This assessment reflects general optimism or pessimism about prospects.

Data analysis

Demographic information and psychometric measures were described with absolute frequencies and percentages for categorical variables and medians and interquartile ranges (IQRs) for continuous ones. Data was stratified by country, and the rate of missing values for each aforementioned variable was reported. Afterward, further stratification by sex was performed within each country, and d fferences by sex were tested with a chi-square test for categorical variables and a Wilcoxon test for continuous ones. All statistical tests were two-sided, and the level of statistical significance was set at 0.05. Data were analyzed using the R software version 4.3.0 57 . Radar plots were generated to visually represent specific results by country, using Flourish 58 , a data visualization platform, and InkScape 59 , a vector graphics editor, to enhance their quality and clarity.

Demographic and Educational profile of participants

Our sample comprised 8773 students in Italy, 612 in Spain, and 396 in Portugal. The response rates in the three universities were 11.1% (Italy), 2.6% (Portugal), and 1.0% (Spain). We then excluded all participants who waived informed consent (n = 90), those older than 35 (n = 1308) or younger than 18 (n = 3), and those with missing information about sex (n = 72) obtaining a final overall sample of 8380 students (7559 students in Italy, 469 in Spain, and 352 in Portugal).

Table 1 shows the demographic and educational characteristics of the sample. The median age of respondents was homogeneous in the three countries. The majority of the sample was composed of females (more than 65% in the three countries) and declared a straight sexual orientation (> 70%). The main reported non-straight sexual orientation was bisexual, declared by 8–20% of the participants across countries (Most respondents attended a program concerning “Humanities and Philosophy” and “Social and Economic Sciences” areas, although over 12% of participants did not provide such information. Most students were in the first three years of college in the three countries (71% in Italy, 62% in Spain, and 88% in Portugal). Less than 50% of students in Italy and Spain declared themselves on track (44% and 46%, respectively), compared to 73% of Portuguese students.

Socioeconomic status and social support

The MacArthur Scale registered slightly higher levels of Subjective Social Status in Italy (median score: 7.0; IQR: 5.0–7.0) than in Spain and Portugal (median score: 6.0; IQR: 5.0–7.0 in both countries). Participants declared that they mainly depend on their families for financial support (> 75%), with variations in rates of work and scholarships across the countries. Notably, fewer respondents in Italy and Portugal (11% and 16%, respectively) relied on scholarships compared to the Spanish sample (29%), while an inverse trend was found regarding rates of work (i.e., lower in Spain than in Italy and Portugal) (Fig.  1 , Table 2 , and Table S2 , Supplementary file).

Financial situation among university students in Italy, Spain, and Portugal. Radar plots with percentages of financial situation are presented across the three countries.

The social support profiles emerging from the MSPSS showed similar perceived support levels on the three subscales among the three countries. Significant other subscales represented the primary source of support (median scores of at least 6.0 across the three countries). Overall, most respondents reported high social support (> 60%), mainly from Significant other and Friends, without relevant cross-country differences. Some sex differences were found within countries concerning social support (Table S3 , Supplementary file). More specifically, females declared higher Friends and Significant others support scores in Italy and Spain than their male peers (p < 0.001). In Portugal, males declared higher scores of Family support than females (p = 0.007). Patterns are globally confirmed adopting the categorized variables.

Mental health and well-being

In Italy and Spain, about two out of three respondents showed a high GAD-2 score (67% and 64%, respectively), while in Portugal, this anxious trait was presented by 50% of the sample (Table 3 , Fig.  2 ). However, the percentages of high depressive scores on the PHQ-2 were below 50% in all countries (44% in Italy, 44% in Spain, and 34% in Portugal). While students in Italy and Spain exhibited a higher frequency of both anxious and depressive symptoms compared to the Portuguese sample, a quite homogeneous picture emerged exploring SBQ-R scores. More specifically, 30%, 26%, and 29% of respondents were classified in the high suicidal risk group in Italy, Spain, and Portugal, respectively. Concerning the MHC-SF questionnaire, Italian respondents exhibited lower overall scores (median score: 30.0; IQR: 21.0–40.0) than Spanish and Portuguese ones (median scores: 41.0 (IQR: 29.0–51.0) and 39.0 (IQR: 29.0–48.0), respectively) indicating lower mental well-being among Italian participants compared to the others. This pattern is consistent across the three domains of the MHC-SF questionnaire.

Radar plots showing rates of mental problems and confidence levels in the professional future among university students in Italy, Spain, and Portugal. Radar plots with percentages of anxiety symptoms (GAD-2), depressive symptoms (PHQ-2), suicidal risk (SBQ-R), and confidence in professional future are presented across the three countries.

