essay on teachers during lockdown

ORIGINAL RESEARCH article

How teachers conduct online teaching during the covid-19 pandemic: a case study of taiwan.

• Department of Science Communication, National Pingtung University, Pingtung, Taiwan

Although online teaching has been encouraged for many years, the COVID-19 pandemic has promoted it on a large scale. During the COVID-19 pandemic, students at all levels (college, secondary school, and elementary school) were unable to attend school. To maintain student learning, most schools have adopted online teaching. Therefore, the purpose of this study was to explore the design of online teaching activities and online teaching processes adopted by teachers at all levels during the pandemic. Online questionnaires were administered to teachers in Taiwan who had conducted online teaching (including during the formal suspension of classes or simulation exercises) due to the pandemic. According to a quantitative analysis and lag sequential analysis, the instructional behaviors most frequently performed by teachers were roll calls, lectures with a presentation screen, in-class task (assignment) allocation, and whole-class synchronous video-/audio-based discussion. Thus, there were six common significant sequential behaviors among teachers at all levels that were categorized into the four instructional stages of identifying the teaching environment, teaching the class, discussing and evaluating learning effectiveness. College teachers reminded students of some matters first and then called the roll after the students went online. Secondary school teachers were more likely to arrange practical or experimental courses and to use synchronous and asynchronous interactive activities. Finally, elementary school teachers were more likely to use homemade videos and share their screens for teaching and to arrange a large variety of teaching interactions. The differences among colleges, secondary schools, and elementary schools were identified, and suggestions were made accordingly.

Introduction

Since 1990, Internet-based distance teaching has become a global trend, and software, hardware and educational training have been evolving. Nouns related to e-learning, such as online learning, distance teaching, digital learning, mobile learning and recent massive open online courses (MOOCs), have shown a trend of learning via the Internet. However, despite active promotion by governments, there are still many limitations to the online educational environment from teaching and learning perspectives ( Meskhi et al., 2019 ; Sadeghi, 2019 ), such as the support of the administrative system, the establishment of a network bandwidth and teachers’ willingness to record e-Learning materials.

Since the first report of coronavirus disease 2019 (COVID-19) in Wuhan (China) in December 2019, COVID-19 has rapidly spread worldwide ( Zhu et al., 2020 ). The World Health Organization (WHO) declared a public health emergency of international concern on January 30, 2020 and named the disease COVID-19 on February 11, 2020. On March 11, 2020, the WHO declared COVID-19 a global pandemic ( Singhal, 2020 ; World Health Organization, 2020 ).

Due to the respiratory illness caused by COVID-19, many countries have suspended all types of face-to-face activities, including in-person education. The COVID-19 pandemic has forced many changes in most life domains to meet the repercussions of the pandemic control measures, and the education sector was no exception. In many countries, colleges, secondary schools and elementary schools have adopted the strategy of online education during the pandemic. As a result, teachers and students have had to quickly alter their teaching methods, regardless of whether they were experienced in and prepared for online education. Because of this situation, a proper term has appeared in the academic domain: emergency remote education.

Online education-related studies and models have been promoted for years ( Sun and Chen, 2016 ). Before the COVID-19 pandemic, most of these studies were focused on colleges, while teachers and students in elementary and secondary schools remained inexperienced in emergency remote education ( Lestari and Gunawan, 2020 ). For example, Taiwan has promoted digital course certification at the university level for many years, and universities have also supported teachers in recording e-learning materials. Therefore, university teachers are more experienced in online teaching. However, in primary and secondary schools, digital teaching plays only a supplementary role. The pre-epidemic model is for students to go to classrooms. Therefore, teachers in primary and secondary schools have insufficient experience in switching to online teaching.

In response to COVID-19, schools at all levels needed an immediate shift towards online education, which can be both an opportunity and a challenge ( Toquero, 2020 ). Therefore, some studies have been conducted to discuss emergency remote education during the COVID-19 pandemic. For example, Crawford et al. (2020) investigated 20 countries’ responses to the COVID-19 epidemic. They pointed out that the response to higher education is diverse, including nonresponse, campus social isolation strategies, and rapid response to fully online courses. Watermeyer et al. (2020) reported a survey from 1,148 academics working in universities in the United Kingdom. They suggested that online migration is engendering significant dysfunctionality and disturbance to their pedagogical roles and their personal lives. Loima (2020) compared socio educational policies and arguments in Sweden and Finland during the COVID-19 pandemic. The results showed that Swedish and Finnish policy obscured mandates and restricted information. However, remote learning was successful in epidemiologic and curricular senses in Finnish. Basilaia and Kvavadze (2020) conducted a case study in Georgia. The Google Meet platform was implemented for online education with 950 students. The results indicated that the quick transition to the online form of education went successful and that gained experience can be used in the future. Putra et al. (2020) visited 10 websites in Indonesia to explore students’ learning experiences during the COVID-19 pandemic. The results showed that student hardship in learning from home caused a lack of learning resources, such as not accessing the Internet and parents’ ability to support their children’s learning. In Cyprus, Souleles et al. (2020) believed that e-learning is not an add-on to existing teaching and learning practices and that disciplinary differences need to be considered. The provision of hurriedly set up workshops to enhance the skill gaps of teachers, although it is a necessary step, cannot replace the need for sustained training in both the pedagogical and technical areas. In Norway, Langford and Damsa (2020) discovered some phenomena, such as the Zoom revolution, a significant level of interactive online learning, innovations for involuntary teaching reform, collegial competence building and self-help, technological challenges and pedagogical insecurity. In Beijing, when the outbreak prevented people from going to school, the scholars of Peking University proposed the following five specific teaching strategies for online education in pandemic circumstances: 1) a high relevance between online instructional design and student learning; 2) the effective delivery of online instructional information; 3) adequate support provided by faculty and teaching assistants to students; 4) high-quality participation to improve the breadth and depth of students’ learning; and 5) contingency plans to address unexpected incidents on online education platforms ( Bao, 2020 ). In addition, many scholars in medical education have explored the challenges and future of online education in their own field. For example, Goh and Sandars (2020) indicated that major changes have been taking place in global medical education and that it is necessary to strengthen technological innovation to maintain teaching; they proposed that the use of artificial intelligence for adaptive learning and virtual reality might be future trends in medical education.

In addition to the abovementioned studies on overall education, there have been more studies that explore students’ opinions during emergency remote education. Abbasi et al. (2020) reported that when students were unable to go to school because of the epidemic, they did not like online learning as much as face-to-face teaching. Thus, school administrative departments and teachers should take the necessary measures to improve online educational environments. Based on a survey of 77 medical students in their classroom situations, Agarwal and Kaushik (2020) argued that students believed that online courses altered their normal procedures, saved a large amount of time and made it easy for them to obtain teaching materials. The main barriers to learning were the number of participants and technical failures during class conversations. Owusu-Fordjour et al. (2020) investigated online learning among 214 college students and found that the pandemic had a negative effect on their learning because many of them were not used to learning effectively on their own. As most of the students in this region could not access the Internet and lacked the technical knowledge of Internet devices, the learning platforms that were used also posed a challenge for them.

Most of the above studies on students’ opinions focused on college education because college students’ abilities for self-regulated learning in online education are better than those of primary and secondary students because of their age ( Heo and Han, 2018 ). However, when the pandemic began, all schools faced the challenge of switching to emergency remote education. Some studies have explored learning issues in elementary and secondary schools during the outbreak. For example, Sintema (2020) noted that Zambian primary and secondary schools enabled teachers and students to have classes via mobile phones and tablets by implementing e-learning and smart revision portals while increasing the number of mobile devices available for use. The study found that these teaching and learning methods helped teachers deliver teaching materials and students to be capable of self-regulated learning during the pandemic. In addition, Fauzi and Khusuma (2020) surveyed 45 elementary school students and identified problems in implementing online teaching, including 1) the availability of facilities, 2) network and Internet usage, 3) the planning, implementation, and evaluation of learning, and 4) collaboration with parents. The authors expected that online learning would be helpful to teachers during the COVID-19 pandemic, but their results indicated poor outcomes of online learning, with 80% of teachers reporting that they felt dissatisfied with online education.

Study Objectives

According to the abovementioned studies on the COVID-19 pandemic, teachers and students were forced to conduct online education regardless of their level of preparation for it. Most of the recent studies have investigated students’ feelings about online education and learning effectiveness, but there has been little discussion of teachers’ design of teaching activities when they had to switch to online teaching due to the pandemic. Accordingly, this study explored how teachers designed their teaching activities when they switched to online teaching due to the pandemic or how they conducted online teaching in the form of exercises to provide a reference for the future promotion of online education. As a result, the first objective of this study is to discuss teachers’ design of online teaching activity during the COVID-19 pandemic.

Moreover, our knowledge of teachers’ online teaching activities is based on online teaching activities in normal conditions. In addition, teaching activity plans are sequential ( Brown and Green, 2018 ). For example, Gagne’s model of instructional design includes 1) gaining attention, 2) informing the learner of the objective, 3) stimulating the recall of prerequisite learning, 4) presenting the stimulus material, 5) providing learning guidance, 6) eliciting the performance, 7) providing feedback, 8) assessing the performance, and 9) enhancing retention and transfer ( Khadjooi et al. (2011) . The second objective of this study is to explore which activities were carried out first and last and the order of teachers’ teaching activities. Thus, to understand the teaching activities adopted by teachers during the COVID-19 pandemic and the implementation of these teaching activities, this study used a lag sequential analysis to inform the discussion on this topic.

During the COVID-19 pandemic, students at all levels (college, secondary school and elementary school) were unable to attend school. Online teaching can continue to maintain learning activities when everyone is not going out. Therefore, to maintain students’ learning, most schools have adopted online teaching. In addition, for students of different ages, e.g., colleges, secondary schools and elementary schools, the teaching behaviors taken by teachers will be different ( Kennan et al., 2018 ). Understanding how teachers engage in online teaching behaviors at this emergency remote learning time can serve as a reference for the future promotion of e-learning. This study discusses teachers’ design of online teaching activity at all levels during the pandemic. The study explores the following two research questions:

What are the online teaching activities adopted by teachers due to the suspension of classroom teaching due to the COVID-19 pandemic? and

What are the similarities and differences among teachers from colleges, secondary schools and elementary schools in the design of their online teaching activity processes?

