online education essay due to covid 19

Remote Learning During COVID-19: Lessons from Today, Principles for Tomorrow

"Remote Learning During the Global School Lockdown: Multi-Country Lessons” and “Remote Learning During COVID-19: Lessons from Today, Principles for Tomorrow"

WHY A TWIN REPORT ON THE IMPACT OF COVID IN EDUCATION?

The COVID-19 pandemic has disrupted education in over 150 countries and affected 1.6 billion students. In response, many countries implemented some form of remote learning. The education response during the early phase of COVID-19 focused on implementing remote learning modalities as an emergency response. These were intended to reach all students but were not always successful. As the pandemic has evolved, so too have education responses. Schools are now partially or fully open in many jurisdictions.

A complete understanding of the short-, medium- and long-term implications of this crisis is still forming. The twin reports analyze how this crisis has amplified inequalities and also document a unique opportunity to reimagine the traditional model of school-based learning.

The reports were developed at different times during the pandemic and are complementary:

The first one follows a qualitative research approach to document the opinions of education experts regarding the effectiveness of remote and remedial learning programs implemented across 17 countries. DOWNLOAD THE FULL REPORT

WHAT ARE THE LESSONS LEARNED OF THE TWIN REPORTS?

• Availability of technology is a necessary but not sufficient condition for effective remote learning: EdTech has been key to keep learning despite the school lockdown, opening new opportunities for delivering education at a scale. However, the impact of technology on education remains a challenge.
• Teachers are more critical than ever: Regardless of the learning modality and available technology, teachers play a critical role. Regular and effective pre-service and on-going teacher professional development is key. Support to develop digital and pedagogical tools to teach effectively both in remote and in-person settings.
• Education is an intense human interaction endeavor: For remote learning to be successful it needs to allow for meaningful two-way interaction between students and their teachers; such interactions can be enabled by using the most appropriate technology for the local context.
• Parents as key partners of teachers: Parent’s involvement has played an equalizing role mitigating some of the limitations of remote learning. As countries transition to a more consistently blended learning model, it is necessary to prioritize strategies that provide guidance to parents and equip them with the tools required to help them support students.
• Leverage on a dynamic ecosystem of collaboration: Ministries of Education need to work in close coordination with other entities working in education (multi-lateral, public, private, academic) to effectively orchestrate different players and to secure the quality of the overall learning experience.
• FULL REPORT
• Interactive document
• Understanding the Effectiveness of Remote and Remedial Learning Programs: Two New Reports
• Understanding the Perceived Effectiveness of Remote Learning Solutions: Lessons from 18 Countries
• Five lessons from remote learning during COVID-19
• Launch of the Twin Reports on Remote Learning during COVID-19: Lessons for today, principles for tomorrow

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• Published: 25 March 2023

The impact of the first wave of COVID-19 on students’ attainment, analysed by IRT modelling method

• Rita Takács   ORCID: orcid.org/0000-0002-0314-4179 1 ,
• Szabolcs Takács   ORCID: orcid.org/0000-0002-9128-9019 2 , 3 ,
• Judit T. Kárász   ORCID: orcid.org/0000-0002-6198-482X 4 , 5 ,
• Attila Oláh 6 , 7 &
• Zoltán Horváth 1  

Humanities and Social Sciences Communications volume  10 , Article number:  127 ( 2023 ) Cite this article

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Universities around the world were closed for several months to slow down the spread of the COVID-19 pandemic. During this crisis, a tremendous amount of effort was made to use online education to support the teaching and learning process. The COVID-19 pandemic gave us a profound insight into how online education can radically affect students and how students adapt to new challenges. The question is how switching to online education affected dropout? This study shows the results of a research project clarifying the impact of the transition to online courses on dropouts. The data analysed are from a large public university in Europe where online education was introduced in March 2020. This study compares the academic progress of students newly enroled in 2018 and 2019 using IRT modelling. The results show that (1) this period did not contribute significantly to the increase in dropout, and we managed to retain our students.(2) Subjects became more achievable during online education, and students with less ability were also able to pass their exams. (3) Students who participated in online education reported lower average grade points than those who participated in on-campus education. Consequently, on-campus students could win better scholarships because of better grades than students who participated in online education. Analysing students’ results could help (1) resolve management issues regarding scholarship problems and (2) administrators develop programmes to increase retention in online education.

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Introduction.

During the spread of the COVID-19 pandemic, several countries closed their university buildings and switched to online education. Some opinions suggest that online education had a negative effect on dropouts because of several factors, e.g., lack of social connections, poor contact with teachers. In bachelor’s programmes—like university courses in computer science—where dropout rates were high prior to the pandemic, many questions were raised about the impact of the transition to online education.

This study focuses on the effects of the first wave of the COVID-19 pandemic on students’ dropouts and performance in Hungary. Although the manuscript addresses academic dropout, other issues such as inequality or accessibility were also covered in the research.

Theoretical background

Educational theory about student dropout in higher education.

Tinto ( 1975 ) was the first researcher who analysed the dropout phenomenon and invented the interactional theory of student persistence in higher education. He ( 2012 ) highlighted the interactions between the student and the institution regarding how well they fit in academically and socially. Interactional theories suggest that students’ personal characteristics, traits, experience, and commitment can have an effect on students’ persistence (Pascarella and Terenzini, 1983 ; Terenzini and Reason, 2005 ; Reason, 2009 ). Braxton and Hirschy ( 2004 ) also emphasized the need for community on campus as a help of social integration to develop relationships between peers because interactions with other students and faculty members crucially determine whether students persist and continue their studies or leave.

The student dropout rate has been a crucial issue in higher education in the last two decades. Attrition has serious consequences on the individual (e.g., Nagrecha et al., 2017 ) at both economic (Di Pietro, 2006 ; Belloc et al., 2011 ) and educational (Cabrera et al., 2006 ) levels. As a worldwide phenomenon, it draws the attention of policy-makers, stake-holders and academics to the necessity of seeking solutions. The dropout crisis requires complex intervention programmes for encouraging students in order to complete their studies. Addressing such a dropout crisis requires an actionable interdisciplinary movement based on partnerships among stake-holders and academics.

According to Vision 2030 studies published by the European Union, education is vital for economic development because it has a direct influence on entrepreneurship and productivity growth; at the same time, it increases employment opportunities and women empowerment. Education helps to reduce unemployment and enhance students’ abilities and skills that will be needed in the labour market. Due to students’ high attrition, the economy also suffers because experts with a degree usually contribute more to the GDP than people without (Whittle and Rampton, 2020 ).

A comparative analysis of past studies has been conducted in order to identify various causes of students’ dropout. Students’ performance after the first academic year is a topic of significant interest: the lack of students' engagement in academic life and their unpreparedness are mainly responsible for dropout after the first highly crucial period. However, further studies are necessary to better understand this phenomenon.

The characteristics of online education and its effect on dropout

Online education had already existed before the COVID-19 pandemic and had had a vast literature because online courses had been playing an important role in higher education. Online education has its own benefits, e.g., it enables students to work from the comfort of their homes with more convenient, accessible materials. In recent years, numerous investigations have been performed on how to increase the motivation of students by making them feel engaged during the learning processes (Molins-Ruano et al., 2014 ; Jovanovic et al., 2019 ). The other benefit is “humanizing”, which is an academic strategy that looks for solutions to improve equity gaps by recognizing the fact that learning situations are not the same for everyone. The aim of humanizing education is to remove the affective and cognitive barriers which appear during online learning and to provide a technique in higher education towards a more equitable future in which the success of all students is supported (Pacansky-Brock and Vincent-Layton, 2020 ). Humanizing online STEM courses has specific significance because creating such academic pathways can especially help the graduation of vulnerable, for example, non-traditional students. The definition of a non-traditional student belongs to Bean and Metzner ( 1985 ), who distinguished students by different characteristics. Non-traditional students are not on-campus students (but they can participate in online education), who are usually aged 24 years or older, and dominantly have a job and/or a family. Non-traditional students have less interaction with other participants in education, and they are much more influenced by other factors, e.g., family or other external responsibilities. Financial factors, family attitudes and external incentives can also influence dropout. The dropout model for non-traditional university students highlights that underperforming students are likely to leave the institution. Carr ( 2000 ) (in Rovai, 2003 ) noticed that persistence in online courses is regularly 10–20% lower than in on-campus courses. The dropout rate differs from institution to institution: some reports claim that 80% of students graduated, whereas other findings show that less than 50% of students completed their courses. Humanizing recognizes that engagement and accomplishment are the key factors in students’ success. Engagement and achievement are social constructs created through students’ experience. Teachers can help students to socialize and adapt to the academic environment by using humanizing practices like a liquid syllabus. Stommel ( 2013 ) also considers that hybrid pedagogy is a useful tool in order to support students’ learning because it helps teachers to implement new learning activities and facilitate collaboration among students.

Despite the various benefits that online education has, the success of students depends on the student’s capacity to independently and effectively engage in the learning process (Wang et al., 2013 ). Online learners are required to be more autonomous, as the exceptional nature of online settings relies on self-directed learning (Serdyukov and Hill, 2013 ). It is therefore especially critical that online learners, compared to their conventional classroom peers, have the self-generated capacity to control and manage their learning activities.

Online education also needs extra attention because the dropout rate is high in online university programmes. Students in online courses are more likely to drop out (Patterson and McFadden, 2009 ; in Nistor and Neubauer, 2010 ). Numerous studies reported much higher dropout rates than in the case of on-campus courses (Willging and Johnson, 2019 ; Levy, 2007 ; Morris et al., 2005 ; Patterson and McFadden, 2009 ; in Nistor and Neubauer, 2010 ). Many factors that lead to dropout were examined in the past. During online courses, students are less likely to form communities or study groups and the lack of learning support can lead to isolation. Consequently, demotivated students who were dedicated to their chosen major, in the beginning, may decide to drop out. Fortunately, there are different ways to support students who study in an online setting depending on their various psychological attributes. These psychological attributes that are connected to dropout have already been examined. One of the most noticeable hypothetical models of university persistence in online education was proposed by Rovai ( 2003 ). He claims that dropout depends on students’ characteristics e.g., learning style, socioeconomic status, studying skills, etc. Besides these factors, the method of education also has an impact on students’ decisions on whether they complete the course or drop out.

It is vital to distinguish the online education that was introduced as a consequence of the COVID-19 lockdown, when universities were forced to move their education to fully online platforms because online education had already existed in some educational institutions.

The COVID-19 pandemic and its effect on education: Inequalities in home learning and colleges’ provision of distance teaching during school closure of the COVID-19 lockdown

The lives of millions of college students were affected not only by the health and economic implications of the COVID-19 pandemic but also by the closure of educational institutions. Home and academic environments were interlaced, and most institutions were caught unprepared. In this article, we examine the effects of the transition to online learning in areas such as academic attainment.