In terms of sex differences across the mental domains, Italian and Portuguese females presented higher scores in both the GAD-2 (p < 0.001 in both countries) and the PHQ-2 scales (p = 0.011 and p = 0.023, respectively), while no substantial patterns were found regarding SBQ-R. In the three countries, lower levels of well–being could be observed in girls than in boys in all domains of the MHC-SF questionnaire, with significant differences between the two sexes in Italy and Portugal for the overall score and social and psychological domains (Table S3 , Supplementary file).

Perceived impact of the COVID-19 pandemic

Results about the perceived impact of the COVID-19 pandemic are shown in Fig.  3 and Table S4 (Supplementary file). University students were more likely to report a negative than a positive pandemic impact on several life domains (i.e., life as a whole, overall and mental health, physical activity, eating behaviors, family financial situation, and future expectations), especially in Italy. In particular, half of Italian students (50.2%) reported a negative impact of the pandemic on their mental health compared to 40.3% and 37.8% of Spanish and Portuguese ones. Conversely, the COVID-19 pandemic’s influence on relationships with family and friends and school performance seemed to have been perceived more positively than negatively. A missing rate of 16% was observed consistently throughout the items.

Prevalence of positive (in blue) and negative (in red) perceived COVID-19 impact on several life domains among university students in Italy, Spain, and Portugal. Radar plots with percentages of perceived COVID-19 pandemic impact on students’ overall health, life in general, family relationships, friends’ relationships, mental health, school performance, physical activity, eating behaviors, future perspectives, and financial situation are presented across the three countries.

Academic stress and future perspectives

The ERI-SQ scoring revealed a homogeneous pattern in perceived overcommitment levels and the ERI ratio across countries (Table 4 ). In all countries, the median ERI ratio was slightly greater than 1, indicating that 6–13% of the effort was not met by the received rewards. In all countries, females seemed to have a significantly higher ERI ratio than males (Table S3 , Supplementary file).

The expectations for the future were similar in the analyzed universities (median score: 7.0; IQR: 5.0–8.0), while perspectives after graduation showed a higher variability across countries (Table 4 ). More specifically, in Italy, most students declared their intention to find a job after graduation (35%), while in Spain and Portugal, most planned to continue their studies (46% and 40%, respectively). Overall, a decreasing prevalence of participant students declaring confidence in their own professional future was found in Spain, Italy, and Portugal (47%. 34%, and 20%, respectively). Furthermore, Italian and Spanish students felt more prepared for work than Portuguese ones (35% and 29% vs. 19%, respectively).

The present cross-country project primarily aimed to identify common and specific mental health and well-being traits among university students in Italy, Spain, and Portugal.

Respondents were primarily females with a median age of 21, currently attending the first three academic years. About three out of four students declared a straight sexual orientation, while bisexuality represented the second most common sexual orientation, ranging from 8% in Italy to 20% in Spain. The high levels of bisexuality compared to the previous studies (up to 10%) could be the result of undergoing changes in sexual norms and behaviors, leading to even more youths identifying as bisexual 60 , 61 . Italian students presented higher median socioeconomic status than Portuguese and Spanish ones, reflecting the different economic wealth situations observed by the World Bank in such countries 38 , 39 . Conversely, quite similar patterns in social support were registered across universities, confirming the expected cultural similarities in social bonds in these three Mediterranean countries 35 , 62 , 63 . Overall, students declared a relatively higher support from Friends and Significant other than Family, underlying their developmental transition from adolescent to young adult supportive networks 64 , 65 , 66 .

The PHQ-2 and GAD-2 assessments showed high levels of anxiety (> 50%) and depressive symptoms (> 30%) among students in the three countries, being exacerbated among females than males. Furthermore, these first insights suggest higher levels of such mental problems among Italian and Spanish students than Portuguese ones. The disparities in emotional, social, and psychological well-being captured by MHC-SF are also noteworthy, with Italian students reporting lower scores than their counterparts in Spain and Portugal.

These results suggested different cross-country trends based on the indicators explored, enforcing the validity of conceptualizing mental health as a multidimensional construct in which the various dimensions can have different correlated patterns 51 , 67 , 68 , 69 , 70 . More specifically, the present study found that Italian students showed the lowest levels of well-being and the highest rates of mental problems across the three countries. These findings align with those reported by recent works on nationally representative samples of adolescents in the same countries, suggesting shared underlying causes at a macro-level, even among contiguous age groups (adolescents and young adults) 36 , 71 . Several factors could be involved in the observed pattern, including pandemic-related measures duration and strictness, as confirmed by the higher levels of negative perceived impact of COVID-19 on mental health in Italy, observed in the present and other studies 36 , 71 . Moreover, cross-country differences in physical activity could have had a contributing role 37 . In particular, the high negative impact of pandemic-related measures on students’ physical activity in Italy could have exacerbated the pre-pandemic cross-cultural exercise differences 37 .