Methods and Materials

Data collection and participants.

This study mainly investigates teachers who had conducted online education (including during the formal suspension of classes and simulation exercises) because of the pandemic. Convenience sampling was adopted. Although many courses might have been changed to online teaching at the time that the teachers answered the questions, the study questionnaire asked about the teaching activity design of only one course. Data were collected from May 20 to June 30, 2020, by using a web-based questionnaire with a cross-sectional design. A total of 270 teachers answered the questionnaires, and 223 of the responses were valid. There were 23 college teachers (10.3%), 51 secondary school teachers (22.9%) and 149 elementary school teachers (66.8%).

In this study, a questionnaire on online teaching activities was developed based on the research purpose and some studies (i.e., Nilson and Goodson, 2017 ; Trust and Pektas, 2018 ; Sharoff, 2019 ). The questionnaire consisted of three major parts, namely, basic data (sex male and female), age (below 30 years old, 31–40 years old, 41–50 years old, 51–60 years old and over 61 years old), the served school (college or university, middle or high school, and elementary school), the years of teaching experience, online teaching experience (Were you experienced in online teaching prior to the pandemic (frequently, occasionally and never), Why did you conduct online teaching? (already in use, class suspension due to medical diagnosis and simulation exercises), and in most cases, which of the following methods do you choose for online teaching?) and the teaching process (synchronous teaching, asynchronous teaching and blended teaching). According to the various online teaching platforms and systems used (e.g., Google Classroom, iCAN, iLMS, Microsoft Teams, Moodle, Sunnet LMS, Adobe Connect, Cisco WebEx, CyberLink U Meeting, Google Meet, Jitsi Meet, JoinNet, LINE Chat, Zoom, YouTube Live broadcast, Facebook Live broadcast and Zuvio), the teaching processes were analyzed, summarized and then divided into the 4 categories of teaching (A), learning interaction (B), learning effectiveness (C) and others (D). After the online teaching activity questionnaire was prepared, three experts in online college education, one elementary school teacher, and one online education administrator of the education agency were invited to assist in the review of the questionnaire. The survey questionnaire was refined according to the suggestions received through the experts’ review. The instructional behaviors that comprise the teaching process are listed below.

 A1 Lecturing–presentation screen. A2 Lecturing–blackboard. A3 Sharing a screen with computer software. A4 Playing videos made by teachers. A5 Playing videos made by others. A6 Practical (experimental) demonstration.

B Learning Interaction

 B1 Whole-class synchronous text-based discussion. B2 Whole-class asynchronous text-based discussion. B3 Whole-class synchronous video-/audio-based discussion. B4 Whole-class asynchronous video-/audio-based discussion. B5 Whole-group synchronous text-based discussion. B6 Whole-group asynchronous text-based discussion. B7 Whole-group synchronous video-/audio-based discussion. B8 Whole-group asynchronous video-/audio-based discussion. B9 Whole-class whiteboard interaction. B10 Whole-group whiteboard interaction. B11 Student self-practice. B12 Operation by remote control. B13 Data collection and collation.

C Learning Effectiveness

 C1 In-class study experience. C2 In-class task (assignment) allocation. C3 In-class online test. C4 In-class online questionnaire. C5 In-class peer evaluation. C6 In-class work submission. C7 In-class assignment/work report. C8 After-class study experience. C9 After-class task (assignment) allocation. C10 After-class online test. C11 After-class online questionnaire. C12 After-class peer evaluation/voting. C13 After-class work submission.

 D1 Roll call D2 Inquiry about the status of hardware and software. D3 Reminders of other noncourse matters. D4 Others.

Data Analysis

In this study, descriptive statistics were used to analyze the basic data, the online teaching experience and the first research question. The second research question was analyzed through a lag sequential analysis ( Bakeman and Gottman, 1997 ). Lag sequential analysis ( Bakeman and Gottman, 1997 ) is used not only to explore a continuous sequence of behavioral coding categories (namely, an online teaching process) in which an initial behavioral coding category is followed by a subsequent category but also to visualize behavioral patterns. Researchers have mainly applied this method to the analysis of education issues. For example, Lin et al. (2020) developed a scaffolding-based collaborative problem-solving (CPS) learning environment to improve students’ learning in CPS activities. According to the study results, the learning performance was significantly better for the scaffolding mind tool group than for the study sheet group, and the scaffolding mind tool group showed more diverse cognitive process transitions in their behavioral patterns. Zarzour et al. (2020) investigated the behavioral patterns of students by using eBooks on Facebook for learning. The experimental results indicated significant behavioral learning sequences and revealed that the behaviors of liking, commenting, and sharing posts with peers showed the most significant differences between the students with higher and lower engagement. Wang and Liu (2020) discussed teachers’ current online teaching and students’ interaction and collaborative knowledge construction. According to the results, the design and organization of learning materials and the facilitation of discourse promoted students’ interaction, reduced the number of peripheral students, and supported students’ collaborative knowledge construction.

The following were the five steps in the lag sequential analysis: 1) calculating the number of transitions among the behavioral codes to obtain the transition frequency table; 2) calculating the conditional probability of the transitions among the codes based on the above sequential frequency matrix to produce the sequential transition conditional probability; 3) calculating the expected value of the overall transition process among the codes based on the sequential frequency matrix; 4) verifying whether all sequences were significantly continuous one-by-one based on the Z-score values of the transition frequency calculated from the above three matrices (adjusted residuals table); and 5) drawing the sequence transition association diagram with nodes that represent all coding behaviors connected by arrows for further inferential analysis.

Results and Discussion

Basic data and online teaching experience.

The Google online questionnaire was adopted in this study, and all questions must be answered to be valid. As shown in Table 1 , a total of 223 valid questionnaires were collected in this study. In terms of sex, there were 100 males (44.8%) and 123 females (55.2%), and there was virtually no difference in the numbers of males and females. Therefore, this study is not affected by gender differences. Regarding age, there were 23 people (13.3%) under 30 years old, 24 people (10.8%) between 31 and 40 years, 57 people (25.6%) between 41 and 50 years, 106 people (47.5%) between 51 and 60 years, and 36 people (16.1%) aged 61 years or over. Most of the respondents were between 41 and 60 years old. In the quartile of age, Q1 was 31–40 years, and Q2 (median) and Q3 were 41–50 years. Regarding the years of teaching experience, there were 12 teachers (5.4%) with less than 1 year of service, 26 teachers (11.7%) with 1–5 years of service, 21 teachers (9.4%) with 6–10 years of service, 54 teachers (24.2%) with 11–15 years of service, 57 teachers (25.6%) with 16–20 years of service, and 53 teachers (23.8%) with more than 21 years of service. In the quartile of teaching experience, Q1 is 1–5 years, Q2 (median) is 16–20 years, and Q3 is more than 21 years. Most teachers were found to have many years of experience. At the school level, there were 23 college teachers (10.3%), 51 secondary school teachers (22.9%), and 149 elementary school teachers (66.8%). Thus, most of the respondents were elementary school teachers, followed by secondary school teachers.

TABLE 1 . Participants’ characteristics, including their online teaching experience.

Then, the study examined whether teachers were experienced in online teaching prior to the pandemic. Fourteen teachers (6.3%) had frequently engaged in online teaching, 79 (35.4%) had engaged in it occasionally, and 130 (58.3%) had never engaged in it, which shows that more than half of the teachers had no experience in online teaching. As a result, the reason why online teaching had been adopted was explored. In total, 21 teachers had been teaching online prior to the pandemic (9.4%), seven taught online due to a medical diagnosis (3.1%), and 195 taught online as a part of simulation exercises (87.4%); these findings show that the primary reason for switching to online teaching was simulation exercises, as the COVID-19 pandemic in Taiwan was well controlled. Regarding the modes frequently used in online teaching, 89 teachers (39.9%) used synchronous teaching (teachers and students go online at the same time to carry out teaching and learning activities), 65 teachers (29.1%) used asynchronous teaching (teachers upload teaching materials to the network platform, and students can watch them online within a specified time and carry out learning activities), and 69 teachers (30.9%) used blended teaching (teaching and learning activities that combine both synchronous and asynchronous modes); thus, similar proportions of the teachers used the three teaching modes.

Teaching Activities

The 223 teachers who returned valid questionnaires had a total of 1,310 instructional behaviors, with an average of 5.87 instructional behaviors for each teacher. Table 2 shows the overall instructional behaviors, and the number and percentage of instructional behaviors in elementary schools, secondary schools, and colleges.

TABLE 2 . Number and percentage of various instructional behaviors.

Overall, there were 329 data points (25.11%) for teaching (A), 340 data points (25.95%) for learning interaction (B), 383 data points (29.24%) for learning effectiveness (C), and 258 data points (19.69%) for others (D). The proportion of other instructional behaviors was similar to but slightly lower than the proportions of the remaining three teaching categories. Among the four teaching categories, the top four behaviors were roll call (D1) with 132 data points (10.08%), lecturing with a presentation screen (A1) with 124 data points (9.47%), in-class task (assignment) allocation (C2) with 104 data points (7.94%), and whole-class synchronous video-/audio-based discussion (B3) with 103 data points (7.86%). Thus, the most common behavior in each category was teaching behavior.