There are several debates on the effectiveness of moving to online education. Since currently there is little literature about the COVID-19 pandemic in relation to how it affects dropouts at universities, it is worth discussing it in order to have an overview of recent studies on students’ performance. The learning environment changed radically during the first wave of the pandemic in the spring semester of 2020. The transition to home learning and teaching in such a short time without any warning or preparation raised concerns and became the focus of attention for researchers, teachers, policymakers, and all those interested in the educational welfare of students.

A potential learning loss was anticipated, possibly affecting students’ cognitive gains in the long term (Andrew et al., 2020 ; Bayrakdar and Guveli, 2020 ; Brown et al., 2020 ); in fact, an increasing number of studies suggested that the lockdown might have far-reaching academic consequences (Bol, 2020 ). In general, results suggest that students’ motivation was substantially affected by the COVID-19 pandemic and that academic and relational changes were the most notable sources of stress on both the students’ side (e.g., Rahiem, 2021 ) and the teachers’ side (e.g., Abilleira et al., 2021 ; Daumiller et al., 2021 ). Engzell et al. ( 2021 ) examined nearly 350,000 students’ academic performance before and after the first wave of the pandemic in the Netherlands. Their results suggest that students made very little development while learning from home. Closures also had a substantial effect on students’ sense of belonging and self-efficacy. Academic knowledge loss could be even more severe in countries with less advanced infrastructure or a longer period of college closures (OECD, 2020 ).

Many researchers started to examine the effects of the COVID-19 pandemic on university students’ mental health and academic performance. Clark et al. ( 2021 ) claim that university students are increasingly considered a vulnerable population, as they experience extremely high levels of stress. They draw attention to the fact that students might suffer more from learning difficulties. Daniels et al. ( 2021 ) used a single survey to collect retrospective self-report data from Canadian undergraduate students ( n  = 98) about their motivation, engagement and perceptions of success and cheating before COVID-19, which shows that students’ achievements, goals, engagement and perception of success all significantly decreased, while their perception of cheating increased (Daniels et al., 2021 ). Other studies claim that during the COVID-19 pandemic, students were more engaged in studying and had higher perceptions of success. Studies also show that teachers’ strategies changed as well because of the lack of interaction between teachers and students, which led to the fact that students experienced more stress and were more likely to have difficulties in following the material presented and it could be one of the reasons for poor academic performance. Mendoza et al. ( 2021 ) investigated the relationships between anxiety and students’ performance during the first wave of the pandemic among college students. Anxiety regarding learning mathematics was measured among mathematics students studying at the Universidad Nacional de Chimborazo (UNACH) during the autumn semester of the academic year 2020. The total sample contained 120 students, who were studying the subject of mathematics at different levels. The results showed that there were statistically significant differences in the understanding of the contents presented by the teachers in a virtual way. During the COVID-19 pandemic the levels of mathematical anxiety increased. Teaching mathematics at university in an online format requires good quality digital connection and time-limited submission of assignments. This study draws attention to the negative result of the pandemic, i.e. the levels of anxiety might be greater during online education and not only in mathematics education but also in other subjects. Thus it could have an effect on students’ academic performance. However, the results are contradictory to what Said ( 2021 ) found, i.e. there was no difference in students’ performance before and during the COVID-19 pandemic. In their empirical study, they investigated the effect of the shift from face-to-face to online distance learning at one of the universities in Egypt. They compared the grades of 376 business students who participated in a face-to-face course in spring 2019 and those of 372 students who participated in the same course fully online in spring 2020 during the lockdown. A T -test was conducted to compare the grades of quizzes, coursework, and final exams of the two groups. The results suggested that there was no statistically significant difference. Another interesting result was that in some cases students had a better performance during the COVID-19 pandemic. At a large public university in Spain, Iglesias-Pradas et al. ( 2021 ) analysed the following instruction-related variables: class size, synchronous/asynchronous delivery of classes, and the use of digital supporting technologies on students’ academic performance. The research compared the academic results of the students during the COVID-19 pandemic with those of previous years. Using quantitative data from academic records across all ( n  = 43) courses of a bachelor’s degree programme, the study showed an increase in students’ academic performance during the sudden shift to online education. Gonzalez et al. ( 2020 ) had similar results. Their research group analysed the effects of COVID-19 on the autonomous learning performance of students. 458 students participated in their studies. In the control group, students started their studies in 2017 and 2018, while in the experimental group, students started in 2019. The results showed that there was a significant positive effect of the COVID-19 lockdown on students’ performance: students had changed their learning strategies and improved their efficiency by studying more continuously. Yu et al. ( 2021 ) found similar results. They used administrative data from students’ grade tracking systems and found that the causal effects of online education on students’ exam performance were positive in a Chinese middle school. Taking a difference-in-differences approach, they found that receiving online education during the COVID-19 lockdown improved students’ academic results by 0.22 of a standard deviation (Yu et al., 2021 ).

Currently, there is little literature about COVID-19 in relation to how it affects students’ performance at universities, so it is worth discussing this aspect as well.

Teachers’ approach to their grading strategies and shift to online education during the COVID-19 lockdown

There is a vast literature on the limits of the capacities and challenges of online education (Davis et al., 2019 ; Dumford and Miller, 2018 ; Palvia et al., 2018 ). The lockdown during the COVID-19 pandemic created new challenges for teachers all over the world and called for innovative teaching techniques (Adedoyin and Soykan, 2020 ; Gamage et al., 2020 ; Paudel, 2020 ; Peimani and Kamalipour, 2021 ; Rapanta et al., 2020 ; Watermeyer et al., 2021 ). These changes had undoubtedly profound impacts on the academic discourse and everyday practices of teaching. Teachers’ motivations for maintaining effective online teaching during the lockdown were diverse and complex, and therefore, learning outcomes were difficult to be guaranteed. Yu et al. ( 2021 ) examined how innovative teaching could be continued during the COVID-19 pandemic, particularly by learning domain-specific knowledge and skills. The results confirmed that during the lockdown teachers who had studied online teaching methods improved their teaching skills and ICT (information and communication technology) efficacy.

Burgess and Sievertsen ( 2020 ) claim that due to the COVID-19 lockdown, educational institutions might cause major interruptions in students’ learning process. Disruption appeared not only in elaborating new knowledge but also in assessment. Given the proof of the significance of exams and tests for learning, educators had to consider postponing rather than renounce assessments. Akar and Coskun ( 2020 ) found that innovative teaching had a slight but positive relationship with creativity. From their point of view, it was not necessarily a consequence of shifting offline teaching to online platforms. Innovative teaching and digital technology were not granted and their impact on student’s performance or teachers’ grading practices is still unclear. The present research aimed to analyse students’ attainment during the COVID-19 pandemic by using student performance data. We focused on the relationship between participation in online courses and dropout decisions, which is connected to teachers’ grading. Examining how grades changed during the lockdown could give us an interesting insight into the educational inequality caused by online education regarding the scholarship system based on student’s grades.

Research questions

We know very little about the effects of transitioning to online education on student dropout and teachers’ grading practices. Even less information is available on the relationship between COVID-19 and dropout, so it is worth a discussion due to the existing controversial and interesting studies on students’ performance. This article gives a suggestion on how the scholarship system could be changed and how we could avoid inequality caused by online education. There is a scholarship system in Hungary that provides financial support to full-time programme students, based on their academic achievement.

Another issue we discuss in this article is dropping out from university programmes, which is a crucial issue worldwide. Between 2010 and 2016 at a large public university in Europe (over 30,000 students) the overall attrition rate is 30%, with the Faculty of Informatics having the worst results (60%) but nowadays these figures are more promising (30|40%). These days at least 800,000 computer scientists may be needed in Europe (Europa.eu, 2015 ), but it seems to be a worldwide issue (Borzovs et al., 2015 ; Ohland et al., 2008 ) to retain students.

This study focuses on the effects of the first wave of the COVID-19 pandemic on students’ dropout and performance in Hungary. Although the manuscript addresses academic dropout, other issues such as inequality or accessibility are also covered in the research. The aim of the paper is therefore to investigate the following questions:

It is inconclusive whether the COVID-19 pandemic had negative effects on students’ performance, which is why we claim that

Hypothesis 1: There is a significant difference in grade point averages between students who participated in online education and those in on-campus education in the second semester of their studies.

Academic achievement (in both traditional and online learning settings) can be measured by accomplishing a specific result in an online assignment and is commonly expressed in terms of a grade point average (GPA; Lounsbury et al., 2005 ; Richardson et al., 2012 ; Wang, 2010 ). According to meta-analyses, GPA is one of the best predictors of dropout (Richardson et al., 2012 ; Broadbent and Poon, 2015 ).

Hypothesis 2: In some subjects (Basic Mathematics practice, Programming, Imperative Programming lecture + practice, Functional Programming, Object-oriented Programming practice + lecture, Algorithms and Data Structures lecture + practice, Discrete Mathematics practice and Analysis practice), it was easier to obtain a passing grade in online education.

Hypothesis 3: More of the students who participated in online education dropped out than those who received on-campus education.

Difficulty and differential analysis of subjects

In the examined higher education system, a BSc programme has six semesters and every subject is graded on a five-point scale, where 1 means fail, and grades from 2 to 5 mean pass, with 5 being the best grade. In the analysis only the final grades were counted in each subject. It is important to see that in order to achieve better grades (or obtain sufficient knowledge), a subject really needs differentiation. It is worth examining the subjects of the various courses because—although there are grades—there is some kind of expected knowledge or skill that the subject should measure. Students are expected to develop these competencies or at least reach an expected level by the end of the semester. To find out whether this kind of competency actually exists (and was developed during online education) and whether the subjects measure this kind of competency, Item Response Theory (IRT) analysis was used to examine the subjects included in the computer science BSc programme. The aim of IRT analysis modelling is to bring the difficulty of the subjects and the ability of the students to the same scale (GRM, Forero and Maydeu-Olivares, 2009 ; Rasch, 1960 ). We had already successfully applied a special IRT model in order to analyse the effects of a student retention programme. In order to prevent student dropout, in a large public university in Europe, a prevention and promotion programme was added to the bachelor’s programme and an education reform was also implemented. In most education systems students have to collect 30 credits per semester by successfully completing 8|10 subjects. We conducted an analysis using data science techniques and the most difficult subjects were identified. As a result, harder subjects were removed, and more introductory courses were built into the curriculum of the first year. A further action—as an intervention—was added to a computer science degree programme: all theoretical lectures became compulsory to attend. According to the results, the dropout level decreased by 28%. The most important benefit of the education reform was that most subjects had become accomplishable (Takács et al., 2021 ). Footnote 1

Hypothesis 1 claims that the online transition due to COVID-19 during the second semester of the 2019 academic year did not result in a change in the requirement system of the subjects. Hypothesis 2 claims that essentially the same expectations were formulated by teachers. In contrast, the way teachers evaluate students necessarily changed. A subject with a given difficulty could be passed by a student with the same ability level with a given probability. Obviously, all subjects that had been less difficult were more likely to be correctly passed than more difficult subjects. The analysis was performed using the IRT, based on the STATA15 software package.