Furthermore, the observed cross-country pattern of mental problems in the university environment may also be attributed to the significant social and academic pressures that Italian university students experience 10 , 72 . Our analysis revealed a lower percentage of scholarship recipients and higher rates of working students in Italy than in the other explored countries. These elements suggest differences in university study support policies across countries, reflecting the different financial frameworks, which also have consequences for the well-being of university students 73 .

Among the mental health issues explored in this survey, results about suicidality deserve to be discussed separately, in light of the latest evidence on this sensitive topic.

Approximately one-third of students within the three countries exhibited characteristics placing them in the “high risk” category in the SBQ-R assessment, with substantially geographically homogeneous patterns across countries. Such prevalence is higher than that emerged from other surveys conducted before the COVID-19 pandemic 74 , 75 , 76 , in line with data collected during 2020 77 , and slightly lower than levels registered in 2021 77 . In particular, literature exploring long-term temporal trends of suicidality suggested an increase in the phenomenon since 2021, which was attributed to the impact of COVID-19 on students’ lives 21 , 78 , 79 , 80 . Furthermore, in our sample, high rates of negative perceived impact of the COVID-19 pandemic on mental health were observed across the three countries, enforcing such possible association. From this perspective, the long-term consequences of COVID-19 pandemic-related measures on youths’ mental health could have left prolonged traces, still detectable in 2023, during the so-called post-COVID-19 era. In this regard, literature is still lacking, and further exploration of the topic is needed to increase the knowledge of the phenomenon and to guide the policy agenda promoting youths’ mental health 81 , 82 .

COVID-19 perceived impact assessment showed a relatively homogeneous picture among students across countries. Specifically, pandemic-related measures seemed to have negatively impacted several domains (i.e., mental health, physical activity, future perspectives, and financial situation). Still, a prevailing positive impact was perceived regarding relationships with family, friends, and school performance. Overall, our findings are consistent with other studies adopting the same measurement tool on nationally representative samples of adolescents in the three countries, enlightening shared environmental exposures across age groups 53 , 83 . More specifically, results referring to the pandemic impact on family relationships are consistent with the findings by other authors, who observed tighter family bonds after the lockdown establishment 17 , 25 , 84 , 85 , 86 , 87 , 88 .

The academic stress assessment pointed out similar trends among countries: the median ERI ratio was higher than one among students regardless of the country, indicating perceived rewards lower than expected, especially among girls. These findings align with results from previous works that showed unbalanced ERI ratios toward effort among university students 10 , 54 .

Finally, a quite heterogeneous geographical pattern was found regarding future professional perspectives: 20–30% of students in our sample felt prepared for work, and confidence in the professional future showed a decreasing pattern from Spain to Italy and Portugal. This presumably reflects the cross-country economic wealth differences and the widespread uncertainty about the future among youths 38 , 39 , 89 , 90 .

Limitations and strengths

The observed findings should be interpreted cautiously due to several limitations of the study. While our sample included over 8000 students, it only represented a small percentage of the target population (approximately 150,000 students in the academic year 2022–2023). This issue could potentially hinder the generalizability of our findings. Additionally, most students responded in Italy, resulting in an unbalanced sample and few participants in Spain and Portugal. These methodological issues could lead to analytical constraints regarding statistical comparisons between countries, making it possible to analyze differences only within each country. The unbalanced sample and the low sample size in 2 out of 3 countries also limited the exploration of the factors associated with well-being in a cross-country framework. Furthermore, the self-reported nature of the data and the cross-sectional design of the study also represented additional weaknesses.

Despite these limitations, the present work is one of the first cross-country surveys exploring academic stress, mental health, and well-being among university students in the post-COVID-19 era. This international research stands out for its rigorous methodology, using validated tools and a consistent protocol to assess the well-being of university students in Italy, Spain, and Portugal. The comparative approach adopted across countries allowed us to explore the complexities of three Southern European countries sharing cultural similarities and to study their influence on university students' well-being. In particular, we found cross-university patterns consistent with the existing studies on the topic despite a high level of heterogeneity recognized in the literature in psychometric instruments and target student populations. Finally, using validated tools like PHQ-2, GAD-2, SBQ-R, and MHC-SF allowed us to simultaneously capture different mental health and well-being dimensions among university students, providing a more comprehensive and holistic framework.

Conclusions

This cross-sectional survey explores the well-being levels and mental health patterns in three Southern European countries in the post-COVID-19 phase in light of their cultural similarities and peculiarities.