Then, the four teaching categories were analyzed from an overall perspective. In teaching (A), lecturing with a presentation screen (A1) was the most frequently used ( N = 124, 9.47%), followed by sharing a screen with computer software (A3) (N = 101, 7.71%); this shows that most teachers frequently lectured with a presentation screen and shared their computer screens in online teaching. In learning interaction (B), whole-class synchronous video-/audio-based discussion (B3) was the most frequently used ( N = 103, 7.86%), followed by student self-practice (B11) ( N = 82, 6.26%); this indicates that the teachers often conducted a whole-class synchronous discussion after teaching and allowed students to become familiar with the teaching content through their own practice. In addition, we also found that the teachers conducted more activities in entire classes than in groups. Although group learning is a common teaching activity in classroom teaching, in the online teaching environment, group interaction is rarely adopted by teachers because of the limitations imposed by the functional design of the learning platform or system. In learning effectiveness (C), the most common and second-most common instructional behaviors both concerned task (assignment) allocation, including class-task (assignment) allocation (C2) with 104 data points (7.94%), and after-class task (assignment) allocation (C9) with 69 data points (5.27%). By comparing all behaviors in class and after class, we found that the frequency of all in-class behaviors ( N = 224, 17.11%) was larger than the frequency of after-class behaviors ( N = 159, 12.14%), which suggests that the teachers mostly evaluated teaching effectiveness in class. Finally, in the other category (D), the most common mode was roll call (D1) with 132 data points (10.08%), followed by inquiry about the status of hardware and software (D2) with 74 data points (5.65%). These two items were important preclass activities in online teaching, although they do not take much time in classroom teaching.

Finally, the study explored the similarities and differences among colleges, secondary schools, and elementary schools in the four categories. In terms of teaching (A), we found that lecturing with a presentation screen (A1) was the most frequently used, followed by sharing a screen with computer software (A3), regardless of the learning stage. In terms of playing videos, we found that most videos played in colleges were made by teachers (A4), while the videos played in secondary and elementary schools were made by others (A5); this shows that college teachers were more likely to make course videos for students to watch. Practical (experimental) demonstration (A6) was the least used. Although physical education courses and experimental courses still existed in the curriculum, the teachers seldom performed practice or experiments in the online teaching environment. In terms of learning interaction (B), we found that whole-class synchronous video-/audio-based discussion (B3) was the most frequently used, regardless of the learning stage. Moreover, unlike student practice (B11), whole-class synchronous text-based discussion (B1) was frequently used in colleges and secondary schools but was less frequently used in elementary schools, while whole-class whiteboard interaction (B9) was frequently used in elementary schools; this indicates that the teachers were more likely to arrange synchronous text-based discussion activities for older students. Finally, we found that data collection and collation (B13), a common activity in online teaching, was used in some secondary and elementary schools but not in colleges. In terms of learning effectiveness (C), we found that task (assignment) allocation (C2 and C9) was the most frequently used, regardless of the learning stage. Second, assignment and work reports (C7 and C13) were commonly used by college teachers for evaluation, online tests (C3 and C10) were commonly used by secondary and elementary teachers for evaluation, and there was almost no difference in their use between online teaching and the current situation in classroom teaching. In terms of the other category (D), based on the proportions of teachers who used the behaviors, we found that the most common behaviors were roll calls (D1), inquiries about the status of hardware and software (D2), and reminders of other noncourse matters (D3), regardless of the learning stage. These behaviors were important for online teaching, but the questionnaire did not dedicate many questions to these behaviors.

Teaching Behavioral Sequence

During the lag sequential analysis, the adjusted residuals table was calculated, where the columns represent initial behaviors, and the rows signify the behaviors that occurred immediately after the behaviors listed in the columns. A Z-score greater than 1.96 indicated that the sequence was significant. In this study, there were 49, 58, and 104 significant behavioral sequences for colleges, secondary schools and elementary schools, respectively (as shown in the Supplementary Appendix ). With the 36 instructional behaviors examined in this study, there were many significant behavioral sequences in each learning stage. To facilitate the discussion, the common significant behavioral sequences of colleges, secondary schools, and elementary schools were first extracted, and six significant behavioral sequences were identified in total. Second, to compare the differences among colleges, secondary schools, and elementary schools in the teaching process, significant behavioral sequences with Z-score values greater than five were discussed. There were 11, 10, and 15 significant behavioral sequences with Z-score values greater than five in colleges, secondary schools and elementary schools, respectively. The values shown in Table 3 are the Z-scores.

TABLE 3 . Significant behavioral sequences (similarities and differences Z-score>5).

There were six common significant behavioral sequences in colleges, secondary schools, and elementary schools ( Figure 1 ). The six significant behavioral sequences were divided into four stages. The first stage included roll calls and the confirmation of an effective online teaching environment (D1→D2). The next stage was teaching the class. The common teaching methods were presentation (A1) and screen sharing (A3). The next stage after teaching included text-based synchronous discussion (A1→B5 and A3→B1). The final stage was the evaluation of learning effectiveness (B5→C7 and C3→C4). Overall, the common significant behavioral sequences in colleges, secondary schools and elementary schools, namely, identifying the teaching environment, teaching the class, discussing and evaluating learning effectiveness, were similar to the usual teaching processes.

FIGURE 1 . Overall behavioral transfer diagram.

Then, the characteristics of the teaching processes in colleges, secondary schools and elementary schools were compared based on the significant behavioral sequences with Z-score values greater than 5. To provide a basis for comparison, the abovementioned phases, i.e., 1) identifying the teaching environment, 2) teaching the class, 3) discussing and 4) evaluating learning effectiveness, were used for discussion. First, colleges ( Figure 2 ) were more likely than secondary and elementary schools to use the following sequence: reminders for students of other noncurriculum matters (D3) → roll call (D1). This may be because, compared with secondary and elementary school teachers, college teachers are more likely to call roll after reminding students of matters during class and waiting for students to go online. This not only presents the actual situation of the physical classroom but also represents the teacher’s differences in class management for students of different ages. In the teaching class stage, there was one common behavioral sequence between college teachers and elementary school teachers, namely, lecturing with a blackboard (A2) → practical (experimental) demonstration (A6). This may be because some experimental course teachers are used to lecture with a blackboard and directly filme experimental courses with cameras. In the discussing stage, college teachers engaged in less interactive learning behaviors than secondary and elementary school teachers, but most of their behaviors were carried out in groups (A5→B6, B5→B10, B10→B3). Finally, in the evaluating learning effectiveness stage, college teachers had more diversified evaluation methods, including practice, tests, and questionnaires. Moreover, college teachers arranged many in-class and after-class evaluations (C1→C12, C3→C12 and C4→C12).

FIGURE 2 . Behavioral transfer diagram for colleges.

Second, in secondary schools ( Figure 3 ), teachers were more likely to arrange practical or experimental courses and then carry out interactive activities such as discussions or questionnaires (A6→B2, A6→B4 and A6→C11). In conducting interactive activities, teachers in secondary schools were more likely to use synchronous and asynchronous methods than teachers in colleges or elementary schools. Finally, in the stage of evaluating learning effectiveness, secondary school teachers had more diversified evaluation methods than college or elementary school teachers, including tests, questionnaires, and practice.

FIGURE 3 . Behavioral transfer diagram for secondary schools.

In elementary schools ( Figure 4 ), teachers were more likely to use homemade videos and share their screens while teaching and then conduct discussions (A3→B3, A5→B2, A5→B7). The teaching interactions arranged by elementary school teachers were diversified, and discussions containing audio and text were conducted with synchronous and asynchronous methods. Elementary school teachers, similar to college and secondary school teachers, used a variety of evaluation methods. In addition, elementary school teachers arranged many in-class evaluations, and after-class assignments, which is similar to general classroom teaching.

FIGURE 4 . Behavioral transfer diagram for elementary schools.

Discussion and Conclusion

During the COVID-19 pandemic, students at all levels (colleges, secondary schools, and elementary schools) were unable to attend school, and most schools switched to online teaching. To understand the design of online teaching activities among teachers at all levels, online questionnaires were adopted in this study to investigate teachers in Taiwan who had conducted online teaching due to the pandemic. There were 223 valid questionnaires.

The first objective was to explore teachers’ online teaching activities when classroom teaching was suspended due to COVID-19. Based on the results of the frequencies of behaviors in the teaching, learning interaction, learning effectiveness and other categories, the top four instructional behaviors were roll calls, lecturing with a presentation screen, in-class task (assignment) allocation and whole-class synchronous video-/audio-based discussion. Then, the study explored the similarities and differences among colleges, secondary schools, and elementary schools in the four categories. In terms of teaching, lecturing with a presentation screen was the most frequently used, regardless of the learning stage. In terms of playing videos, most videos played in colleges were made by teachers, while most videos played in secondary and elementary schools were made by others. In terms of learning interaction, we found that whole-class synchronous video-/audio-based discussion was the most frequently used, regardless of the learning stage. In addition, teachers’ arrangement of synchronous text-based discussions depended on the learning level. In terms of learning effectiveness, task (assignment) allocation was the most frequent behavior, regardless of the learning stage. Second, assignments and work reports were commonly used by college teachers for evaluation, while teachers in secondary and elementary schools were more likely to use online tests for evaluation. Finally, in terms of the other category, we found that roll calls and inquiries about the learning environment, such as the status of hardware and software, were necessary for online teaching, regardless of the learning stage.

Overall, more time was spent on roll calls and inquiries about the status of hardware and software in online teaching than in classroom teaching. This means that teachers’ technical capabilities for online teaching, students’ familiarity with digital platforms, and the software and hardware assistance provided by the school’s information center will all affect the quality of e-learning. Moreover, in terms of teaching, interaction and evaluation, the arrangement of these activities among teachers at all levels was slightly different from the arrangement of these activities in classroom teaching, and appropriate teaching activities could be designed according to the online teaching environment. Despite the limitations of online teaching platforms, online learning activities can still be carried out.

The second objective of this study was to explore the similarities and differences among college, secondary school and elementary school teachers in the design of the online teaching activity process. According to the sequential behavioral analysis, the common significant behavioral sequences of colleges, secondary school and elementary schools were divided into 1) roll calls and identification of the teaching environment, 2) teaching through presentation and screen demonstration, 3) synchronous text-based discussion, and 4) an effectiveness evaluation. Overall, the common significant behavioral sequences of colleges, secondary schools and elementary schools were similar to the usual teaching processes. In terms of the characteristics, some college teachers reminded students of some matters first and then called the roll after students went online. During class, some teachers in experimental or practical courses were used to lecture with a blackboard, and directly filme experimental courses with cameras. Moreover, college teachers engaged in less interactive learning behaviors, but most of their behaviors were carried out in groups. Second, secondary school teachers were more likely to arrange practical or experimental courses and to use synchronous and asynchronous interactive activities. Finally, elementary school teachers were more likely to use homemade videos and share their screens for teaching and to arrange a large variety of teaching interactions; in addition, discussions containing audio and text were conducted with both synchronous and asynchronous methods.