In the study, 862 students were involved in the bachelor’s computer science programme. There were 438 (415) students who started on-campus education in 2018 and 447 students who started on-campus education in 2019, but from March 2020 they participated in online education (Table 1 ). Table 1 shows the result of Hypothesis 1: The grade point average of students who participated in online education (2.5) was lower than that of students who participated in on-campus education (3.3). Table 1 also shows that 447 students participated in online education and only 19 dropped out; 438 students started on-campus education and 50 dropped out. We can conclude that there was no significant difference between students’ dropping out who participated in online education and those who received on-campus education (Hypothesis 3). Note: We can conclude that the grade point average of students who participated in online education (2.5) was lower than that of students who participated in on-campus education (3.3) (Hypothesis 1). On the other hand, there was no significant difference between the drop-out rate of students’ who participated in online education and that of those who received on-campus education (Hypothesis 3). These case numbers make it unnecessary to apply any statistical evidence because the result is obvious.

The subjects were examined by fitting a 2-parameter IRT model to them (scale 1–5 with grades, assuming an ordinal model using the STATA15 programme). ‘Grades’ mean the final grade of the subjects. The STATA15.0 software package was used for the analysis, and the Graded Response Model version of the Ordered item models was chosen from the IRT procedures (GRM; Forero and Maydeu-Olivares, 2009 ).

During the procedure, we examined two parameters: the difficulty of the items and the slope. We took into account those subjects for which the subject matter of the subject remained the same over the years, or the exams did not change substantially (exam grade, according to the same assessment criteria). However, it is important to note that obviously, not the same students completed the assignments each year.

The study involved the following subjects (only professional subjects were considered):

Mathematical Foundations

Programming

Computer Systems lecture+practice

Imperative Programming

Functional Programming

Object-oriented Programming lecture + practice

Algorithms and Data Structures I. lecture

Algorithms and Data Structures I. practice

Discrete Mathematics I. lecture

Discrete Mathematics I. practice

Analysis I. L

Analysis I. P

Examination of slope and difficulty coefficients

In this section, we examine Table 2 . As a first step, it is crucial to understand the slope indices of the given objects in different years, whether they change from one year to another. Table 2 shows the result of Hypothesis 2: In most subjects (Basic Mathematics practice, Programming, Imperative Programming lecture + practice, Functional Programming, Object-oriented Programming practice+lecture, Algorithms and Data Structures lecture + practice, Discrete Mathematics practice, and Analysis practice), it was easier to obtain a passing grade in online education.

Two parametric procedures were applied: each subject has a difficulty index and a slope.

While if the student’s ability falls short of the difficulty, the denominator of the fraction will increase, so the probability that the student will be able to pass the exam will increase—they will earn a good grade (Fig. 1 ).

Difficulty levels of the subjects in 2018 and 2019 academic year.

Instead of introducing the whole subject network, we introduce a typical subject that was analysed using the IRT. The analyses of the subject of Discrete Mathematics enable us to adequately illustrate the classic phenomenon that arose. The complete analysis of the subjects can be found in Table 2 .

The period before 2019 and after 2019 are shown separately in the table, as at the beginning of 2020 the lockdown took place when online education was introduced to all students so it had an impact on academic achievement. We presupposed that it had manifested itself in the subjects’ completing difficulty and in their ability to differentiate.

Discrete mathematics I. practice

As far as the Discrete Mathematics subject is regarded, we can observe a slope of high value above 3 (sometimes 4) before and after 2019, which means that the subject had strong differentiating abilities both before and after the COVID-19 pandemic.

There is a debate in the literature on how the performance of students changed during online education. Whereas Said ( 2021 ) found no difference in students’ performance before and during the COVID-19 pandemic, the study by Iglesias-Pradas et al. ( 2021 ) showed an increase in students’ academic performance in distance education. Gonzalez et al. ( 2020 ) predicted better results during online education than in the case of on-campus education. This study partly confirmed their result because more students tried taking the exams. However, they could not perform better as predicted by Gonzalez et al. ( 2020 ) because among computer science students those who participated in online education obtained lower grade point averages than those who participated in on-campus education. According to our results, grade point averages differed substantially between the two examined groups (Hypothesis 1). It can be seen that there are no significant differences in the study groups in terms of dropout after the first year of studies, and the number of students affected was not substantially higher/lower. There are no significant differences in dropout rates between students participating in on-campus or online education (Hypothesis 3).

The result above is crucial; however, the implications and prospective steps based on this result are even more important.

It can be seen that with the introduction of online education, more teaching and learning strategies became available for certain subjects. Teachers’ grading strategies as well as their intentions when giving grades can be assumed as the possible reasons behind the grades. These strategies on both sides (teachers’ and students’) may have appeared during online education.

There were basically two types of changes regarding the grades for the different subjects:

The difficulty associated with the particular grade of the subject in online education decreased for each value on a scale of 1–5 for a given subject (Hypothesis 2). This means that even failing (grade 1) was easier (students preferred to try the exam even if they were unprepared), or even obtaining other passing grades was easier, too. It should be noted that the examined phenomenon cannot have a negative slope (typically not 0), because a slope of 0 means that there is ½ of a probability (regardless of ability) that a student passes a given exam. Fortunately, this is not the case, so we can assume that all slopes are positive.

(a) Behind this strategy, in the case of grade 1, it can be assumed that in online education students’ general strategy was to register for the exam and try it even if unprepared in contrast to the on-campus student who would not take the exam if s/he was unprepared.

(b) It seems that it became easier to obtain a passing grade. Behind this phenomenon, strategies can be assumed from both faculty members' and students’ sides. In case of failing the exam, it makes no sense to talk about the strategy of the teacher, because the teacher was more likely to give a passing grade or even a better grade for less knowledge. In general, the thresholds for obtaining the grade were lower in all cases. This could have been illustrated by the following subjects: Basic Mathematics practice, Programming, Imperative Programming lecture + practice, Functional Programming, Object-oriented Programming practice + lecture, Algorithms and Data Structures lecture + practice, Discrete Mathematics practice and Analysis practice.

Analysing further the subjects by IRT modelling, we saw that it was easier to obtain lower grades (grades 1, 2 and 3). However, in the case grade 4 or 5, it appears that it was more difficult to obtain them due to the prevalence of the higher requirements of the subjects.

(a) The insufficient grades’ (i.e. grade 1) lower level of difficulty (shown by the IRT model) clearly showed that there was no substantial difference in this respect compared to obtaining insufficient grades during the on-campus or online education period.

(b) The results showed that obtaining good grades (4 or 5) became more difficult during online education. It can be assumed that students participating in online education require some kind of help from education management in order to compensate for the disadvantages posed by distance learning because they got worse grades and worse average grade points as compared to on-campus students.

In the following, we examine what strategies faculty members and students may apply considering the difficulty of each grade of the subjects (left column of Table 2 ) showed a decreasing trend.

From the students’ point of view, isolation could result in students being involved in studying more effectively. Consequently, the time spent on the elaboration of the subjects may increase (Wang et al., 2013 ) compared to in-class education and by using available materials, textbooks, practice assignments, students could devote extra energy to subjects, which may result in better exam grades.

From the teachers’ point of view, teachers might want to offer some ‘compensation’ at exams due to non-traditional teaching. In light of this, they are likely to ask a ‘slightly easier’ question, adapt them to the practice tasks, or even lower the exam requirements, e.g., lowering the score limits by 1-2 points more favourable, or accepting answers that would not be accepted in other circumstances.

Note that these two strategies may have been present at the same time: the teacher perceived increased student contribution during the semester, for example, greater activity in online classes, and therefore, provided them with some reward by giving better final grades after taking into consideration their overall performance during the semester.

Please note that both narratives could appear at the same time.

It is also important to see that although grade point averages shifted, the shift was not necessarily drastic, and dropout rates did not improve. It may also be legitimate that there were individual characteristics that caused the difference in the grade point average.

From the student’s point of view, it could also mean that they were prepared in the same way in online education as in in-class education for exams. However, the same strategy did not necessarily result in better grades in the upper segment (obtaining 4 or 5).

The teacher determined the minimum level of requirements, either for mid-term achievements or final assignments and communicated it clearly to the students. How to obtain a passing grade was clear to the students. However, how to obtain good and excellent grades would have required more serious preparation and self-directed learning in online settings.

It is important to see that subjects, where it was more difficult to obtain better grades, were mainly theoretical ones (e.g.: lectures). They were tested mostly by oral exams where it was not possible to use additional materials, they had to answer directly to the questions. In this respect, teachers’ explanations, for example, could lead to very serious shortcomings in the case of knowledge transfer as well as the transfer of the same levels of the previous examination systems. This could result in lower achievement in areas where teachers’ explanations would have been necessary. Students had a harder time bridging the online-offline gap.

Education management issues

In the higher education system analysed, students receive a scholarship according to their grade point average achievement. It is calculated based on the average of the final grades received at the end of the semester and the credits earned. It is worth considering that for online systems, credit-weighted averages will not necessarily show students’ real knowledge. This also results in serious problems when it comes to rewarding students’ performance with a scholarship, where multiple types of educational models may conflict.

This is because whether students can successfully complete a subject differs greatly in an online education system but subjects seem to have become fundamentally easier.

Thus, different education systems (in-class education and online education) can lead to different grading results, so it is not advisable to apply the same scholarship system because it can be fundamentally unfair (some fields can become easier or more difficult).

The results of this study imply that COVID-19 had various effects on the education sector. The results are discussed in connection with the introduction of online education during the COVID-19 pandemic in terms of dropouts. The teachers who were involved in this study were the same during online education and on-campus education. This is the reason why we can conclude that the results also seem to suggest that teachers tried to compensate for the negative effects of the pandemic by bringing in pedagogical strategies aimed at ensuring that students could more easily obtain passing grades in examinations. Similarly, according to Mendoza et al. ( 2021 ), the failures of online education had a direct impact on student’s performance and learning.

This study found that students achieved better results during in-class education, which offers interesting implications for teaching practice. The results suggest that organizational support and flexible structures are needed in order to adapt teaching to the new circumstances set by the crisis. Higher education institutions should pay careful attention to developing students’ skills as well as to seeking ways to quickly respond to environmental changes while sustaining the delivery of high-quality education.

In the literature review, contradictory results were found for students’ performance during online education; therefore, this result contends previous literature and should be further explored.

A substantial difference in grade point averages can be found between the two examined groups. The first hypothesis was confirmed: students who participated in on-campus education obtained better grade point averages than students of online education. The teachers declared the minimum level of requirement and communicated it to the students quite clearly. It is a thought-provoking result that for online education, credit-weighted grade point averages would not necessarily show real knowledge well.