Overall, Italian students showed the lowest levels of mental well-being and the highest rates of mental problems (i.e., anxiety and depression) and suicidal risk across the three countries despite the relatively similar profiles of social support. The prevalence of the students’ confidence in their professional future is higher in Spain than in Italy and Portugal. The emerging picture offers valuable insights into this public health topic and paves the way for further exploration of the relationships between students' environmental factors (e.g., social support and academic stress) and various aspects of their well-being.

Data availability

Data is available from the corresponding author upon reasonable request.

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We would like to thank the students who participated in the study and the university staff who assisted us in sending the links for participation.

The present study was funded by the University of Torino (COMR_GFI_22_01_F, COMR_RILO_23_01_F, COMR_RILO_24_01).

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The Impact of COVID-19 on the Careers of Women in Academic Sciences, Engineering, and Medicine (2021)

Chapter: 8 major findings and research questions, 8 major findings and research questions, introduction.

The COVID-19 pandemic, which began in late 2019, created unprecedented global disruption and infused a significant level of uncertainty into the lives of individuals, both personally and professionally, around the world throughout 2020. The significant effect on vulnerable populations, such as essential workers and the elderly, is well documented, as is the devastating effect the COVID-19 pandemic had on the economy, particularly brick-and-mortar retail and hospitality and food services. Concurrently, the deaths of unarmed Black people at the hands of law enforcement officers created a heightened awareness of the persistence of structural injustices in U.S. society.

Against the backdrop of this public health crisis, economic upheaval, and amplified social consciousness, an ad hoc committee was appointed to review the potential effects of the COVID-19 pandemic on women in academic science, technology, engineering, mathematics, and medicine (STEMM) during 2020. The committee’s work built on the National Academies of Sciences, Engineering, and Medicine report Promising Practices for Addressing the Underrepresentation of Women in Science, Engineering, and Medicine: Opening Doors (the Promising Practices report), which presents evidence-based recommendations to address the well-established structural barriers that impede the advancement of women in STEMM. However, the committee recognized that none of the actions identified in the Promising Practices report were conceived within the context of a pandemic, an economic downturn, or the emergence of national protests against structural racism. The representation and vitality of academic women in STEMM had already warranted national attention prior to these events, and the COVID-19

pandemic appeared to represent an additional risk to the fragile progress that women had made in some STEMM disciplines. Furthermore, the future will almost certainly hold additional, unforeseen disruptions, which underscores the importance of the committee’s work.

In times of stress, there is a risk that the divide will deepen between those who already have advantages and those who do not. In academia, senior and tenured academics are more likely to have an established reputation, a stable salary commitment, and power within the academic system. They are more likely, before the COVID-19 pandemic began, to have established professional networks, generated data that can be used to write papers, and achieved financial and job security. While those who have these advantages may benefit from a level of stability relative to others during stressful times, those who were previously systemically disadvantaged are more likely to experience additional strain and instability.

As this report has documented, during 2020 the COVID-19 pandemic had overall negative effects on women in academic STEMM in areas such productivity, boundary setting and boundary control, networking and community building, burnout rates, and mental well-being. The excessive expectations of caregiving that often fall on the shoulders of women cut across career timeline and rank (e.g., graduate student, postdoctoral scholar, non-tenure-track and other contingent faculty, tenure-track faculty), institution type, and scientific discipline. Although there have been opportunities for innovation and some potential shifts in expectations, increased caregiving demands associated with the COVID-19 pandemic in 2020, such as remote working, school closures, and childcare and eldercare, had disproportionately negative outcomes for women.

The effects of the COVID-19 pandemic on women in STEMM during 2020 are understood better through an intentionally intersectional lens. Productivity, career, boundary setting, mental well-being, and health are all influenced by the ways in which social identities are defined and cultivated within social and power structures. Race and ethnicity, sexual orientation, gender identity, academic career stage, appointment type, institution type, age, and disability status, among many other factors, can amplify or diminish the effects of the COVID-19 pandemic for a given person. For example, non-cisgender women may be forced to return to home environments where their gender identity is not accepted, increasing their stress and isolation, and decreasing their well-being. Women of Color had a higher likelihood of facing a COVID-19–related death in their family compared with their white, non-Hispanic colleagues. The full extent of the effects of the COVID-19 pandemic for women of various social identities was not fully understood at the end of 2020.

Considering the relative paucity of women in many STEMM fields prior to the COVID-19 pandemic, women are more likely to experience academic isolation, including limited access to mentors, sponsors, and role models that share gender, racial, or ethnic identities. Combining this reality with the physical isolation stipulated by public health responses to the COVID-19 pandemic,

women in STEMM were subject to increasing isolation within their fields, networks, and communities. Explicit attention to the early indicators of how the COVID-19 pandemic affected women in academic STEMM careers during 2020, as well as attention to crisis responses throughout history, may provide opportunities to mitigate some of the long-term effects and potentially develop a more resilient and equitable academic STEMM system.