Overall, colleges, secondary schools, and elementary schools had common significant sequential behaviors, including roll calls and the identification of the teaching environment, teaching through presentation and screen sharing, synchronous text-based discussion and an effectiveness evaluation. Moreover, college, secondary, and elementary school teachers had similar characteristics in the design of their teaching activity processes. In addition to these similar characteristics, college, secondary, and elementary school teachers also have some different characteristics. These different characteristics show that teachers at different stages of learning vary in their teaching strategies. These differences, in addition to showing the current teaching situation, can also provide scholars with information for related follow-up research.

According to the conclusions generated based on the descriptive analysis and lag sequential analysis, the following suggestions can be made.

Despite the small proportion of online practical and experimental courses, as evidenced by the observed online instructional behaviors, such courses are arranged in classroom teaching. It is suggested that when relevant, teachers should consider in advance how to respond to challenges in implementing practical and experimental courses in online teaching.

Discussion is more important in the online teaching environment than in general classroom teaching ( Wu, 2016 ). This study found that whole-class synchronous video-/audio-based discussion was the most frequently used method. Thus, whether activities are conducted as a class or in groups and whether synchronous or asynchronous discussion is used, teachers should improve the online discussion layout and their online leadership skills ( Tseng et al., 2019 ).

In classroom teaching, problem-based learning (PBL) courses are often arranged, which require students to collect and collate data through the Internet ( Dolmans et al., 2016 ). However, in this study, the rate of data collection and collation was low, even in the online education environment, but the activities of data collection and collation in the online learning environment are more suitable for adoption. Therefore, it is suggested that teachers should design activities of data collection and collation for more diversified teaching activities.

Due to the pandemic, people have been restricted in their ability to leave home. Therefore, in addition to the synchronous activities in class during teaching time, it is suggested that teachers arrange after-class asynchronous activities so that students can carry out learning activities when they cannot go out.

In classroom teaching, it does not take much time to call roll or manage hardware and software. However, the two behaviors are important in the online teaching environment. Thus, both teachers and learning platforms or system developers should think about how to reduce the time spent on roll calls and the management of hardware and software.

In terms of the research limitations and suggestions for future studies, this study took Taiwan’s teachers as an example; it is suggested that cross-country comparisons be carried out in future studies. Second, this study mainly discussed the situations, similarities and differences of colleges, secondary schools and elementary schools in the teaching activities and processes affected by the pandemic. However, teaching activities are also influenced by the course that is being taught. Thus, it is suggested that future researchers base their discussions on various types of courses. Finally, teachers’ preparation for online teaching affects the quality of online education ( Hung, 2016 ), which was not analyzed in this study. Therefore, it is suggested that future researchers compare the differences in teachers’ experiences with online teaching.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author Contributions

The author contributed to the conception of the idea, implementing and analyzing the experimental results, and writing the manuscript.

Conflict of Interest

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

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2021.675434/full#supplementary-material

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Keywords: COVID-19, e-learning, online teaching, lag sequential analysis (LSA), emergency remote education (ERE)

Citation: Wu S-Y (2021) How Teachers Conduct Online Teaching During the COVID-19 Pandemic: A Case Study of Taiwan. Front. Educ. 6:675434. doi: 10.3389/feduc.2021.675434

Received: 03 March 2021; Accepted: 06 May 2021; Published: 28 May 2021.

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*Correspondence: Sheng-Yi Wu, [email protected]

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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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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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Rita Takács & Zoltán Horváth

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Szabolcs Takács

Károli Gáspár University of the Reformed Church in Hungary, Budapest, Hungary

Doctoral School of Education, ELTE Eötvös Loránd University, Budapest, Hungary

Judit T. Kárász

Institute of Education, ELTE Eötvös Loránd University, Budapest, Hungary

Doctoral School of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary

Attila Oláh

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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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The changing role of teachers and technologies amidst the COVID 19 pandemic: key findings from a cross-country study

Maria barron, cristóbal cobo, alberto munoz-najar, inaki sanchez ciarrusta.

“Whoever teaches learns in the act of teaching and whoever learns teaches in the act of learning" wrote the Brazilian pedagogue Paulo Freire in his famous book “Pedagogy of Freedom” (1996). 

Despite the overwhelming consequences of the pandemic, this global crisis has also been an extraordinary time for learning. We are learning how adaptable and resilient educational systems, policy makers, teachers, students and families can be. In this blog (which is part of a series highlighting key lessons learned from a study to understand the perceived effectiveness of remote learning solutions, forthcoming) we summarize lessons learned in different countries, with special focus on teachers and how they had to quickly reimagine human connections and interactions to facilitate learning. The role of teachers is rapidly evolving becoming in many ways more difficult than when learning took place only in person. 

How has the pandemic changed the role of teachers?

Two crucial factors have shifted due to the pandemic. First, pedagogical adaptations have proven to be pivotal as the traditional lecturing in-person models do not translate to a remote learning environment. No matter the type of channel used (radio, TV, mobile, online platforms, etc.) teachers need to adapt their practices and be creative to keep students engaged as every household has become a classroom - more often than not - without an environment that supports learning. Some countries are supporting teachers with this. In Sierra Leone , where the main remote learning channel is radio, a ‘live’ and toll-free phone line is open for students to call teachers with questions and schedules of radio lessons allow time for children to help their families with daily chores.

Second, the pandemic has recalibrated how teachers divide their time between teaching, engaging with students, and administrative tasks. In Brazil according to a survey conducted by Instituto Peninsula, 83% of teachers did not consider being prepared to teach remotely, 67% were anxious, 38% felt tired, and less than 10% were happy or satisfied. The pandemic has highlighted the need for flexibility and more time for student-teacher interactions. For example, in Estonia teachers were given autonomy to adjust the curriculum, lesson plans, and their time allocation. 

How systems have supported teachers in their new role?

Almost 90% of countries that responded to the survey of Ministries of Education on National Responses to COVID-19 conducted by UNESCO, UNICEF, and the World Bank (2020) supported teachers by sharing guidelines stressing the importance of: providing feedback to students, maintaining constant communication with caregivers, and reporting to local education units to keep track of learning. Fewer governments took a different approach: Costa Rica developed a digital toolbox with pedagogical resources such as a guide for autonomous work, the state of São Paulo in Brazil organized frequent two-hour conversations between Secretary Rossieli Soares and teachers  through the mobile application developed by the state. These conversations and tools allowed governments to have an open line of communication with teachers to better understand their concerns and adjust remote learning programs.

As teachers started to implement these guidelines and recommendations, they found themselves balancing educating and providing feedback to students remotely, filling administrative reports, and taking care of their families. Some governments recognized early-on that their well-intentioned teacher support systems ended up generating burnout. Peru’s Ministry of Education was open to receive feedback and reacted rapidly by changing the guidelines to reduce teacher’s administrative workload. The state of Minas Gerais in Brazil developed the mobile application ‘Conexao Escola’ to encourage teacher-student interaction during designated time after each class, avoiding a situation in which students contacted teachers through WhatsApp or text message throughout the day. In Uruguay, teachers were expected to fill administrative information, but instead of requesting new information from them, the government decided to use GURI, a digital platform that has been used by Uruguayan teachers for over 10 years to report information such as student attendance and grades.

Beyond providing guidelines and tools, some governments have leveraged existing professional development programs that worked before the pandemic. The state of Edo in Nigeria trained all 11 thousand primary school teachers who are part of the Edo-BEST program in the past two years to effectively use digital technologies in the classroom; during the pandemic, this in-service teacher training program transitioned from in-person to remote training. Similarly, in Uruguay, The Institute for in-Service Teacher Training took an existing coaching program online to provide remote pedagogical support and Ceibal strengthened its teacher training program and Open Educational Resources repository. While over 90% of Uruguayan teachers were satisfied with the remote training received during the pandemic, some expressed the need for further training.

What impact have technologies generated in this changing role?  

Faced with the pandemic, countries have combined high-tech and low-tech approaches to help teachers better support student learning . In Cambodia, for example, education leaders designed a strategy that combines SMS, printed handouts, and continuous teacher feedback , taking advantage of the high mobile phone penetration in the country. The approach goes beyond providing low-tech materials: it gives information on how to access learning programs, ensures students access paper-based learning materials, and includes home visits to monitor distance learning activities. Teachers are also expected to provide weekly paper-based resources to students and meet them weekly to provide their marked worksheets and issue new ones for the week ahead.  

Technology has also enhanced government-teacher support , adapting existing coaching programs to be delivered remotely (as the mentioned cases of Nigeria and Uruguay), creating spaces for peer support programs (for example the Virtual EdCamps initiative, created to facilitate peer-to-peer learning among teachers) or establishing EdTech hotlines for teachers (like in Estonia, where the HITSA – the Information Technology Foundation for Education - opened an educational technology information line to solve any technological question teachers might have).

Technology interventions should enhance teacher engagement with students , through improved access to content, data and networks, helping teachers better support student learning, as laid out in the World Bank’s Platform for Successful Teachers , where effective use of technology is one of the key principles to ensure cadres of effective teachers. 

How policymakers can support teachers during the reopening of schools?

In order to build back stronger education systems, countries will need to apply those teaching initiatives that have proved to be effective during the remote learning phase and integrate them into the regular education system. It is critical to empower teachers , investing in the necessary skills development and capacity building to exploit the full potential of remote and blended learning. 

Equally important is to free teachers’ time from administrative tasks (as Brazil, Peru and Uruguay did), focus on what is pedagogically effective, and provide socio-emotional support for teachers.  The pandemic and the extended school closures have changed the role of teachers and most of them were not prepared for such change; a comprehensive strategy is required for socio-emotional monitoring and psychosocial support to ensure teacher wellbeing and avoid burnout.