The second hypothesis was also proved because some subjects became easier to pass in online education, at least obtaining a passing grade. Online education facilitated students’ strategies e.g., creating an agenda of studying was essential to maintain effective and continuous learning.

The third hypothesis was not confirmed because significant differences in dropout rates were not found between the students who participated in online education and on-campus education. The dropout rate remained nearly unchanged between students who participated in online education (19 students dropped out), and students who participated in on-campus education (50 students dropped out). Introducing online education was effective or at least not harmful in terms of dropout because the dropout rate remained unchanged, compared to the previous year.

The results suggest that regarding dropout rates, there was no significant difference between online and on-campus education. The result suggests several assumptions: e.g.: the teachers had been more indulgent, as they also found it more difficult to communicate effectively during the COVID-19 period and were less able to apply with traditional methods. The process of knowledge transfer moved to online platforms and a different kind of interaction could be applied to rely on the online education system.

Limitations of the study and future research

This study proposed research clarifying the impact of the transition to online courses on dropout. The results show that this period did not contribute significantly to the increase in dropouts. Subjects became more achievable during online education. Students who participated in online education reported lower average grade points than students who participated in on-campus education. Consequently, on-campus students could win better scholarships than students who participated in online education because of better grades.

Several other factors e.g., whether students have met in person in the past, could affect the dropout and grade point averages which were not taken into consideration in this research. In the future, it is recommended to measure students’ current level of knowledge, how much they can adapt to online education, and how they would react in the next similar crisis.

Even though this study presents interesting results, the authors believe that the conclusions derived from them should be interpreted carefully. It allows both researchers and teachers to develop further methods to examine students’ strategies in online education during the COVID-19 period. Future research should be extended with additional variables. Data analysis techniques should also be taken into consideration in order to evaluate the academic profile of students who dropped out in previous years. Limitations include that analysis does not entirely reflect the true engagement of students in the education system because only the first two semesters were examined.

The results of this study open new lines of similar research. It is hoped that other researchers will consider examining the potential impact of COVID-19 on educational planning and scholarship systems. The results of this study can further be validated by considering a wider study that would collect both quantitative and qualitative data to give a deeper understanding of the effects of this epidemic.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

For a detailed explanation of the method see Takács et al. ( 2021 ).

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Acknowledgements

The described article was carried out as part of the EFOP 3.4.3-16-2016-00011 project in the framework of the Széchenyi 2020 programme. The realization of these projects is supported by the European Union, co-financed by the European Social Fund.

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TR contributed to the design of the study and data interpretation. As principal author, she coordinated the writing process of the manuscript. KJ and TS are researchers that study the dropout phenomenon across higher education, and therefore have participated on each phase of this research. OA and HZ have largely contributed to the analysis and interpretation of data, and consequently to the understanding of the phenomenon. Every author have played a remarkable role in the writing of this article.

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Takács, R., Takács, S., Kárász, J.T. et al. The impact of the first wave of COVID-19 on students’ attainment, analysed by IRT modelling method. Humanit Soc Sci Commun 10 , 127 (2023). https://doi.org/10.1057/s41599-023-01613-1

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Research Article

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

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

* E-mail: [email protected]

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

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

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

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

Roles Investigation, Methodology, Writing – review & editing

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

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

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

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

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

Material and methods

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

Findings and discussion

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

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

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

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

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

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

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

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

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

Introduction

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

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

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

Design and sampling

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

Online questionnaire

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

Digital focus group interview

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

Data analysis

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

Ethical considerations

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

Quantitative data

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

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

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

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

Suggestions for how to increase learning outcome in future digital courses

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

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

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

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

Qualitative data

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

Digital lectures.

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

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

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

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

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

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

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

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

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

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

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

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

Digital group work.

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

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

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

Motivation.

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

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

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

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

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

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

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

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

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

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

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

Strengths and weaknesses of the study

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

Conclusions

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

Supporting information

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

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

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

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

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

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Acknowledgments

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

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

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

March 3, 2022

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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The changes we need: Education post COVID-19

1 Melbourne Graduate School of Education, University of Melbourne, Parkville, Australia

2 School of Education, University of Kansas, 419 JRP, Lawrence, KS 66049 USA

Jim Watterston

The COVID-19 pandemic has caused both unprecendented disruptions and massive changes to education. However, as schools return, these changes may disappear. Moreover, not all of the changes are necessarily the changes we want in education. In this paper, we argue that the pandemic has created a unique opportunity for educational changes that have been proposed before COVID-19 but were never fully realized. We identify three big changes that education should make post COVID: curriculum that is developmental, personalized, and evolving; pedagogy that is student-centered, inquiry-based, authentic, and purposeful; and delivery of instruction that capitalizes on the strengths of both synchronous and asynchronous learning.

Introduction

The impact of the COVID-19 pandemic on education is both unprecedented and widespread in education history, impacting nearly every student in the world (UNICEF 2020 ; United Nations 2020 ). The unexpected arrival of the pandemic and subsequent school closures saw massive effort to adapt and innovate by educators and education systems around the world. These changes were made very quickly as the prevailing circumstances demanded. Almost overnight, many schools and education systems began to offer education remotely (Kamanetz 2020 ; Sun et al. 2020 ). Through television and radio, the Internet, or traditional postal offices, schools shifted to teach students in very different ways. Regardless of the outcomes, remote learning became the de facto method of education provision for varying periods. Educators proactively responded and showed great support for the shifts in lesson delivery. Thus, it is clear and generally accepted that “this crisis has stimulated innovation within the education sector” (United Nations 2020 , p. 2).

However, the changes or innovations that occurred in the immediate days and weeks when COVID-19 struck are not necessarily the changes education needs to make in the face of massive societal changes in a post-COVID-19 world. By and large, the changes were more about addressing the immediate and urgent need of continuing schooling, teaching online, and finding creative ways to reach students at home rather than using this opportunity to rethink education. While understandable in the short term, these changes will very likely be considered insubstantial for the long term.

The COVID-19 pandemic has the potential to be a once in a generation opportunity for real change a number of reasons. First, the pandemic was global and affected virtually all schools. As such, it provides the opportunity for educators and children to come together to rethink the education we actually need as opposed to the inflexible and outdated model that we are likely to feverishly cling to. Second, educators across the world demonstrated that they could collectively change en masse. The pandemic forced closure of schools, leaving teachers, children and adults to carry out education in entirely different situations. Governments, education systems, and schools offered remote learning and teaching without much preparation, planning, and in some cases, digital experience (Kamanetz 2020 ; Sun et al. 2020 ). Third, when schools were closed, most of the traditional regulations and exams that govern schools were also lifted or minimally implemented. Traditional accountability examinations and many other high stakes tests were cancelled. Education was given the room to rapidly adapt to the prevailing circumstances.

It is our hope that as we transition out of the COVID-19 pandemic and into an uncertain future that we can truly reimagine education. In light of this rare opportunity, we wish to urge scholars, policy makers, and educators to have the courage to make bold changes beyond simply changing instructional delivery. The changes that we advocate in this paper are not new but they never managed to gain traction in the pre-COVID-19 educational landscape. Our most recent experience, however, has exacerbated the need for us to rethink what is necessary, desirable, and even possible for future generations.

Changes we need

It is incumbant upon all educators to use this crisis-driven opportunity to push for significant shifts in almost every aspect of education: what, how, where, who, and when. In other words, education, from curriculum to pedagogy, from teacher to learner, from learning to assessment, and from location to time, can and should radically transform. We draw on our own research and that of our colleagues to suggest what this transformation could look like.

Curriculum: What to teach

It has been widely acknowledged that to thrive in a future globalized world, traditionally valued skills and knowledge will become less important and a new set of capabilities will become more dominant and essential (Barber et al. 2012 ; Florida 2012 ; Pink 2006 ; Wagner 2008 ; Wagner and Dintersmith 2016 ). While the specifics vary, the general agreement is that repetition, pattern-prediction and recognition, memorization, or any skills connected to collecting, storing, and retrieving information are in decline because of AI and related technologies (Muro et al. 2019 ). On the rise is a set of contemporary skills which includes creativity, curiosity, critical thinking, entrepreneurship, collaboration, communication, growth mindset, global competence, and a host of skills with different names (Duckworth and Yeager, 2015 ; Zhao et al. 2019 ).

For humans to thrive in the age of smart machines, it is essential that they do not compete with machines. Instead, they need to be more human. Being unique and equipped with social-emotional intelligence are distinct human qualities (Zhao 2018b , 2018c ) that machines do not have (yet). In an AI world individual creativity, artistry and humanity will be important commodities that distinguish us from each other.

Moreover, given the rapidity of changes we are already experiencing, it is clear that lifelong careers and traditional employment pathways will not exist in the way that they have for past generations. Jobs and the way we do business will change and the change will be fast. Thus there are almost no knowledge or skills that can be guaranteed to meet the needs of the unknown, uncertain, and constantly changing future. For this reason, schools can no longer preimpose all that is needed for the future before students graduate and enter the world.

While helping students develop basic practical skills is still needed, education should also be about development of humanity in citizens of local, national, and global societies. Education must be seen as a pathway to attaining lifelong learning, satisfaction, happiness, wellbeing, opportunity and contribution to humanity. Schools therefore need to provide comprehensive access and deep exposure to all learning areas across all years in order to enable all students to make informed choices and develop their passions and unique talents.

A new curriculum that responds to these needs must do a number of things. First, it needs to help students develop the new competencies for the new age (Barber et al. 2012 ; Wagner 2008 , 2012 ; Wagner and Dintersmith 2016 ). To help students thrive in the age of smart machines and a globalized world, education must teach students to be creative, entrepreneurial, and globally competent (Zhao 2012a , 2012b ). The curriculum needs to focus more on developing students’ capabilities instead of focusing only on ‘template’ content and knowledge. It needs to be concerned with students’ social and emotional wellbeing as well. Moreover, it needs to make sure that students have an education experience that is globally connected and environmentally connected. As important is the gradual disappearance of school subjects such as history and physics for all students. The content is still important, but it should be incorporated into competency-based curriculum.

Second, the new curriculum should allow personalization by students (Basham et al. 2016 ; Zhao 2012b , 2018c ; Zhao and Tavangar 2016 ). Although personalized learning has been used quite elusively in the literature, the predominant model of personalized learning has been computer-based programs that aim to adapt to students’ needs (Pane et al. 2015 ). This model has shown promising results but true personalization comes from students’ ability to develop their unique learning pathways (Zhao 2018c ; Zhao and Tavangar 2016 ). That is, students can follow their passions and strengths. This not only requires the curriculum to be flexible so that students can choose what they wish to learn, but also requires students to come up with their own learning pathway without being overly constrained by the pre-determined curriculum. Thus national curriculum or curriculum for all students should be a minimal suite of essential knowledge and skills, sufficient for all students to develop the most basic competences and learn the most common norms, expectations, and the societal organizations of a jurisdiction.