MAJOR FINDINGS

Given the ongoing nature of the COVID-19 pandemic, it was not possible to fully understand the entirety of the short- or long-term implications of this global disruption on the careers of women in academic STEMM. Having gathered preliminary data and evidence available in 2020, the committee found that significant changes to women’s work-life boundaries and divisions of labor, careers, productivity, advancement, mentoring and networking relationships, and mental health and well-being have been observed. The following findings represent those aspects that the committee agreed have been substantiated by the preliminary data, evidence, and information gathered by the end of 2020. They are presented either as Established Research and Experiences from Previous Events or Impacts of the COVID-19 Pandemic during 2020 that parallel the topics as presented in the report.

Established Research and Experiences from Previous Events

___________________

1 This finding is primarily based on research on cisgender women and men.

Impacts of the COVID-19 Pandemic during 2020

RESEARCH QUESTIONS

While this report compiled much of the research, data, and evidence available in 2020 on the effects of the COVID-19 pandemic, future research is still needed to understand all the potential effects, especially any long-term implications. The research questions represent areas the committee identified for future research, rather than specific recommendations. They are presented in six categories that parallel the chapters of the report: Cross-Cutting Themes; Academic Productivity and Institutional Responses; Work-Life Boundaries and Gendered Divisions of Labor; Collaboration, Networking, and Professional Societies; Academic Leadership and Decision-Making; and Mental Health and Well-being. The committee hopes the report will be used as a basis for continued understanding of the impact of the COVID-19 pandemic in its entirety and as a reference for mitigating impacts of future disruptions that affect women in academic STEMM. The committee also hopes that these research questions may enable academic STEMM to emerge from the pandemic era a stronger, more equitable place for women. Therefore, the committee identifies two types of research questions in each category; listed first are those questions aimed at understanding the impacts of the disruptions from the COVID-19 pandemic, followed by those questions exploring the opportunities to help support the full participation of women in the future.

Cross-Cutting Themes

• What are the short- and long-term effects of the COVID-19 pandemic on the career trajectories, job stability, and leadership roles of women, particularly of Black women and other Women of Color? How do these effects vary across institutional characteristics, 2 discipline, and career stage?

2 Institutional characteristics include different institutional types (e.g., research university, liberal arts college, community college), locales (e.g., urban, rural), missions (e.g., Historically Black Colleges and Universities, Hispanic-Serving Institutions, Asian American/Native American/Pacific Islander-Serving Institutions, Tribal Colleges and Universities), and levels of resources.

• How did the confluence of structural racism, economic hardships, and environmental disruptions affect Women of Color during the COVID-19 pandemic? Specifically, how did the murder of George Floyd, Breonna Taylor, and other Black citizens impact Black women academics’ safety, ability to be productive, and mental health?
• How has the inclusion of women in leadership and other roles in the academy influenced the ability of institutions to respond to the confluence of major social crises during the COVID-19 pandemic?
• How can institutions build on the involvement women had across STEMM disciplines during the COVID-19 pandemic to increase the participation of women in STEMM and/or elevate and support women in their current STEMM-related positions?
• How can institutions adapt, leverage, and learn from approaches developed during 2020 to attend to challenges experienced by Women of Color in STEMM in the future?

Academic Productivity and Institutional Responses

• How did the institutional responses (e.g., policies, practices) that were outlined in the Major Findings impact women faculty across institutional characteristics and disciplines?
• What are the short- and long-term effects of faculty evaluation practices and extension policies implemented during the COVID-19 pandemic on the productivity and career trajectories of members of the academic STEMM workforce by gender?
• What adaptations did women use during the transition to online and hybrid teaching modes? How did these techniques and adaptations vary as a function of career stage and institutional characteristics?
• What are examples of institutional changes implemented in response to the COVID-19 pandemic that have the potential to reduce systemic barriers to participation and advancement that have historically been faced by academic women in STEMM, specifically Women of Color and other marginalized women in STEMM? How might positive institutional responses be leveraged to create a more resilient and responsive higher education ecosystem?
• How can or should funding arrangements be altered (e.g., changes in funding for research and/or mentorship programs) to support new ways of interaction for women in STEMM during times of disruption, such as the COVID-19 pandemic?

Work-Life Boundaries and Gendered Divisions of Labor

• How do different social identities (e.g., racial; socioeconomic status; culturally, ethnically, sexually, or gender diverse; immigration status; parents of young children and other caregivers; women without partners) influence the management of work-nonwork boundaries? How did this change during the COVID-19 pandemic?
• How have COVID-19 pandemic-related disruptions affected progress toward reducing the gender gap in academic STEMM labor-force participation? How does this differ for Women of Color or women with caregiving responsibilities?
• How can institutions account for the unique challenges of women faculty with parenthood and caregiving responsibilities when developing effective and equitable policies, practices, or programs?
• How might insights gained about work-life boundaries during the COVID-19 pandemic inform how institutions develop and implement supportive resources (e.g., reductions in workload, on-site childcare, flexible working options)?