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Essay on Role of Teachers During Lockdown

Students are often asked to write an essay on Role of Teachers During Lockdown in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Role of Teachers During Lockdown

Introduction.

The Covid-19 pandemic led to worldwide lockdowns, affecting education. Teachers played a key role during this period.

Switching to Digital Education

Maintaining student engagement.

Teachers used innovative methods to keep students engaged. They organized online quizzes, debates, and interactive sessions.

Providing Emotional Support

Many students faced anxiety due to the pandemic. Teachers provided emotional support, helping students cope with the situation.

250 Words Essay on Role of Teachers During Lockdown

The COVID-19 pandemic has significantly disrupted the education sector, prompting an unprecedented shift to online learning. Teachers have played a pivotal role in this transition, ensuring that learning continues despite the challenges.

Transition to Online Learning

Teachers have had to swiftly adapt to online platforms, creating digital content and conducting virtual classes. They have become not just educators, but also tech-savvy facilitators, troubleshooting technical issues and helping students navigate online learning tools.

Student Engagement and Support

The lockdown has increased the risk of student disengagement. Teachers have taken on the role of mentors, closely monitoring student participation and performance. They have also provided socio-emotional support, recognizing the heightened stress and isolation students may be experiencing.

Collaboration and Innovation

The lockdown has also seen teachers collaborating more than ever, sharing resources and best practices. They have had to innovate, finding creative ways to engage students and simulate classroom dynamics virtually.

The role of teachers during the lockdown has been crucial in ensuring learning continuity. Their adaptability, resilience, and commitment have underpinned the education sector’s response to this crisis. As we navigate this new normal, their role will continue to evolve, shaping the future of education in profound ways.

500 Words Essay on Role of Teachers During Lockdown

The shift to remote learning.

The first and most obvious change in teachers’ roles during lockdown has been the shift to remote learning. As physical classrooms became inaccessible, teachers had to quickly become versed in various digital platforms to facilitate online learning. This ranged from learning to use video conferencing tools like Zoom or Google Meet, to creating and managing content on Learning Management Systems (LMS). The teachers’ role expanded to include that of a tech-support specialist, helping students and parents navigate the new digital learning landscape.

Adapting Pedagogical Approaches

The shift to online learning also required teachers to rethink their pedagogical approaches. Traditional teaching methods often do not translate well to a digital format, and teachers had to find innovative ways to engage students, maintain their motivation, and ensure they were learning effectively. This involved creating interactive lessons, incorporating multimedia elements, and using formative assessments to gauge student understanding in real-time.

Mental Health Advocacy

Building resilience and adaptability.

In conclusion, the role of teachers during lockdown has been multifaceted and complex, requiring them to adapt to new technologies, pedagogical approaches, and student needs. They have risen to the challenge, ensuring the continuity of education and supporting students’ wellbeing in these trying times. This period has highlighted the significance of teachers not just as providers of education, but as pillars of support and guidance for their students, demonstrating their irreplaceable value in society.

Apart from these, you can look at all the essays by clicking here .

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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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Effects of remote learning during COVID-19 lockdown on children’s learning abilities and school performance: A systematic review

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This systematic review describes the effects of COVID-19 lockdowns on children’s learning and school performance. A systematic search was conducted using three databases. A total of 1787 articles were found, and 24 articles were included. Overall, academic performance was negatively affected by COVID-19 lockdowns, with lower scores in standardized tests in the main domains compared to previous years. Academic, motivational, and socio-emotional factors contributed to lower performance. Educators, parents, and students reported disorganization, increased academic demands, and motivational and behavioral changes. Teachers and policymakers should consider these results in developing future education strategies.

1. Introduction

The Coronavirus Disease 2019 (COVID-19) pandemic has had severe global impacts, from the deaths of millions of people to worldwide economic crises. The spread of this unprecedented disease has forced communities into social isolation, changing the ways we relate and socialize with others. Since March 11, 2020, when the World Health Organization declared a global pandemic, the world has increasingly transitioned toward remote communication, placing a virtual interface between human interactions ( Cucinotta and Vanelli, 2020 ). Children have been profoundly affected by this sudden lifestyle change. With the closure of schools and colleges, learning and education have increasingly become screen-dependent, impacting children’s cognitive, social, and emotional development ( Alban Conto et al., 2021 , Haleemunnissa et al., 2021 ).

Although remote learning benefits disease control, it has augmented socioeconomic inequalities regarding access to technological resources ( Hossain, 2021 ). During the pandemic, low-income families tended to have less access to reliable internet and devices compared with high-income families in the same city ( Francis and Weller, 2022 ). Consequently, children from less privileged households spent fewer hours learning and were more likely to drop out of school ( The Lancet, 2021 , Zagalaz-Sánchez et al., 2021 ). Indeed, UNICEF reports that the impacts of the COVID-19 pandemic on children’s education in Ghana were marked by a lack of access to essential tools and learning materials (such as computers and textbooks) and inadequate conditions for effective learning (overcrowded households, poor or no access to electricity, and improper space for learning). These circumstances were more common in children living in rural and remote areas. Children with disabilities and physical or learning impairments were also affected ( Karpati et al., 2021 ). Furthermore, a lack of high-quality education impacts individuals’ health and income, as well as professional opportunities in the future, because of the bidirectional links between health and education ( The Lancet, 2021 ).

Moreover, several adverse effects of remote learning on children’s mental health have been identified, mostly related to the excessive use of electronic devices and lack of in-person contact with school classmates and teachers. These reported effects include disturbed sleep patterns, attention deficits, frustration, stress, depression, and boredom ( Xie et al., 2020 ). However, positive effects of distance learning have also been reported, such as improved competitive and motor skills ( Sundus, 2017 ). Therefore, the overall impact of school closures and remote learning remains controversial.

Remote learning has also negatively affected children’s cognitive and academic performance throughout all age groups ( Colvin et al., 2022 ). Standardized assessments during and after obligatory confinement have revealed students’ difficulties meeting grade expectations, particularly in schools with less in-person class time ( Colvin et al., 2022 ). Specific academic difficulties have been reported in mathematics, language, and reading skills. More than 1.5 million students from across the United States exhibited worse performance in mathematics and reading scores compared with the previous academic year ( Colvin et al., 2022 ).

As the death rate from COVID-19 slows, people have gradually returned to in-person businesses, and schools have begun to reopen. Current evidence still needs to be more consistent regarding the effect of remote learning on academic performance. Although remote tools may facilitate access to education and allow the development of additional learning skills, the consequences of screen-dependent learning during confinement are likely to affect children in the post-COVID-19 era, and the long-term impact remains to be seen. Therefore, the current systematic review sought to describe the effects of COVID-19 lockdowns on children’s learning abilities and school performance.

2. Materials and methods

A systematic literature search was conducted on September 24, 2021, and February 3, 2023, to identify experimental, observational, or analytical studies. The search was performed in three online databases. The following terms were used in a search of PubMed (https://pubmed.ncbi.nlm.nih.gov/advanced/): (((((((((virtual) OR (virtually)) AND (learning)) AND (learning disorders)) AND (distance learning[MeSH Terms])) OR (distance education[MeSH Terms])) AND (pandemic[MeSH Terms])) OR (confinement)) AND (School children) AND (COVID-19)). For searching the Scopus database (https://www.scopus.com), we used the following terms: ALL ( virtual OR virtually AND learning AND learning AND disorders AND (“distance” AND “learning”) AND (“distance” AND “education”) AND (pandemic OR confinement) AND (“school” AND “children”) AND covid-19) AND (LIMIT-TO (SUBJAREA, “MEDI”) OR LIMIT-TO (SUBJAREA, “PSYC”) OR LIMIT-TO (SUBJAREA, “HEAL”) OR LIMIT-TO (SUBJAREA, “NEUR”)). Finally, for searching the Science Direct database (https://www.sciencedirect.com/search), we used the following terms: ((((((((virtual) AND (learning)) AND (learning disorders)) AND (distance learning[MeSH Terms])) OR (distance education[MeSH Terms])) AND (pandemic[MeSH Terms])) OR (confinement)) AND (school children) AND COVID-19. The ID 290696 was generated in the International Prospective Register of Systematic Reviews.

We found 1787 articles, removed duplicates, and filtered the remaining articles by title and abstract following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines ( Fig. 1 ). Articles were excluded if they: (I) assessed the impact of COVID-19 lockdown on physical education, metabolic diseases, or visual impairment; (II) focused on paternal stress or adult academic performance; (III) focused on mental health or lifestyle implications caused by confinement without analyzing the association with learning abilities; (IV) were book chapters or narrative reviews; or (V) were published in languages other than Spanish, English, and French. Consequently, we selected 24 articles. All included articles were evaluated using the Joanna Briggs checklist to guarantee quality (https://jbi.global/critical-appraisal-tools). Finally, we extracted the following information: title, year of publication, authors, digital object identifier number, objectives, period of the study, period of confinement in the country of the study, evaluated learning area, population and sample, tests implemented for learning assessment, and overall results. In addition, a final question was answered for each study: “Did learning improve, stay the same, or worsen after lockdown?” All investigators participated in the data collection process and the preparation for data presentation and synthesis.

Preferred reporting items for systematic reviews and meta-analyses flow diagram.