Enabling students to co-develop part of the curriculum is not only necessary for them to become unique but also gives them the opportunity to exercise their right to self-determination, which is inalienable to all humans (Wehmeyer and Zhao 2020 ). It provides the opportunities for students to make choices, propose new learning content, and learn about consequences of their actions. Furthermore, it helps students to become owners of their learning and also develop life-long learning habits and skills. It is to help them go meta about their learning—above what they learn and understand why they learn.

Third, it is important to consider the curriculum as evolving. Although system-level curriculum frameworks have to be developed, they must accommodate changes with time and contexts. Any system-level curriculum should enable the capacity for schools to contextualize and make changes to it as deemed necessary. Such changes must be justifiable of course but a system-level curriculum framework should not use national or state level accountability assessments to constrain the changes.

Pedagogy: How to teach

There is increasing call for learners to be more actively engaged in their own learning. The reasons for students to take a more significant role in their own learning are multiple. First, students are diverse and have different levels of abilities and interests that may not align well with the content they are collectively supposed to learn in the classroom. Teachers have been encouraged to pursue classroom differentiation (Tomlinson 2014 ) and students have been encouraged to play a more active role in defining their learning and learning environments in collaboration with teachers (Zhao 2018c ). Second, the recent movement toward personalized learning (Kallick and Zmuda 2017 ; Kallio and Halverson 2020 ) needs students to become more active in understanding and charting their learning pathways.

To promote student self-determination as both a self-evident, naturally born right and an effective strategy for enhanced learning (Wehmeyer and Zhao 2020 ), we need to consider enabling students to make informed decisions regarding their own learning pathway. This generation of learners are much more active and tech-savvy. They access information instantly and have been doing so throughout their daily life. They have different strengths and weaknesses. They also have different passions. Thus, schools should use discretion to start relaxing the intense requirements of curriculum. Schools could start by allowing students to negotiate part of their curriculum instead of requiring all students learn the same content, as discussed earlier. Students should be enabled to have certain levels of autonomy over what they want to learn, how they learn, where they learn and how they want to be assessed (Zhao 2018c ). When students have such autonomy, they are more likely to be less constrained by the local contexts they are born into. The impact of their home background and local schools may be less powerful.

Students should exercise self-determination as members of the school community (Zhao 2018c ). The entire school is composed of adults and students, but students are the reason of existence for schools. Thus, schools and everything in the school environment should incorporate and serve the students, yet most schools do not have policies and processes that enable students to participate in making decisions about the school—the environment, the rules and regulations, the curriculum, the assessment, and the adults in the school. Schools need to create these conditions through empowering students to have a genuine voice in part of how they operate, if not in its entirety. Students’ right to self-determination implies that they have the right to determine under what conditions they wish to learn. Thus, it is not unreasonable for schools to treat students as partners of learning and of change (Zhao 2011 , 2018c ).

It should not be unique to see school practices co-developed with students (Zhao 2018c ). Students not only will be co-owners (with parents and teachers) of their own learning enterprise, but also co-owners of the school community. It is likely to see students having their own personal learning programs and also acting as fully functioning members of the entire school community, contributing to fundamental decisions regarding the curriculum for all, the staff, the students, and the entire environment.

Moreover, with ubiquitous access to online resources and experts, students do not necessarily need teachers to continually and directly teach them. When students are enabled to own their learning and have access to resources and experts, the role of the teacher changes (Zhao 2018a ). Teachers no longer need to serve as the instructor, the sole commander of information to teach the students content and skills. Instead, the teacher serves other more important roles such as organizer of learning, curator of learning resources, counselor to students, community organizer, motivator and project managers of students’ learning. The teacher’s primary responsibility is no longer simply just instruction, which requires teacher education to change as well. Teacher education needs to focus more on preparing teachers to be human educators who care more about the individual students and serve as consultants and resource curators instead of teaching machines (Zhao 2018a ).

Pedagogy should change as well. Direct instruction should be cast away for its “unproductive successes” or short-term successes but long term damages (Bonawitza et al. 2011 ; Buchsbauma et al. 2011 ; Kapur 2014 , 2016 ; Zhao 2018d ). In its place should be new models of teaching and learning. The new models can have different formats and names but they should be student-centered, inquiry-based, authentic, and purposeful. New forms of pedagogy should focus on student-initiated explorations of solutions to authentic and significant problems. They should help students develop abilities to handle the unknown and uncertain instead of requiring memorization of known solutions to known problems.

Organization: Where and when to teach

Technology has made it possible for schools to offer online education for quite some time and the number of students taking online courses has been on the rise, but not until the arrival of COVID-19 has the majority of education been offered through this mode. While there are many good reasons for schools to return to what was refrred to as “normal,” the normalcy may not be easily achieved because of the uncertainty of the virus, and as discussed above, may not even be desirable.

Moving teaching online is significant. It ultimately changed one of the most important unwritten school rules: all students must be in one location for education to take place. The typical place of learning has been the classroom in a school and the learning time has been typically confined to classes. This massive online movement changed the typical. It has forced teachers to experience remote teaching without proximity to the students. It has also given many teachers the opportunity to rethink the purpose of teaching and connecting with students.

When students are not learning in classes inside a school, they are distributed in the community. They can interact with others through technologies. This can have significant impact on learning activities. If allowed or enabled by a teacher, students could be learning from online resources and experts anywhere in the world. Thus, the where of learning changes from the classroom to the world.

Furthermore, the time of learning also changes. When learning goes online and students are not or do not need to be in schools, their learning time vastly expands beyond the traditional school time. They can learn asynchronously at anytime. Equally important is that their learning time does not need to be synchronous with each other or with that of the teacher.

There are many possible ways for schools to deliver remote learning (Zhao 2020 ). The simplest is to simulate that schools are open with traditional timetables with the default model being that all students attend lessons on screen at the same time as they do in schools. In this case, nothing changes except for the fact that students are not in the same location as their classmates and the teacher. While it has been perhaps the most common approach that has been taken by many schools, this approach has not been very effective and successful, resulting in distress, disengagement, and much less personal interaction and learning than traditional face-to-face situations (Darby 2020 ; Dorn et al. 2020 ).

As schools continue to explore online learning, new and more effective models are being explored, innovatively developed, and practiced. The more effective models of online learning have a well-balanced combination of both synchronous and asynchronous sessions that enable more desirable ways of learning. Instead of teaching online all the time, it is possible, for example, to conduct inquiry-based learning. Students receive instructions from online resources or synchronous meetings, conduct inquiry, create products individually or within small groups, and make presentations in large class synchronous meetings. Instead of lecturing to all students, teachers could create videos of lectures or find videos made by others and share them with students. They would also be meeting with small groups of individuals for specific advice and support. The fundamental pursuit is that there is minimal benefit or student engagement for teachers to lecture all the time when more interesting and challenging instructional models can be developed.

Today, being disconnected physically can result in being more broadly connected virtually. Students have been traditionally associated with their schools and schools have typically served local communities. Thus, students typically are connected and socialize with their peers from restricted catchment areas. Despite the possibility to connect globally with people from other lands, most schools’ activities are local. Today, when local connections become less reliable and students are encouraged to have social distancing, it is possible to encourage more global connections virtually. Students could join different learning communities that involve members from different locations, not necessarily from their own schools. Students could also participate in learning opportunities provided by other providers in remote locations. Furthermore, students could create their own learning opportunities by inviting peers and teachers from other locations.

The ideal model of organizing students, based on the COVID-19 experiences, is perhaps a combination of both online and face-to-face learning opportunities. Many schools have already reopened, but when schools reopen it is unnecessary to undo the online aspect of learning developed during COVID-19. Online learning can be effective (Means et al. 2013 ; Rudestam and Schoenholtz-Read 2010 ; Zhao et al. 2005 ), but a well-designed mixed mode delivery of online and face-to-face education should be more effective for learning in general but especially so should there be future instances of virtual learning (Tucker 2020 ). The idea of blended learning or flipped classrooms (Bishop and Verleger 2013 ) has been promoted and researched in recent years as very effective models of teaching. COVID-19 should have made the convincing much easier since many teachers have been forced to move online.

When learning is both online and face-to-face, students are liberated from having to attend classes at specific times. They are also no longer required to be in the same place to receive instruction from teachers. They could work on their own projects and reach out to their teachers or peers when necessary. When students are no longer required to attend class at the same time in the same place, they can have much more autonomy over their own learning. Their learning time expands beyond school time and their learning places can be global.

Education will undoubtedly go through major changes in the next decade as the combined result of multiple major forces. These changes include curricular changes that determine what is to be learned by learners. It is likely that more students will be moving toward competency-based learning that has an emphasis on developing unique skills and abilities. Learning has to become more based on strengths and passions and become personalized. In response, education providers will need to make student autonomy and student agency key to transforming pedagogy and school organizations. Students will prosper by having more say in their own learning and their learning communities. Moreover, schools will have a unique opportunity to positively and proactively change as a result of COVID-19 and the need for global connections. It is possible to see schools rearrange their schedules and places of teaching so that students can at the same time take part in different and more challenging learning opportunities regardless of their physical locations. Relevant online learning will be on the rise and perhaps becomes a regular part of the daily routine for many students.

Of course, we cannot forget that not all students have equal access to technology, both in terms of hardware and digital competency. The issue of digital divide remains a significant issue around the globe. It is important for us to reimagine a better education with technology and find creative ways to make education more equitable, including wiping out the digital divide.

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Contributor Information

Yong Zhao, Email: ude.uk@oahzgnoy .

Jim Watterston, Email: [email protected] .

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Student Education Analysis of e-Learning during COVID-19 Using Support Regression Random Forest Algorithm

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Impact of COVID-19 in the web accessibility of higher education institutions: a pending challenge

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• P. Nso-Mangue 1 ,
• C. Cachero-Castro 1 ,
• S. Meliá 1 &
• S. Luján-Mora 1  

The COVID-19 pandemic forced educational institutions to close and led to a radical transformation of the global education system. This process of change had to take place in a short period of time and, as a result, methodologies and learning tools were adapted. The closure of educational institutions and the disruption to learning impacted all students. However, vulnerable students, including those with disabilities, were particularly affected due to the lack of preparedness for inclusive learning during the rapid transition to emergency online learning. One of the many challenges faced by educational institutions during this transition was ensuring web accessibility for students with disabilities. However, it appears that some of the positive changes that took place in the education system during the pandemic, such as the enhancement of web accessibility, have been declining recently. The aim of this article is to review how a group of universities responded to the closure caused by the pandemic from the point of view of web accessibility, whether they improved the accessibility of their websites and whether this improvement has been maintained over time. To achieve this, the web accessibility of the home pages of selected universities around the world was evaluated against Web Content Accessibility Guidelines 2.1, for the period from 2018 to 2024. The results show that there was an improvement in web accessibility immediately after the COVID-19 outbreak, but this trend has not been maintained.