Collaboration, Networking, and Professional Societies

• What were the short- and long-term effects of the COVID-19 pandemic-prompted switch from in-person conferences to virtual conferences on conference culture and climate, especially for women in STEMM?
• How will the increase in virtual conferences specifically affect women’s advancement and career trajectories? How will it affect women’s collaborations?
• How has the shift away from attending conferences and in-person networking changed longer-term mentoring and sponsoring relationships, particularly in terms of gender dynamics?
• How can institutions maximize the benefits of digitization and the increased use of technology observed during the COVID-19 pandemic to continue supporting women, especially marginalized women, by increasing accessibility, collaborations, mentorship, and learning?
• How can organizations that support, host, or facilitate online and virtual conferences and networking events (1) ensure open and fair access to participants who face different funding and time constraints; (2) foster virtual connections among peers, mentors, and sponsors; and (3) maintain an inclusive environment to scientists of all backgrounds?
• What policies, practices, or programs can be developed to help women in STEMM maintain a sense of support, structure, and stability during and after periods of disruption?

Academic Leadership and Decision-Making

• What specific interventions did colleges and universities initiate or prioritize to ensure that women were included in decision-making processes during responses to the COVID-19 pandemic?
• How effective were colleges and universities that prioritized equity-minded leadership, shared leadership, and crisis leadership styles at mitigating emerging and potential negative effects of the COVID-19 pandemic on women in their communities?
• What specific aspects of different leadership models translated to more effective strategies to advance women in STEMM, particularly during the COVID-19 pandemic?
• How can examples of intentional inclusion of women in decision-making processes during the COVID-19 pandemic be leveraged to develop the engagement of women as leaders at all levels of academic institutions?
• What are potential “top-down” structural changes in academia that can be implemented to mitigate the adverse effects of the COVID-19 pandemic or other disruptions?
• How can academic leadership, at all levels, more effectively support the mental health needs of women in STEMM?

Mental Health and Well-being

• What is the impact of the COVID-19 pandemic and institutional responses on the mental health and well-being of members of the academic STEMM workforce as a function of gender, race, and career stage?
• How are tools and diagnostic tests to measure aspects of wellbeing, including burnout and insomnia, used in academic settings? How does this change during times of increased stress, such as the COVID-19 pandemic?
• How might insights gained about mental health during the COVID-19 pandemic be used to inform preparedness for future disruptions?
• How can programs that focus on changes in biomarkers of stress and mood dysregulation, such as levels of sleep, activity, and texting patterns, be developed and implemented to better engage women in addressing their mental health?
• What are effective interventions to address the health of women academics in STEMM that specifically account for the effects of stress on women? What are effective interventions to mitigate the excessive levels of stress for Women of Color?

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The spring of 2020 marked a change in how almost everyone conducted their personal and professional lives, both within science, technology, engineering, mathematics, and medicine (STEMM) and beyond. The COVID-19 pandemic disrupted global scientific conferences and individual laboratories and required people to find space in their homes from which to work. It blurred the boundaries between work and non-work, infusing ambiguity into everyday activities. While adaptations that allowed people to connect became more common, the evidence available at the end of 2020 suggests that the disruptions caused by the COVID-19 pandemic endangered the engagement, experience, and retention of women in academic STEMM, and may roll back some of the achievement gains made by women in the academy to date.

The Impact of COVID-19 on the Careers of Women in Academic Sciences, Engineering, and Medicine identifies, names, and documents how the COVID-19 pandemic disrupted the careers of women in academic STEMM during the initial 9-month period since March 2020 and considers how these disruptions - both positive and negative - might shape future progress for women. This publication builds on the 2020 report Promising Practices for Addressing the Underrepresentation of Women in Science, Engineering, and Medicine to develop a comprehensive understanding of the nuanced ways these disruptions have manifested. The Impact of COVID-19 on the Careers of Women in Academic Sciences, Engineering, and Medicine will inform the academic community as it emerges from the pandemic to mitigate any long-term negative consequences for the continued advancement of women in the academic STEMM workforce and build on the adaptations and opportunities that have emerged.

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COVID-19 linked to higher diabetes risk, vaccination reduces impact

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In a recent study published in The Lancet Diabetes & Endocrinology , a group of researchers investigated the association between coronavirus disease 2019 (COVID-19) and the incidence of type 2, type 1, non-specific, and gestational diabetes, and the effect of COVID-19 vaccination.