Articles included in the review were grouped based on the primary domain of children’s learning performance examined during COVID-19 lockdowns. First, children’s academic performance was clustered in mathematics, reading, language, and biology. Second, we grouped articles that examined emotional and behavioral impacts on academic performance, and those that focused on children’s, parents’, and teachers’ recollections regarding perceptions of learning ( Table 1 ). Twelve studies were conducted in Europe ( Álvarez-Guerrero et al., 2021 , Chambonnière et al., 2021 , Engzell et al., 2020 , Giménez-Dasí et al., 2020 , Haelermans et al., 2022 , Korzycka et al., 2021 , Maldonado and Witte, 2021 , Rose et al., 2021 , Scarpellini et al., 2021 , Spitzer and Musslick, 2021 , Tomasik et al., 2021 , Zagalaz-Sánchez et al., 2021 ), followed by four in Asia ( Cui et al., 2021 , Sakarneh, 2021 , Zhang et al., 2020 , Zhao et al., 2020 ), seven in North America ( Domingue et al., 2022 , Gaudreau et al., 2020 , Goldhaber et al., 2022 , Kuhfeld et al., 2022 , Kuhfeld et al., 2020 , Maulucci and Guffey, 2020 , Relyea et al., 2023 ), and one in South America ( González et al., 2022 ) ( Supplementary table ). Regarding evaluation methods, fifteen papers used standardized tests or formative assessment, eight studies used online questionnaires or surveys, and one study used an evaluation scale. Overall, we found that worsening learning outcomes were reported in 16 studies, whereas four studies reported improvements in children’s performance in mathematics, biology, and cognitive abilities, using adaptable teaching strategies for online classes. Finally, four studies reported stable learning performance. Further discussion of each study and the results is presented below.

Articles examining the impact of remote learning during the COVID-19 pandemic.

4. Discussion

4.1. effects of covid-19 lockdowns on children’s mathematics performance.

Six of the 24 studies evaluated differences in mathematical performance before and after lockdowns ( Cui et al., 2021 , Engzell et al., 2020 , Goldhaber et al., 2022 , Kuhfeld et al., 2020 , Rose et al., 2021 , Tomasik et al., 2021 ). Of these, only one study reported improved children’s academic outcomes, comparing the relative error and absolute error rates in mathematical problem sets in 2500 German students from grades 4–10 before and during school closures ( Spitzer and Musslick, 2021 ). The results revealed a positive effect of remote learning during COVID-19 lockdowns compared with the results from the previous year, particularly in students with previous lower academic achievement ( Spitzer and Musslick, 2021 ).

The other studies that evaluated students using standardized math tests in American, Swiss, Dutch, Flemish, and British schools reported mainly lower primary school scores during and after lockdowns ( Engzell et al., 2020 , Goldhaber et al., 2022 , Kuhfeld et al., 2020 , Maldonado and Witte, 2021 , Rose et al., 2021 , Tomasik et al., 2021 ). Differences in school performance varied among primary and secondary Swiss students, with the former being the most affected group ( Tomasik et al., 2021 ). Overall academic achievement was reduced in both groups, whereas only primary school students exhibited delayed learning with a distance learning system ( Tomasik et al., 2021 ). The authors proposed that cognitive, motivational, and socio-emotional effects were contributing factors ( Spitzer and Musslick, 2021 ). These findings align with projections of slower academic development after school closures in the United States ( Goldhaber et al., 2022 , Kuhfeld et al., 2020 ). A Policy Analysis for California Education report found that by the time students completed interim winter assessments in the 2020–21 school year, they had experienced a learning lag of approximately 2.6 months in English language arts (ELA) and 2.5 months in math ( Pier et al., 2021 ). Moreover, economically disadvantaged students, English learners, and students of color experienced a more significant learning lag than students not in these groups ( Goldhaber et al., 2022 , Pier et al., 2021 ).

4.2. Effects of COVID-19 Lockdowns on Children’s reading performance

Several studies in the United States, Netherlands, and England evaluated the effects of COVID-19 lockdowns on reading abilities in children ( Domingue et al., 2022 , Engzell et al., 2020 , Gaudreau et al., 2020 , Goldhaber et al., 2022 , Kuhfeld et al., 2020 , Rose et al., 2021 , Tambyraja et al., 2021 ). Engzell et al. analyzed performance in reading and comprehension of factual and literary subjects among 350,000 primary school students in national exams before and after an 8-week lockdown during the COVID-19 pandemic ( Engzell et al., 2020 ). The results revealed a post-pandemic decrease in reading performance of more than 3 % compared with pre-pandemic test results ( Engzell et al., 2020 ). Similar unfavorable results were reported by Rose et al.’s study in England during the spring and summer of 2020 ( Rose et al., 2021 ), which followed 6000 pupils for two years and evaluated learning performance using National Foundation for Educational Research standardized tests. The results revealed significantly lower reading performance in 2020 compared with a 2017 sample, with 5.2 % of students scoring two marks fewer. Moreover, reading assessments revealed a 7-month progress delay in 2020, compared with a 2019 sample ( Rose et al., 2021 ).

In the United States, Kuhfeld et al. proposed several projections regarding the impact of COVID-19 on learning patterns in 5 million students ( Kuhfeld et al., 2020 ). Data were extracted from Measures of Academic Progress Growth assessments in the previous two years. The authors made various predictions regarding best-case scenarios through to worst-case scenarios. Projections in a partial absenteeism scenario were predicted to result in 63–68 % of the expected annual learning gains in reading, whereas full absenteeism was predicted to result in less than 30 % of learning gains in reading. In addition, variability between students’ reading performance was estimated to be 1.2 times the standard deviation normally expected ( Kuhfeld et al., 2022 ).

Several studies reported that students’ socioeconomic status was a determinant factor for negative impacts on reading performance caused by COVID-19 lockdowns ( Domingue et al., 2022 , Engzell et al., 2020 , Kuhfeld et al., 2020 , Rose et al., 2021 , Tambyraja et al., 2021 ). In the United States, studies reported that students who attended high socioeconomic-status schools achieved better academic performance and had a more robust growth level than those who attended low socioeconomic-status schools or had reduced-price lunches ( Domingue et al., 2022 ). In the Netherlands, the decrease in reading learning performance was reported to be 60 % greater in children from disadvantaged homes ( Engzell et al., 2020 , Haelermans et al., 2022 ). Moreover, in England, Rose et al. reported that the gap between disadvantaged and non-disadvantaged students was 8.28 standardized points in the test, corresponding to an 8-month learning gap between the two groups ( Rose et al., 2021 ).

However, Gaudreau et al. proposed that during the COVID-19 pandemic, children’s remote vocabulary learning, and comprehension could be supported with virtual strategies designed to contribute to the educational progress of young students ( Gaudreau et al., 2020 ). The researchers evaluated reading comprehension and vocabulary learning in 58 4-year-old children under three different storytelling format conditions: live, video chat, and prerecorded storytelling. The results revealed that reading in all three formats positively stimulated verbal learning compared with children not exposed to reading, with more significant responses reported in the live and video chat conditions ( Gaudreau et al., 2020 ).

In addition, absenteeism significantly impacts students’ reading performance, indicating greater variability between children’s academic skills ( Kuhfeld et al., 2020 ). Some reading strategies used in remote learning environments may be beneficial for reading and could be implemented by teachers ( Gaudreau et al., 2020 ). Furthermore, social, and economic inequalities may contribute to gaps in reading performance between students that could last for years, requiring substantial mitigation efforts from schools and governments.

We found only a few studies conducted in other countries. Angrist et al. estimated learning losses in terms of oral reading fluency in sub-Saharan Africa from half a year to over one year in the short term, which can accumulate over time, and children might be unable to catch up. Their estimates suggest that short-term learning deficits for a child in grade 3 could accumulate to the equivalent of 2.8 years of lost learning by grade 10 ( Angrist et al., 2021 ).

4.3. Effects of COVID-19 Lockdowns on Children’s language performance

School closures caused by COVID-19 lockdowns have been reported to affect language learning negatively. Three of the 17 included studies reported reduced performance in language standardized tests compared with previous test results ( Engzell et al., 2020 , Maldonado and Witte, 2021 , Tomasik et al., 2021 ). Maldonado et al. evaluated mathematical and language scores in a Flemish school and reported lower Dutch and French learning results than in mathematics ( Maldonado and Witte, 2021 ). The authors proposed that the lack of Dutch speaking at home contributed to lower language performance. However, this difference was not found by Engzell et al., who evaluated reading, spelling, and mathematics scores in a Dutch school and reported lower scores in all three subjects than the previous year ( Engzell et al., 2020 , Maldonado and Witte, 2021 ). Children who relied on speech and language therapy faced a more significant challenge after school closures. The lack of access to in-person therapy and the shift to newly established teletherapy modalities contributed to therapy dropout and were likely to have decreased academic achievement in this population ( Tambyraja et al., 2021 ).

4.4. Effects of COVID-19 Lockdowns on Children’s biology performance

Biology and science performance was also assessed during COVID-19 lockdowns, and different virtual strategies have been proposed by researchers ( Maulucci and Guffey, 2020 ). Maulucci et al. examined the effects of Bybee’s 5E virtual academic model in biology lessons among 71 high school students. Bybee’s 5E model was integrated into a remote biology school curriculum, following two standard courses: The Alabama Course of Study and the Next Generation Science Standards. The authors examined responses to two biology pretest questions to assess misconceptions and evaluate students’ progress. The course involved several engaging, exploring, explaining, extending, and evaluating virtual activities. Analysis of the course dynamics revealed that students who attended live lessons benefited from discussion and feedback opportunities. This finding indicates that increasing live lessons and real-time participation may increase engagement, using tools like Nearpod, Zoom, and bio-interactive platforms. Overall, the results suggest that teachers’ and students’ technology skills must be developed quickly to enable new virtual strategies that guarantee the best learning environments for students ( Maulucci and Guffey, 2020 ).

4.5. Children’s, parents, and teachers’ perceptions of learning during COVID-19

Multiple investigators have studied the perceptions of students, parents, and teachers regarding the changes in education caused by COVID-19 ( Álvarez-Guerrero et al., 2021 , Cui et al., 2021 , Korzycka et al., 2021 , Sakarneh, 2021 , Scarpellini et al., 2021 , Zagalaz-Sánchez et al., 2021 , Zhang et al., 2020 ). Here we discuss the perceptions reported in these studies, emphasizing those that involve academic performance and learning skills. We will also review how students perceive their learning process and how parents and teachers perceive it from their perspectives.