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1 Introduction

During the COVID-19 pandemic, organisations worldwide turned to the Internet to provide services to citizens [ 1 , 2 ]. In some countries, essential procedures such as interacting with the administration, health services, or banks, were only avaiable online [ 3 , 4 ]. Companies and individuals had to adapt to this situation during and after the pandemic through digitalisation [ 1 , 5 ].

The percentage of the population with access to the Internet is increasing, although 33.7 % of the world’s population still does not have access to the Internet [ 6 ]. Therefore, a significant proportion of the population experienced serious barriers in coping with the exceptional situation imposed by the COVID-19 pandemic lockdown [ 7 , 8 ]. The closure of COVID-19 presented an unprecedented challenge, particularly for higher education institutions, which had to turn to online platforms to continue their activities. This shift to online learning further highlighted the existing barriers that persons with disabilities face in accessing online education [ 9 , 10 ].

Accessing the Web is not equal to everyone. About 16 % of the world’s population, estimated at 1.3 billion people, live with some form of disability and this value is increasing, in part due to the ageing of the population and the prevalence of non-communicable diseases [ 11 ]. Hence, web accessibility needs to be monitored to raise awareness for continuous improvement.

There are more reasons to monitor web accessibility. First, the performance of the Digital Accessibility Rights Evaluation Index (DARE) [ 7 ] has not improved significantly in recent years, although it is rising slightly [ 12 ]. Second, non-compliance with the Web Content Accessibility Guidelines (WCAG) has led to lawsuits, such as those against the University of California Berkeley [ 13 ] and Harvard University [ 14 ]. Third, the 2023 Digital Accessibility Index shows that only 3 % of the Web is accessible to persons with disabilities [ 15 ]. The key findings of this report are that around 56 % of images on corporate websites are not accessible to persons with visual impairment, 64 % of pages have links that are not clear to persons with some visual and cognitive impairments, and 25 % of forms lack clear labels. Fourth, the 2024 report of The WebAIM Million report shows that by February 2024, 95.9 % of the pages analyzed have some WCAG failure. [ 16 ].

Monitoring the evolution of web accessibility performance is of special importance for higher education. Quality education is one of the United Nations Sustainable Development Goals (UN-SDGs) [ 17 ]; because education enables upward socio-economic mobility and is a key to escaping poverty. In the information society, equal access to the Web is essential for inclusive and quality education. Improving web accessibility compliance can improve the web experience for all users, whether they have a disability or not [ 18 , 19 ]. Furthermore, achieving the UN-SDGs requires good web accessibility policies and compliance [ 20 ].

An open question is whether the efforts made by universities to cope with the COVID-19 pandemic have continued after the pandemic has ended. This is the motivation for this research: its aim is to verify, from the point of view of web accessibility, how a group of universities responded to the constriction caused by the pandemic, whether they improved the accessibility of their web pages, and whether this improvement has been maintained over time. The review is based on the WCAG 2.1 [ 21 ] of the World Wide Web Consortium (W3C). Although WCAG version 2.2 was released in October 2023, no automated web accessibility evaluation tools (AWAETs) have implemented it yet [ 22 ].

As this research aims to assess web accessibility over a period of time, it needs to make use of a digital preservation project called the Internet Archive, Footnote 1 which is dedicated to preserving the websites of organisations around the world. The archived home pages of selected universities are retrieved from the Internet Archive’s Wayback Machine for all the years from 2018 to 2024.

Laws and international treaties such as the Convention on the Rights of Persons with Disabilities (CRPD) [ 18 ] enforce the implementation of web accessibility. The CRPD has conceptualised the accessibility of information and communication technologies (ICTs) as a prerequisite for the enjoyment of human rights and has led to a number of reforms in national legal frameworks worldwide. Many studies have evaluated the level of compliance of websites of different organisations. Most of these evaluations are very punctual in time, but this study evaluates the performance of web accessibility over a period of seven years (2018 to 2024): the two years before the COVID-19 pandemic, the two years during the pandemic and the two years after its end. This general objective is broken down into the following specific objectives:

To determine the web accessibility scores of selected web pages before, during and after the COVID-19 pandemic;

To evaluate the evolution of web accessibility errors of selected web pages during the period from 2018 to 2024;

To measure the level of implementation of Accessible Rich Internet Applications (ARIA) [ 23 ], on selected web pages during the period from 2018 to 2024.

Web accessibility can be evaluated in three main ways: by experts in the field, by AWAETs, and by user testing. The most widely used method, which is less affected by subjective opinions, is the use of AWAETs. However, a combination of automated and manual evaluation is recommended, as these AWAETs do not detect all possible web accessibility issues [ 24 ]. Nevertheless, to ensure that this study can be reproduced by other researchers, only AWAETs are used.

The remainder of this article is structured as follows. Section 2 describes the background information needed to understand web accessibility, its regulation around the world, and its relationship to the COVID-19 pandemic. Section 3 presents the methodology used to collect web accessibility information for the period before, during and after COVID-19. Section 4 presents the web accessibility results obtained from selected universities around the world in a way that is understandable to the audience, according to the objectives. Section 5 discusses the results and section 6 presents the conclusions, highlighting possible future work that could be derived from this study.

2 Background

2.1 web accessibility regulation and legislation worldwide.

The W3C periodically publishes WCAG, which remains the standard for evaluating web accessibility [ 25 ]. In 2008, WCAG version 2.0 was released and in 2012 it became the ISO/IEC 40500:2012 standard [ 26 ]. WCAG 2.0 states that a web page is accessible if it is perceivable, operable, understandable and robust. In June 2018, WCAG 2.1 was released [ 21 ]. To achieve these four principles, WCAG 2.1 provides 13 guidelines, 78 testable criteria and 3 levels of conformance (A, AA and AAA) [ 27 ]. WCAG 2.2 was also released in October 2023; however, no AWAET has implemented it yet.

The most important current web accessibility laws [ 28 ] are the Americans with Disabilities Act (ADA) and Section 508 from the United States of America, the Accessibility for Ontarians with Disabilities Act (AODA) from Canada, and the Web Accessibility Directive (WAD) and the European Accessibility Act (EEA) from the European Union. Some countries around the world have also made web accessibility mandatory by law and have established web accessibility certification programmes [ 29 ].

Web accessibility is already regulated in many countries around the world. Each country follows a normative hierarchy structure similar to Kelsen’s pyramid [ 30 ]. In the European Union, for example, this hierarchy is organised from top to bottom in the national constitution, European Union directives, international treaties, national laws and regulations. Accessibility regulation around the world could be placed at any level of this hierarchy [ 31 ]. For example, in Ecuador it is in the form of a regulation, “Reglamento Técnico Ecuatoriano RTE INEN 288" [ 32 ], in the European Union it is in the category of a directive [ 33 ], “Directive (EU) 2016/2102 on the accessibility of the websites and mobile applications of public sector bodies", in countries such as the United States, Australia, Argentina, Israel, Canada, Republic of Korea, Switzerland and others, it is in the form of a law. This law could be about persons with disabilities in general, like the “Section 508 Amendment to the Rehabilitation Act of 1973 from United States of America" [ 34 ] or the “Disability Discrimination Act 1992 from Australia" [ 35 ], or strictly related to web accessibility in particular, like “Ley de Accesibilidad de la Información en las Páginas Web de Argentina" [ 36 ]. However, some countries, such as Taiwan, Hong Kong, India and others, still regulate web accessibility in the form of policies, which may be translated into legislation in the future. Regrettably, numerous countries still lack any governmental policy regarding web accessibility [ 28 ].

2.2 COVID-19 and web accessibility

The COVID-19 pandemic crisis highlighted the importance of the Web as a means of communication between governments and their citizens. The imposition of quarantine during the pandemic forced human interaction to take place through ICT. Several universities and educational centres continued to offer their courses online, through the Web. However, some institutions were unable to do it due to economic reasons or the digital divide.

The post-COVID-19 era has normalised the Web as the main way for citizens to interact with e-government, e-health, e-education, e-commerce and e-entertainment services; it has also highlighted the importance of web accessibility in achieving the UN-SDGs and emphasised that the development must be inclusive. Of the 17 UN-SDGs that make up this agenda, there are several that contain specific references to persons with disabilities. These are: UN-SDG 4 on inclusive and quality education; UN-SDG 8 on economic growth, full employment and decent work; UN-SDG 10 on the reduction of inequalities; UN-SDG 11 on inclusive and sustainable cities and communities; and finally UN-SDG 17 on the implementation of the agenda and the necessary alliances [ 37 ].

2.3 Related works

Web accessibility of universities is a trendy topic and many researchers have conducted studies on it. The scope of this brief literature review is limited to the period from 2018 to 2024. In a previous work [ 38 ], we summarized 42 scientific papers about accessibility evaluation of university websites. Some of these studies have focused on evaluating general web accessibility issues of universities around the world [ 38 , 39 , 40 , 41 , 42 , 43 , 44 ]. However, the focus of this literature review will be on the core issue of this research, which is to determine to what extent web accessibility and its relationship to COVID-19 has been researched and what aspects are still missing and need to be addressed.

Acosta et al. [ 45 ] carried out an evaluation of the web accessibility of the universities of the European Union in times of COVID-19. The aim of this work was to evaluate the accessibility of the websites of the 1,584 best universities in the European Union according to the Webometrics ranking [ 46 ], using Pa11y, an AWAET based on WCAG 2.1. The results of the statistical analysis showed that the position in the ranking of European Union universities was not an indicator of the level of accessibility of their websites. It was also shown that the percentage of WCAG 2.1 compliance failures was very similar to the percentage of HTML coding standard failures. This study highlights the urgent need to include accessibility features in to the websites of European Union universities; therefore, web designers, developers and authorities of educational institutions must reflect and take decisions to eliminate accessibility barriers and deficiencies in their websites, since the right of access to education of persons with disabilities is being violated.

Doush et al. [ 47 ] carried out an evaluation of the web accessibility of Palestinian universities during the COVID-19 pandemic against WCAG 2.0. They found that the most violated guideline was empty link, which is related to success criterion 2.4.4 Link purpose. The second most violated error was linked image missing alternative text, which is related to success criterion 1.1.1 Non-text content. The obtained results show that the websites of selected university do not comply with WCAG 2.0 Level A.

Ennam [ 48 ] conducted and assessed the COVID-19 pandemic forced transition to distance e-learning in Moroccan universities. About 274 students were interviewed to collect and analyse their perceptions, reactions and attitudes towards the COVID-19. Much of the data collected testified to the inadequacy of online teaching/learning, mainly due to low web accessibility/affordability.