Background  

At least 700 million people have been infected with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), with reports indicating a 30-50% excess incidence of type 2 diabetes post-infection, raising public health concerns. Three studies found no link between type 1 diabetes and SARS-CoV-2.

It remains unclear if excess diabetes is due to short-term hyperglycemia or long-term effects. Most studies examined diabetes incidence at fixed time points post-COVID-19. COVID-19 severity and vaccination likely influence outcomes, but only one study assessed vaccination's impact on post-COVID-19 diabetes. Further research is needed to understand long-term effects, vaccination impact, and underlying mechanisms.

About the study  

The present study analyzed data from individuals aged 18 or older registered with primary care practices using TPP software in England within the Open Secure Analytics Framework for Electronic Health Records (OpenSAFELY) platform.

This included primary care records from 24 million people, linked to SARS-CoV-2 testing data, National Health Service (NHS) hospital admissions, and death registry records, alongside COVID-19 vaccination data. The United Kingdom (UK) COVID-19 vaccine rollout began on December 8, 2020, with eligibility based on clinical vulnerability, age, and occupation, making all adults eligible by June 18, 2021.

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Three cohorts were defined: pre-vaccination (follow-up from January 1, 2020, to December 14, 2021), vaccinated (follow-up starting two weeks after the second vaccination), and unvaccinated (starting 12 weeks after vaccination eligibility without receiving the vaccine).

Eligible participants were registered for at least six months before the baseline, were aged 18-110 years, and had available data for region, sex, and area deprivation. Those with prior SARS-CoV-2 infection or COVID-19 diagnosis were excluded.

The study assessed associations between COVID-19 and diabetes diagnoses, examining variations up to two years post-diagnosis by diabetes type, vaccination status, and COVID-19 severity. Statistical analyses estimated incidence rates and hazard ratios, with subgroup analyses by demographics and comorbidities. Data was sorted and analyzed using Python and R, and ethical approval was obtained.

Study results 

Of the 33,404,025 individuals in OpenSAFELY-TPP eligible for the pre-vaccination cohort, 16,699,943 met the study inclusion criteria. Among the 33,023,366 participants alive at the start of the delta era, 12,279,699 were included in the vaccinated cohort and 3,076,951 in the unvaccinated cohort. Follow-up periods were January 1, 2020, to December 14, 2021, for the pre-vaccination cohort and June 1 to December 14, 2021, for the vaccinated and unvaccinated cohorts.

In the pre-vaccination cohort, 916,802 (5.5%) were diagnosed with COVID-19. In the vaccinated cohort, 774,475 (6.3%) had COVID-19, and in the unvaccinated cohort, 153,941 (5.0%) were diagnosed. Mortality within 28 days of diagnosis was 0.1% in the pre-vaccination cohort, 0.2% in the vaccinated cohort, and 0.3% in the unvaccinated cohort.

The unvaccinated cohort was younger, had a higher proportion of men, more individuals from South Asian and Black ethnic backgrounds, and more from the most deprived backgrounds compared to the vaccinated cohort. The median follow-up times were 714 days for the pre-vaccination cohort, 190 days for the vaccinated cohort, and 126 days for the unvaccinated cohort.

During the study, 145,533 people were diagnosed with type 2 diabetes in the pre-vaccination cohort, meanwhile 34,365 in the vaccinated cohort, and 2,781 in the unvaccinated cohort. Type 1 diabetes diagnoses were 2,619 in the vaccinated cohort, 16,047 in the pre-vaccination cohort, and 747 in the unvaccinated cohort.

Incidence rates for type 2 diabetes were higher in the vaccinated cohort compared to the unvaccinated cohort. Age-sex-standardized incidence rates for diabetes post-COVID-19 diagnosis were higher in the unvaccinated cohort than in the pre-vaccination and vaccinated cohorts. Diabetes incidence was greater in those hospitalized with COVID-19.

In the pre-vaccination cohort, 145,323 type 2 diabetes diagnoses had follow-up data, with 61.6% being persistent. Persistent diabetes was slightly higher after hospitalization with COVID-19. Adjusted hazard ratios (aHRs) showed increased type 2 diabetes incidence post-COVID-19, especially in the unvaccinated cohort. In the pre-vaccination cohort, type 2 diabetes incidence remained elevated 53-102 weeks post-diagnosis.

Type 1 diabetes incidence was higher during the first four weeks post-COVID-19 diagnosis across all cohorts, with higher aHRs in the pre-vaccination and unvaccinated cohorts. The pre-vaccination cohort showed elevated type 1 diabetes incidence up to 52 weeks post-diagnosis. No significant increase in gestational diabetes post-COVID-19 was observed. The incidence of other diabetes types was also elevated, particularly after hospitalization with COVID-19. 