4.5.1. Perceptions of parents’ and teachers of children with special needs

Regarding students with intellectual disabilities, five studies have been conducted so far ( Álvarez-Guerrero et al., 2021 , Averett, 2021 , Sakarneh, 2021 , Scarpellini et al., 2021 , Tellier, 2022 ). Some studies revealed negative perceptions and challenges of remote learning ( Álvarez-Guerrero et al., 2021 , Averett, 2021 , Sakarneh, 2021 ). In Jordan, Sakarneh interviewed ten parents of children with special needs about their perceptions regarding the use of online platforms, behavioral changes caused by lockdowns, and the level of inclusion of education ( Sakarneh, 2021 ). Parents reported two main issues regarding remote learning adaptation: first, the lack of motivation to complete tasks individually, and second, the use of conventional teaching techniques that were not adaptable to children’s particular needs because of strict schedules and inadequate learning material ( Sakarneh, 2021 ). Studies conducted in Spain, Italy, and the US highlighted the lack of virtual accommodations for the special needs population and the lack of social skills development due to virtual interactions ( Álvarez-Guerrero et al., 2021 , Averett, 2021 , Scarpellini et al., 2021 ).

On the contrary, some parents and teachers in the US and Canada shared positive experiences with remote learning in children with disabilities. They expressed stress relief, control of mood swings, time flexibility, increased accessibility, and support due to the hard work of school staff ( Averett, 2021 , Pellicano and Stears, 2020 , Tellier, 2022 ).

Several strategies have been proposed. Utilization of concept maps, prolonged work times, and decreases in the number of tasks as well as encouraging children to ask for help, promoting the preparation of the class materials, stimulating peer discussion, familiarization with the learning platform, and using an individualized student center method ( Cui et al., 2021 , Tellier, 2022 , Zhao et al., 2020 ). In Spain, Álvarez-Guerrero et al. analyzed the Dialogic Literary Gatherings responses of five children with moderate to severe intellectual disabilities ( Álvarez-Guerrero et al., 2021 ). Teachers' and parents' perceptions were also examined. Two teachers directed the meetings once a week for six months. Visual aids, such as photographs and drawings related to the literary content, facilitated children's comprehension. In addition, the role of families in learning interaction during gatherings was essential for the transition from face-to-face to virtual dynamics. Teachers perceived the benefits of debate and discussion in cognitive and behavioral processes. Moreover, Dialogic Literary Gatherings were reported to promote children's vocabulary, comprehension, and reading abilities and enhance their interactions with society ( Álvarez-Guerrero et al., 2021 ).

4.5.2. Perceptions of parents and teachers of neurotypical children

In neurotypical children, further studies were carried out that reflected essential concerns, which can be grouped into the following clusters: perception of virtual learning disorganization, increased academic demands, motivational and behavioral changes, and particular academic impact in rural areas ( Sakarneh, 2021 , Scarpellini et al., 2021 , Zagalaz-Sánchez et al., 2021 ).

First, the overall results reported a perception of the disorganization of distance learning. In Italy, 1601 mothers were interviewed to explore their perceptions of primary and middle school children's experiences with remote learning during COVID-19 lockdowns. The results revealed that 1.5 % of children lacked access to technology, particularly primary school students who were often exposed to less structured routines. Furthermore, the results revealed diminished teacher feedback and contact compared with face-to-face teaching formats. Regarding learning assessments, primary school students performed less than in the previous academic year. In contrast, middle school grades remained consistent because of better planning of tests and oral exams ( Scarpellini et al., 2021 ). In a survey conducted in Poland, school children's concerns were regarding the lack of feedback from teachers, unclear evaluation parameters for older students, and an absence of academic progress comparison with peers among younger students ( Korzycka et al., 2021 ).

Second, the curriculum structure was a perceived concern, particularly increased academic demands. A national survey in Poland assessed adolescents' perceptions of remote learning and performance during COVID-19 lockdowns ( Korzycka et al., 2021 ). For older students, curriculum structure was identified as a difficulty, particularly increased academic demands ( Korzycka et al., 2021 ). In China, Cui et al. conducted a questionnaire with 1008 elementary school children and parents, distributed in two data collection periods, one at the beginning and the other at the end of 40 days during China's COVID-19 lockdown ( Cui et al., 2021 ). According to the results, parents agreed that the lecture format was inadequate, surpassing students' capacities and potentially promoting emotional and behavioral disturbances ( Cui et al., 2021 ).

Third, a lack of motivation and behavioral problems were commonly raised in surveys. A survey by Cui et al. revealed that a trend for decreased motivation was reflected in uncompleted homework assignments and dissatisfaction with online lessons ( Cui et al., 2021 ). Moreover, Korzycka et al. reported that lack of motivation was thought by children to be secondary to the lack of a school environment and extracurricular activities ( Korzycka et al., 2021 ). Furthermore, Italian mothers also reported behavioral changes, such as reduced attention span (< 20 min), an increased need for breaks (every 10 min), restlessness in younger children (69.1 %), and anxiety in older children (34.2 %) ( Scarpellini et al., 2021 ). In addition, living conditions during COVID-19 lockdowns significantly affected children's motivation, and the degree of happiness and fatigue were related to the size of housing ( Zagalaz-Sánchez et al., 2021 ). Specifically, larger house environments were associated with greater happiness and less fatigue, while participants that lived in rural areas had increased levels of physical activity and reading ( Zagalaz-Sánchez et al., 2021 ). A survey performed in India regarding the perception of teachers and students towards online classes reported generalized negative feedback and overall preference for regular classes and highlighted the influence of learning environments on the quality of online learning and teaching ( Selvaraj et al., 2021 ).

Finally, specific academic impacts in rural areas were also reported in three studies ( Korzycka et al., 2021 , van Cappelle et al., 2021 , Zagalaz-Sánchez et al., 2021 ). In Spain, a 45-day cross-sectional study was performed to analyze the effects of living conditions during COVID-19 on educational activities and learning processes. A sample of 837 0–12-year-old children and their families responded to a validated questionnaire, and daily life activities were compared between children from urban and rural areas. Regarding technological devices, children with higher usage tended to live in apartments, followed by children without gardens in their houses, who mostly lived in urban areas ( Zagalaz-Sánchez et al., 2021 ). In addition, students in rural areas faced significant tech-support challenges in remote learning compared with students from large cities ( Korzycka et al., 2021 ).

Similarly, a study reflecting on the findings from a UNICEF survey in India found several factors related to adolescents' perception of their learning. The frequency of teacher contact and live video classes had a positive impact. However, time spent on domestic chores significantly decreased reported levels of perceived learning ( van Cappelle et al., 2021 ).

Overall, the authors proposed that the multiple stimuli involved in remote learning can overload children’s integrating learning abilities ( Korzycka et al., 2021 ). The lack of appropriate cognitive stimulation and social interaction caused by COVID-19 lockdowns might affect learning performance, particularly in young children ( Scarpellini et al., 2021 ). Further institutional efforts should focus on comprehending social determinants to improve interventions and academic conditions for children.

4.6. Emotional and behavioral impacts on academic performance

Some previous studies have focused on understanding the emotional and behavioral factors regarding learning and academic environments during the COVID-19 pandemic. However, only three studies have sought to relate these factors to children's school performance and learning abilities ( Giménez-Dasí et al., 2020 , Zhang et al., 2020 , Zhao et al., 2020 ). For example, resilience, emotional regulation, psychiatric disorders, and behavioral changes have been examined in various studies. In Spain, Giménez-Dasí et al. evaluated psychological and behavioral effects in 167 3-to-11-year-old children and their families ( Giménez-Dasí et al., 2020 ). The System of Evaluation of Children and Adolescents questionnaire was assessed twice: before and after 4–6 weeks of lockdown. The results were divided between older (6–11-year-olds) and younger (3-year-olds) children. Older children exhibited the worst emotional regulation, attention, self-control, and willingness to study. In addition, younger children's parents reported worsening psychological states (55 % in early Childhood and 64 % in Primary education), whereas 36 % reported no change, and 17 % felt that their child's psychological state had improved ( Giménez-Dasí et al., 2020 ). Similar results were reported by Zhao et al. in 2010 school-aged children, parents, and teachers, using online questionnaires for seven days in China ( Zhao et al., 2020 ). Overall, participants reported that homeschooling methods were acceptable, whereas teachers mentioned a possible decline in children's academic performance, motivation, and focus. In addition, the results revealed that 17.6 % of respondents suspected emotional and behavioral problems in children, and 68.8 % of parents reported that their children had more than 3 h of screen time per day, which exceeds the recommendations of the American Academy of Pediatrics ( Committee on Public Education, 2001 , Zhao et al., 2020 ). Another study conducted in Spain found that online digital storytelling activity during the pandemic crisis provided primary school cognitive, emotional, and social support ( Alonso-Campuzano et al., 2021 ).

In China, Zhang et al. evaluated emotional resilience and its effects on learning skills in 896 12–14-year-old middle school children ( Zhang et al., 2020 ). In addition, different questionnaires were implemented in seventh and eighth graders during the first lockdown period. The results revealed that greater resilience contributed to a better time, environment, and resource management abilities. However, the authors reported that the follow-up duration was short and suggested further studies examining other factors, such as academic performance, family support, and technology habits ( Zhang et al., 2020 ).

5. Limitations

The number of studies selected for qualitative analysis is low, which impedes significant overall conclusions of the effects of lockdowns on academic outcomes. Although studies analyzed in this review provide general conclusions about the impact of remote learning on children's school performance, additional studies are required to further evaluate the potential moderators of learning. Furthermore, articles included in this study are heterogeneous in terms of the number of subjects, study design, and evaluation methods, which makes results difficult to compare one to another, thereby reaching subjective conclusions rather than quantitatively significant results. We also acknowledge an important geographic bias since most of the studies with significant results in academic performance were conducted in selected regions, and we found less evidence from Latin America, Africa, and other developing countries.

6. Conclusions

A relatively small number of studies examining the impact of COVID-19 lockdowns on academic performance and learning abilities have been published to date. Our analysis suggested several negative consequences of lockdowns and the shift to virtual learning schemes for children's academic performance in different knowledge areas. However, in about 35 % of the studies included, no learning loss was reported; therefore, the negative impact of academic performance during lockdown should be tempered. Some contributing factors were identified: socioeconomic status (type of household and family income), access to technology, learning environment, quality of innovative remote resources, and teachers' feedback.