Russ et al. [ 49 ] investigated the problems faced by students and teachers during the abrupt transition to online education during the COVID-19 lockdown. They reviewed and analysed 14 papers on e-learning accessibility published over the past 11 years, in order to translate their findings into actionable recommendations for improving the accessibility of platforms at the time of the COVID-19 crisis, as well as for future pandemics. Their findings highlighted the need to build organisational cultures of accessibility, with support for educators as accessible content creators, and to raise awareness of the many types of disabilities that can affect students and how accessible content can prevent widening opportunity gaps.

Laamanen et al. [ 44 ] conducted an empirical study on the accessibility of Finnish higher education web pages. The aim was to examine the accessibility of all Finnish higher education landing pages based on WCAG 2.1 using a combination of two AWAETs. The results showed that the web pages of higher education institutions were not accessible and that there were enormous differences between the institutions.

Finally, an interesting study that deserves to be mentioned, despite the fact that it has nothing to do with universities and COVID-19, is a study carried out by Lazar et al. [ 50 ]. They evaluated the potential implementation of new metrics in AWAET for managers. Its significance in relation to this study is that they also used digital preservation, via the Wayback Machine, to automatically crawl and evaluate websites from the past in order to provide feedback to managers about the accessibility of their organisations’ websites.

In summary, this literature review on web accessibility and COVID-19 shows that most of these articles are categorized as cross-sectional studies, as there were focused on assessing the status of web accessibility in universities at a particular point in time. Those articles that analyzed a time period were basically a literature review of articles published on the subject during that same time period. Other articles presented the analysis of data collected by surveys. Therefore, there is still a gap of research for performance indicators of web accessibility of universities from past periods in general and during the COVID-19 pandemic in particular. Therefore, our study tries to fill this gap by performing a longitudinal study that shows the web accessibility performance of selected universities from 2018 to 2024, in order to observe its evolution before, during and after the COVID-19 pandemic.

3 Materials and methods

The method used to determine the web accessibility performance of universities from five continents around the world for the period from 2018 to 2024 is divided into six phases, as shown in Fig.  1 .

Phases of the applied research methodology

3.1 Phase 1: review bibliography on web accessibility and COVID-19

We conducted a comprehensive bibliographic review of research related to web accessibility of universities’s websites and COVID-19 in Scopus, Web of Science and Google Scholar. The aim of this review was to find out what has been done and what aspects still need to be researched. The search results were filtered by years between 2018 and 2024.

3.2 Phase 2: select universities to evaluate their web accessibility from 2018 to 2024

We chose a set of 25 universities from around the world. Six universities were pre-selected as this work is part of a project with them as partners. The rest of the universities were randomly selected. The source of the universities was Webometrics [ 46 ], although ShangaiRanking was also an option, but Webometrics was preferred because it is easy to search by continent. The procedure for random selection consisted of creating a random calculation in Microsoft Excel that ranged between number one and five, being five the maximum number of universities on each continent. Once the universities were selected, a web archive repository was needed to be able to retrieve websites from the past. The Wayback Machine holds historical website information for many organisations around the world and was chosen as the source of information for this research. Footnote 2

3.3 Phase 3: choose the automated web accessibility evaluation tool to be used

Many tools can be used to evaluate web accessibility [ 51 ]. In this research, Mauve++ Footnote 3 and WAVE Footnote 4 were selected. Mauve++ was selected among them because of its ability to perform server-side rendering evaluations. In this research, server-side rendering was used because it provides more accurate evaluations. Using the Server Side Rendering Validation, the validation tool does not parse the static web page code, but it uses Selenium to load the HTML and CSS code in a headless version of the Chrome browser. In this way, it simulates the loading phase as if the page were open in the user’s browser and then performs the validation on the DOM of the resulting page obtained by also performing the scripts included in it. Mauve++ supports WCAG 2.1 (conformance levels A, AA and AAA). Mauve++ provides two evaluation results, by technology and by success criteria. This research considered only the results by success criteria.

The WAVE tool was chosen for the evaluation of web accessibility errors presented in the web page and the level of ARIA implementation. Having good ARIA implementation is an indication that the organisation and its web developers have considered the need for robustness of the website so that it can communicate the roles, states and properties of user interface elements to assistive technologies.

There was a need to set a threshold score for a university website to be considered accessible; in this research this score was set to 80 for WCAG 2.1 and conformance level AA. Here we considered that 20 % of non WCAG conformance cause 80 % of web accessibility barriers encountered by persons with disabilities. This is an arbitrary score set for this research based on Pareto’s principle [ 52 , 53 ]. In order to categorise performance over the years, this research sets three levels of performance (poor, partial and good). Scores below 50 were considered poor performance, scores between 51 and 80 were considered partial performance, and scores above 80 were considered good performance.

3.4 Phase 4: perform web accessibility evaluation from 2018 to 2024

The evaluations were carried out on the archived home pages of the selected universities using the Wayback Machine of the Internet Archive’s Wayback Machine, Footnote 5 which is a digital preservation repository that holds copies of websites from previous years for many websites on the Internet. The home pages of the selected universities were evaluated for the period from 2018 to 2024. In this research, 2018 to 2019 represents the pre-COVID-19 period, 2020 to 2021 represents the COVID-19 period, and 2022 to 2024 represents the post-COVID-19 period. This research used the last backup of the year for the university’s website as the primary source for evaluation, i.e. the last backup of December; however, if this backup was not available, the source was the next backup going backward through the months of the year.

3.5 Phase 5: present and discuss results aligned to the objectives

We present the results and discussion in relation to the objectives of this research. To improve the readability of the results presented, the names of the universities were shortened as shown in the Table  1 , composed of the short name of a university followed by the country code. The results are grouped and presented by continent to facilitate understanding and to avoid overwhelming the reader with a lot of information in one place. Finally, these results are discussed, including a final comparison of web accessibility performance by continents. The content of this phase is presented in Section 4 and Section 5 .

3.6 Phase 6: establish conclusions from obtained results and recommend future work

We draw conclusions from the results presented in phase 4 and the discussion made in phase 5. Finally we suggest future work that could be derived. The content of this phase is presented in Section 6 .

What follows are the results of the web accessibility scores, errors and ARIA implementations of selected universities from around the world for the period from 2018 to 2024. These results are derived from phase 4 of the methodology shown in Fig.  1 and are presented grouped by the continent that the universities belong, in alphabetic order.

The values from 2018 to 2019 represent the pre-COVID-19 period; 2020 to 2021 represent the COVID-19 pandemic period; and 2022 to 2024 represent the post-COVID-19 pandemic period. A total of 175 evaluations (25 universities by 7 years) were conducted using two AWAETs.

The Mauve++ tool was used to determine the web accessibility score, and WAVE was used to collect web accessibility errors and the number of ARIA implementations. These results are grouped by continent and presented in alphabetical order. The web accessibility score is represented by the acronym AC, the errors by ER and the ARIA by AR. The names of the universities are also replaced by the corresponding short names presented earlier in Table  1 .

Table  2 presents the results of web accessibility scores, errors and ARIA of universities from Africa, for the period from 2018 to 2024. This table comprises five columns; the first column is the short name of the university being evaluated, the second column is the archived URL of the its home page, the third column is the web accessibility score of that home page, the fourth column is the number of web accessibility errors encountered, the fifth column is the number of ARIA implementations found and the sixth column is the number of contrast errors. The archived URL is the one that appears in the “timestamp” of the page file in the Internet Archive. For example, the first URL has 20181228231929, which means it was archived in December 28, 2018 at 23:19:29. This table structure is the same for all continents and will be used in Tables  3 ,   4 ,   5 and   6 .

Most of the web accessibility scores of African universities are lower than 80, which is the established threshold, which means that either they are partially or poorly accessible. From the five universities evaluated, only one can be considered as having good level of web accessibility as achieved scores higher than, and for three consecutive years. The values of ARIA implementation are low, although web accessibility errors prevail throughout the period.

Figure  2 shows the performance of African universities in the form of a line chart for the period from 2018 to 2024. An increase in web accessibility score or ARIA represents a good performance, while an increase in errors represent a decrease in performance.

Most of these universities show low performance over the years, and only the University Cheikh Anta Diop de Dakar (UCAD-SN), Senegal, maintained a good web accessibility performance from 2018 to 2021; however, its performance decreased after the end of COVID-19. The performance of the University of Johannesburg (UJ-ZA), South Africa, was good before the start of the COVID-19 pandemic; although it has made good efforts to reduce the number of errors, ARIA and web accessibility have not improved.

Web accessibility performance of African universities for the period from 2018 to 2024

4.2 America

Table  3 shows the results of web accessibility scores, errors and ARIA of universities from America for the period from 2018 to 2024. Most of the web accessibility scores of American universities are lower than 80, which is the established threshold. The values of ARIA implementation are also low and only one university, out of five, the Universidad de Veracruz (UV-MX), Mexico, has improved in ARIA implementation. However, American universities present a number of web accessibility errors.

Figure  3 shows the performance of American universities in the form of a line chart for the period from 2018 to 2024. In general, the performance of web accessibility remained low during this period. An increase in performance was observed during the COVID-19 pandemic, but it decreased after the end of the pandemic. The performance of the Universidad Politécnica Salesiana de Ecuador (UPS-EC), was good before the start of the COVID-19 pandemic, but it decreased immediately afterwards and has remained partial since then.

A decrease in web accessibility errors is observed at the beginning of COVID-19, but increases immediately after its end. ARIA implementation also increases during this period. The Instituto Tecnológico de Aguas Calientes (TECNM-MX), Mexico, did not have archived data from the Wayback Machine for 2018.

Web accessibility performance of American universities for the period from 2018 to 2024

Table  4 shows the results of web accessibility scores, errors and ARIA of universities from Asia for the period from 2018 to 2024. Most of the web accessibility scores of Asian universities are lower than 80, which is the established threshold. The values of ARIA implementation are also low and only one university, out of five, the Tel Aviv University (TAU-IL), Israel, has improved in both ARIA implementation and web accessibility scores. Asian universities present significant number of web accessibility errors. We did have issue to open the archived URL of University of Calcutta (CALUNIV-IN), India, for 2024, therefore we performed the web accessibility evaluation directly from the online URL at 27 of March 2024.

Figure  4 shows the performance of Asian universities in the form of a line chart for the period from 2018 to 2024. The Tel Aviv University (TAU-IL), Israel, stands out, although in terms of web accessibility performance before and during the COVID-19 pandemic, although it has decreased after the end of the pandemic. For the rest of the Asian universities evaluated, some maintained their web accessibility performance during the COVID-19 pandemic, while others experienced a decline. After the end of the COVID-19 pandemic, all these Asian universities experienced a decline in web accessibility performance, although their performance remained partial throughout the period. The implementation of ARIA did not improve in these universities during this period, but a decrease in the number of errors was observed.