Conclusions 

To summarize, in the cohort exposed to COVID-19 before vaccines, type 2 diabetes incidence was four times higher during the first four weeks post-diagnosis and remained elevated by 64% in the second year, especially in hospitalized cases.

The increase was significantly lower in vaccinated individuals (1.6 vs. 8.8 times higher). Type 1 diabetes incidence was elevated only in the first year post-diagnosis, with no apparent increase in gestational diabetes.

This study highlights the importance of vaccination and routine diabetes testing after severe COVID-19 to manage long-term health impacts. Its findings are supported by a large, representative UK population sample.

• Taylor K, Eastwood S, Walker V, et al. (2024). Incidence of diabetes after SARS-CoV-2 infection in England and the implications of COVID-19 vaccination: a retrospective cohort study of 16 million people, The Lancet Diabetes & Endocrinology . doi: 10.1016/S2213-8587(24)00159-1. https://www.thelancet.com/journals/landia/article/PIIS2213-8587(24)00159-1/fulltext  

Posted in: Medical Science News | Medical Research News | Medical Condition News | Disease/Infection News

Tags: Coronavirus , Coronavirus Disease COVID-19 , covid-19 , Diabetes , Endocrinology , Gestational Diabetes , Hospital , Hyperglycemia , Mortality , Primary Care , Public Health , Research , Respiratory , SARS , SARS-CoV-2 , Severe Acute Respiratory , Severe Acute Respiratory Syndrome , Software , Syndrome , Type 1 Diabetes , Type 2 Diabetes , Vaccine

Vijay Kumar Malesu

Vijay holds a Ph.D. in Biotechnology and possesses a deep passion for microbiology. His academic journey has allowed him to delve deeper into understanding the intricate world of microorganisms. Through his research and studies, he has gained expertise in various aspects of microbiology, which includes microbial genetics, microbial physiology, and microbial ecology. Vijay has six years of scientific research experience at renowned research institutes such as the Indian Council for Agricultural Research and KIIT University. He has worked on diverse projects in microbiology, biopolymers, and drug delivery. His contributions to these areas have provided him with a comprehensive understanding of the subject matter and the ability to tackle complex research challenges.    

Please use one of the following formats to cite this article in your essay, paper or report:

Kumar Malesu, Vijay. (2024, August 07). COVID-19 linked to higher diabetes risk, vaccination reduces impact. News-Medical. Retrieved on August 17, 2024 from https://www.news-medical.net/news/20240807/COVID-19-linked-to-higher-diabetes-risk-vaccination-reduces-impact.aspx.

Kumar Malesu, Vijay. "COVID-19 linked to higher diabetes risk, vaccination reduces impact". News-Medical . 17 August 2024. <https://www.news-medical.net/news/20240807/COVID-19-linked-to-higher-diabetes-risk-vaccination-reduces-impact.aspx>.

Kumar Malesu, Vijay. "COVID-19 linked to higher diabetes risk, vaccination reduces impact". News-Medical. https://www.news-medical.net/news/20240807/COVID-19-linked-to-higher-diabetes-risk-vaccination-reduces-impact.aspx. (accessed August 17, 2024).

Kumar Malesu, Vijay. 2024. COVID-19 linked to higher diabetes risk, vaccination reduces impact . News-Medical, viewed 17 August 2024, https://www.news-medical.net/news/20240807/COVID-19-linked-to-higher-diabetes-risk-vaccination-reduces-impact.aspx.

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The impact of covid-19 on construction project performance: a case study in pakistan.

1. Introduction

1.1. impact of covid-19 on the construction industry, 1.2. covid-19 and the pakistan construction industry, 2. materials and methods, 2.1. identification of factors, 2.2. development of instrument survey.

2.3. Demographics of Projects

2.4. demographics of respondents, 3.1. material and equipment, 3.2. human resource, 3.3. occupational health and safety, 3.4. financial and contracts, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest, appendix a. open-ended questions and consent form.

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Bukhari, S.R.A.; Nasir, A.R.; Greco, R.; Mollo, L. The Impact of COVID-19 on Construction Project Performance: A Case Study in Pakistan. COVID 2024 , 4 , 1253-1271. https://doi.org/10.3390/covid4080090

Bukhari SRA, Nasir AR, Greco R, Mollo L. The Impact of COVID-19 on Construction Project Performance: A Case Study in Pakistan. COVID . 2024; 4(8):1253-1271. https://doi.org/10.3390/covid4080090

Bukhari, Syed Rafay Ali, Abdur Rehman Nasir, Roberto Greco, and Luigi Mollo. 2024. "The Impact of COVID-19 on Construction Project Performance: A Case Study in Pakistan" COVID 4, no. 8: 1253-1271. https://doi.org/10.3390/covid4080090

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