Web accessibility performance of Asian universities for the period from 2018 to 2024

Table  5 shows the results of web accessibility scores, errors and ARIA of universities from Europe for the period from 2018 to 2024. Most of the web accessibility scores of European universities are lower than 80, which is the established threshold. Two universites out of five, Universidad de Alicante (UA-ES), Spain, and National Technical University of Ukraine (KPI-UA), have good web accessibility scores. The values of ARIA implementation are also low and only one university, out of five, Universidad de Alicante (UA-ES), has improved on ARIA implementation. European universities present very low web accessibility errors. We did have issue to open archived URL of Universidade Aberta (UAB-PT), Portugal, for 2024, therefore we performed the web accessibility evaluation directly from the online URL at 27 of March 2024.

Figure  5 shows the performance of European universities in the form of a line chart, for the period from 2018 to 2024. At the beginning of COVID-19, the Universidad de Alicante (UA-ES), Spain, experienced a decrease of the good performance it had before the beginning of the pandemic and it has remained partial since then. The National Technical University of Ukraine (KPI-UA) stands out with a good performance before and during the COVID-19 pandemic, but it also dropped to partial performance when the pandemic ended, and an increase in web accessibility errors is observed since then. Most of these universities have reduced the number of errors in their web pages, but have not improved their ARIA implementations.

Web accessibility performance of European universities for the period from 2018 to 2024

4.5 Oceania

Table  6 presents the results of web accessibility scores, errors and ARIA of universities from Oceania, for the period from 2018 to 2024. Most of the web accessibility scores of Oceanian universities are higher than 80, which is the established threshold. However, the values of ARIA implementation are is low. Oceanian universities present a number of web accessibility errors.

Figure  6 shows the performance of Oceanian universities in the form of a line chart for the period from 2018 to 2024. Australian National University (ANU-AU), Australia, University of Waikato (WAIKATO-NZ), New Zealand, Fiji National University (FNU-FJ), Fiji and National University of Samoa (NUS-WS) had good performance before and during the COVID-19 pandemic, but it dropped to partial performance when the pandemic ended. The University of Papua New Guinea (UPNG-PG) had partial performance before, during and after the COVID-19 pandemic. The number of errors on these sites did not improve during this period, but there was a slight increase in the use of ARIA features.

Web accessibility performance of Oceanian universities for the period from 2018 to 2024

Figure  7 shows the web accessibility performance of selected universities grouped by continent in the form of a line chart for the period from 2018 to 2024. First, it can be seen that the web accessibility score in 2024 is lower than in 2018 on all continents. Second, web accessibility errors fluctuate up and down throughout the period for all continents except Asia, which shows a steady decrease in errors. Third, the performance of ARIA in general improves steadily throughout the period for all continents, especially for the Americas and Europe. Fourthly, contrast errors are higher in Africa than in any other continent, and in Asia they increase steadily throughout the period.

Web accessibility performance by continents for the period from 2018 to 2024

Figure  8 shows the six most frequent web accessibility issues, out of a total of 12, recorded for selected universities from all continents, in the form of a bar chart for the period 2018 to 2024. The values are the sum of each type of web accessibility problem registered from 2018 to 2024. On the one hand, low contrast, lack of alternative text on images and empty links are the top three recurring issues across all continents. On the other hand, empty headings, empty buttons and empty form labels are recurring issues that vary between continents. Other common web accessibility problems recorded are: broken ARIA reference, missing language, marquee, missing form label and missing page title. However, these problems did not occur on all continents at the same time, so they were excluded.

Cumulative web accessibility errors of selected universities by continents for the period from 2018 to 2024

Figure  9 shows the six most frequent web accessibility problems at selected universities on all continents in the form of a bar chart for the period 2018 to 2024. Low contrast ranks first, followed by missing alternative text on images, empty links, empty headings, empty form labels and empty buttons. The values are the sum of each type of web accessibility problem registered from 2018 to 2024.

Total cumulative errors of selected universities for all continents for the period from 2018 to 2024

5 Discussion

The websites of African universities show partial performance in web accessibility scores, low performance in errors and ARIA. Low scores in web accessibility and errors mean that these universities do not comply with the WCAG guidelines and present barriers for persons with disabilities to access their websites. Moreover, low performance in ARIA means that African universities may not be compatible with assistive technology for persons with disabilities.

The websites of American universities show partial performance in web accessibility scores, low performance in errors and ARIA. Low scores for web accessibility and errors mean that these universities do not comply with the WCAG guidelines and present barriers for persons with disabilities to access their websites. Low performance in ARIA means that American universities may not be compatible with assistive technology for persons with disabilities.

The websites of Asian universities show partial performance in web accessibility scores, and low performance in errors and ARIA. Low scores for web accessibility and errors mean that these universities do not comply with the WCAG guidelines and present barriers for persons with disabilities to access their websites. Low performance in ARIA means that Asian universities are not compatible with assistive technology for persons with disabilities.

The websites of European universities show partial performance in web accessibility scores, low performance in ARIA and good performance in errors. Low performance in web accessibility means that these universities do not comply with the WCAG guidelines and present barriers for persons with disabilities to access their websites. Good performance in web accessibility errors means that these universities are making efforts to improve web accessibility. Low performance in ARIA means that European universities are not compatible with assistive technologies for persons with disabilities.

The websites of Oceanian universities score well on web accessibility and poorly on ARIA and errors. High scores for web accessibility mean that these universities comply with the WCAG guidelines and do not present many barriers for persons with disabilities to access their websites. Low performance in ARIA means that African universities are not compatible with assistive technology for persons with disabilities.

Overall, there is a progressive decrease in web accessibility performance (AC) from 2018 to 2024 for all continents, as well as the prevalence of web accessibility errors (ER). However, the implementation of ARIA (AR) has, on the contrary, increased since 2018, except for the Asian continent, which shows a sharp decrease in performance from 2023. This can be better appreciated in Fig.  7 , which shows the web accessibility performance of universities from all continents in the form of a line chart for the period from 2018 to 2024.

This longitudinal study also shows that digital preservation of web pages provides researchers with a good source of information to understand the evolution of web accessibility in universities around the world years before the start of the COVID-19 pandemic, during its duration, and years after its end. The ability to analyse web accessibility scores, errors and ARIA on web pages from the past provides indicators that organisations can use in their scorecards when conducting performance evaluations.

The differences in the web accessibility performance of different universities from different continents are due to differences in the commitment, implementation capacity and results in web accessibility of universities and the associated countries and supranational organisations to which they belong. Nevertheless, the results of this longitudinal study can provide managers with a better understanding of what needs to be done to improve web accessibility by relating these web accessibility indicators to other performance variables and finding their correlations.

The six most common web accessibility issues illustrated in Figs.  8 and   9 mean that persons with disabilities have difficulty perceiving, navigating and understanding the content of the websites of selected universities from five continents. As such, this highlights non-compliance with the WCAG principles [ 21 ]. persons with visual impairment are most affected as low contrast error is the number one problem, which is consistent with the findings of the 2023 Digital Accessibility Index [ 15 ].

This study alone cannot clarify the reason for the decline in the universities’ web accessibility compliance performance after the end of the COVID-19 pandemic. Further studies are needed as other factors may be involved, such as legislation, regulations, policies, programs, organisation, processes, resources, etc. These factors are examined nationally by the Digital Accessibility Rights Evaluation Index (DARE Index); therefore, a correlation study between the web accessibility of universities and the DARE Index of the countries to which they belong could provide more information on the factors behind the decline in web accessibility performance of universities after COVID-19.

6 Conclusions and future works

The COVID-19 outbreak increased the web accessibility performance of many of the universities evaluated in this study. Regrettably, after the COVID-19 pandemic ended, this performance was found to have declined, in some cases to levels lower than before the outbreak. This behaviour suggests that the closure during the COVID-19 pandemic may have led stakeholders to consider web accessibility, but further studies should be conducted to verify that this was not due to other factors. In any case, web accessibility remains a challenge after the COVID-19 pandemic.

The lack of positive web accessibility performance by universities around the world is significant. Persons with visual impairment are most affected, as low contrast errors and lack of alternative text on images remain the main barriers to equal web access for persons with disabilities. Universities provide knowledge to society and should be committed to facilitating universal access in the information society. As institutions of advanced learning, universities should be concerned with the equal access and active participation of potentially all citizens in the Information Society.

The fact that the web accessibility of the universities selected in this study changed immediately after the end of the COVID-19 pandemic confirms that web accessibility is an ongoing issue. Therefore, this study emphasises the need to approach web accessibility in a proactive rather than reactive mode in order to ensure continuous improvement. In this way, the web of higher education institutions will always be perceivable, usable, understandable and robust, in line with the principles of WCAG, Article 9 of the CRPD and Goal 4 of the UN-SDGs.

The reasons for this drop in web accessibility scores after the end of the COVID-19 pandemic need to be investigated. However, on the one hand, it may be due to a decline in the following three variables of the DARE index [ 12 ], which are country commitments (laws, regulations, policies and programs), country implementation capacity (organisation, processes, resources) and actual digital accessibility outcomes for persons with disabilities in 10 areas of products and services [ 12 ]. However, there are no data available for the DARE index from 2020, and its evolution from 2018 to 2020 is positive. On the other hand, the decline in web accessibility performance in the post-COVID-19 era may also be due to a lack of funding; the World Bank’s index of government expenditure on education has declined globally since 2018 [ 54 ]. However, the available data go up to 2021, so this hypothesis needs to be analysed and confirmed by further studies in the future.

This study has a number of limitations. Firstly, it does not evaluate the accessibility of all the universities of the five continents of the world, but focuses on a selection of universities. Therefore, the results should be taken as indicators of web accessibility performance in a given period. Secondly, the variables analysed in the study, web accessibility scores, errors, contrast errors and ARIA implementation, are not separated because the main objective of the study is to evaluate the trend of web accessibility performance over a period of time. Therefore, the study is not intended to highlight which specific WCAG principle or technique is being violated the most, as there are other studies that do this. This study is more focused on providing web accessibility performance indicators to stakeholders to help them understand the importance of continuous improvement of web accessibility in higher education institutions. Finally, this study is not intended to explain the reason for the decline in web accessibility compliance performance of higher education institutions after the end of the COVID-19 pandemic. There may be other factors at play that require further correlational studies.

This study can be extended in the future by conducting a hybrid evaluation, combining AWAETs and manual validation by web accessibility experts to improve the accuracy of the results. Furthermore, this research could also be extended by including more universities and variables in the study, such as the Human Development Index (HDI) and the DARE, government spending on education, and analysing their correlations with web accessibility scores.

Data availability

The datasets generated during and/or analyzed during the current study are available from https://data.mendeley.com/datasets/jthx28w7dn/1

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Nso-Mangue, P., Cachero-Castro, C., Meliá, S. et al. Impact of COVID-19 in the web accessibility of higher education institutions: a pending challenge. Univ Access Inf Soc (2024). https://doi.org/10.1007/s10209-024-01149-4

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Accepted : 03 September 2024

Published : 17 September 2024

DOI : https://doi.org/10.1007/s10209-024-01149-4

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