Furthermore, remote learning has increased the learning gap between students, including those with intellectual disabilities who face a more significant challenge. New learning strategies have been developed to improve assessment and interactive pedagogical tools for improving children's attention, motivation, and willingness to study. In addition, psychological support for the behavioral and emotional consequences of COVID-19 is needed to facilitate children's transition back into in-person learning routines. Further research should focus on the long-term learning impact on school performance after lockdown to establish truthful conclusions.

Preparation for a possible new emergency is deemed necessary. Consideration of flexible learning modalities and standardized tests for performance monitoring could help overcome language, geography, and disability barriers. In addition, psychological support for the behavioral and emotional consequences of COVID-19 is needed to facilitate children's transition back into in-person learning routines. Further research should focus on the long-term learning impact on school performance after lockdown to establish truthful conclusions.

Ethics approval and consent to participate

Consent for publication.

This research received no external funding.

CRediT authorship contribution statement

María C. Cortés-Albornoz: Conceptualization, Methodology, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. Sofía Ramírez-Guerrero: Conceptualization, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. Danna P. García-Guáqueta: Conceptualization, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing. Alberto Vélez-Van-Meerbeke: Conceptualization, Investigation, Resources, Writing – review & editing. Claudia Talero-Gutiérrez: Conceptualization, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Supervision.

Conflicts of interest statement

The authors declare that they have no competing interests.

Appendix A Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ijedudev.2023.102835 .

Appendix A. Supplementary material

Supplementary material

Data Availability

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Peer-reviewed

Research Article

The long-term effects of perceived instructional leadership on teachers’ psychological well-being during COVID-19

Roles Conceptualization, Methodology, Writing – original draft, Writing – review & editing

Affiliations School of Information Engineering, Shandong Youth University of Political Science, Jinan, Shandong, China, Faculty of Education, Qufu Normal University, Qufu, Shandong, China

Roles Investigation, Writing – review & editing

Affiliation Faculty of Education, Jiangxi Science and Technology Normal University, Nanchang, Jiangxi, China

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

* E-mail: [email protected] (I-HC); [email protected] (JHG)

Affiliation Chinese Academy of Education Big Data, Qufu Normal University, Qufu, Shandong, China

Roles Supervision, Validation, Writing – review & editing

Affiliation Department of English, National Changhua University of Education, Changhua, Taiwan

Roles Data curation, Writing – review & editing

Affiliation Yangan Primary School of Qionglai City, Qionglai, Sichuan, China

Affiliation Gaogeng Nine-year School, Qionglai, Sichuan, China

Roles Validation, Writing – review & editing

Affiliation Shandong Provincial Institute of Education Sciences, Jinan, Shandong, China

• Xiu-Mei Chen, 
• Xiao Ling Liao, 
• I-Hua Chen, 
• Jeffrey H. Gamble, 
• Xing-Yong Jiang, 
• Xu-Dong Li, 

• Published: August 19, 2024
• https://doi.org/10.1371/journal.pone.0305494
• Reader Comments

The COVID-19 outbreak led to widespread school closures and the shift to remote teaching, potentially resulting in lasting negative impacts on teachers’ psychological well-being due to increased workloads and a perceived lack of administrative support. Despite the significance of these challenges, few studies have delved into the long-term effects of perceived instructional leadership on teachers’ psychological health. To bridge this research gap, we utilized longitudinal data from 927 primary and secondary school teachers surveyed in two phases: Time 1 in mid-November 2021 and Time 2 in early January 2022. Using hierarchical linear modeling (HLM), our findings revealed that perceptions of instructional leadership, especially the "perceived school neglect of teaching autonomy" at Time 1 were positively correlated with burnout levels at Time 2. Additionally, burnout at Time 2 was positively associated with psychological distress and acted as a mediator between the "perceived school neglect of teaching autonomy" and psychological distress. In light of these findings, we recommend that schools prioritize teachers’ teaching autonomy and take proactive measures to mitigate burnout and psychological distress, aiming for the sustainable well-being of both teachers and students in the post-pandemic era.

Citation: Chen X-M, Liao XL, Chen I-H, Gamble JH, Jiang X-Y, Li X-D, et al. (2024) The long-term effects of perceived instructional leadership on teachers’ psychological well-being during COVID-19. PLoS ONE 19(8): e0305494. https://doi.org/10.1371/journal.pone.0305494

Editor: Ali B. Mahmoud, St John’s University, UNITED STATES OF AMERICA

Received: April 29, 2023; Accepted: May 30, 2024; Published: August 19, 2024

Copyright: © 2024 Chen 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: This study was financially supported by the 2021 National Social Science Foundation of China (NSSFC) “Research on Mixed Ownership Model of Vocational Education” in the form of an award (BJA210105) received by I-HC. No additional external funding was received for this study. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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

1 Introduction

In response to the outbreak of COVID-19, countries worldwide implemented protective measures, such as physical distancing, to prevent the spread of the virus, resulting in the closure of schools globally [ 1 ]. The closure of schools has not only affected students’ psychological well-being [ 2 – 5 ], but has also caused a significant level of stress among teachers [ 6 , 7 ]. Studies indicate that teachers experienced pressure during the closure period due to mandatory teaching of online courses [ 8 ], increased teaching workloads [ 9 ], lack of support from administrators [ 10 , 11 ], and poor communication with students and parents [ 9 ]. Additionally, teachers suffered from symptoms such as anxiety, depression, and sleep disturbances [ 12 ]. As such, the literature has provided mounting evidence to suggest that COVID-19 has caused considerable psychological distress among teachers [ 13 – 15 ].

Recent studies have underscored the potential long-term consequences of pandemic-induced stress, which can erode protective factors such as teachers’ resilience. This erosion can lead to burnout [ 16 ] and adversely affect their psychological well-being [ 17 – 19 ]. The challenges are compounded by the fact that school closures and the shift to online teaching have heightened the risk of burnout among teachers [ 20 ]. This exacerbates their already significant levels of psychological distress [ 21 , 22 ], leading researchers to delve deeper into the factors contributing to job burnout and psychological distress among educators.

Building on this, individual-level factors during COVID-19 have been extensively studied. These include role conflict [ 23 ], professional experience (such as the number of years spent teaching) [ 24 ], teacher professional identity (which encompasses individual beliefs, values, and commitments related to the teaching profession) [ 25 ], and perceptions about one’s ability to control situations [ 26 ]. This also covers competence in online teaching tasks [ 27 ] and anxiety related to communicating with parents [ 28 ]. On the organizational front, Maslach et al. [ 29 ] posited that burnout stems from extended exposure to work-related stressors. Thompson et al. [ 30 ] introduced the Six Areas of Worklife model, pinpointing workload, control, reward, and values as organization-level factors linked to burnout, especially during the COVID-19 era. Other organization-level factors contributing to teacher burnout include work climate, work pressure, perceptions of collective exhaustion among peers, disruptions to conventional classroom teaching [ 31 ], diminished administrative support [ 28 , 32 ], and supervisory management styles [ 33 , 34 ]. Research has also highlighted the correlation between principals’ leadership styles and teacher burnout [ 35 – 37 ]. Moreover, numerous studies have identified teacher burnout as a significant predictor of psychological distress in educators [ 21 , 38 , 39 ].

While the significance of both individual-level and organization-level factors related to burnout has been assessed in the context of COVID-19, organization-level factors have not been sufficiently evaluated. Indeed, the education department should place greater emphasis on factors at the organizational level when implementing decisive measures to address them. Instructional leadership, a pivotal aspect of school leadership [ 40 , 41 ], has yet to be thoroughly explored in terms of its impact on teachers’ well-being during the pandemic. To date, there seems to be a gap in the literature regarding how teachers’ perceptions of instructional leadership influence their experiences of burnout and psychological distress, especially during school closures. This gap is particularly evident in studies focusing on the longitudinal effects of perceived instructional leadership on the mental health of Chinese teachers. Given this context, this study seeks to address the following research question: How do teachers’ perceptions of instructional leadership affect their subsequent experiences of burnout and psychological distress ?

To address the above gap, our study undertook two waves of data collection: the first wave was gathered during the period of online teaching when campuses were closed, aiming to gauge teachers’ perceptions of instructional leadership. The second wave was collected after the resumption of face-to-face classes to assess teacher burnout and psychological distress. The objective of this paper is to explore the relationship between perceived instructional leadership and subsequent burnout and psychological distress using hierarchical linear modeling (HLM). In this context, teachers’ perceptions of instructional leadership are considered at the school level, while burnout and psychological distress are evaluated at the individual (teacher) level. The subsequent section will present the model and research hypotheses.

2 Model and hypothesis

In the present research, we employed longitudinal data to systematically examine the influence of teachers’ perceptions of instructional leadership on subsequent manifestations of job burnout and psychological distress, as delineated in Fig 1 . To operationalize the construct of perceived instructional leadership, we grounded our categorization within the tenets of the Self-Determination Theory (SDT), segmenting it into three distinct categories. To elucidate the interrelationships among these variables, we anchored our investigation in the Stressor-Strain-Outcome (SSO) model, as proposed by Koeske and Koeske [ 42 ], subsequently formulating pertinent research hypotheses.

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The dotted line represents the indirect effect of perceived instructional leadership at Time 1 on psychological distress at Time 2.

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2.1 The SSO model

The Stressor-Strain-Outcome (SSO) model explains how work-related stressors negatively impact employee behavior through psychological strain, and conceptualizes strain as a mediating factor [ 42 ]. Stressors, in the SSO model, are environmental stimuli that employees perceive as bothersome and disruptive, such as excessive workload, a lack of support, and conflicting roles [ 42 – 44 ]. Strain, on the other hand, is a negative reaction to environmental stimuli that disrupts employees’ concentration, effecting their physiology and mood [ 42 , 45 ], with burnout as a common manifestation [ 42 , 43 ]. Outcome refers to the lasting behavioral or psychological effects of chronic stress and strain, such as physical or psychological symptoms (e.g., psychological distress in the workplace).

Based on the aforementioned concerns, three perceptions of school instructional leadership were evaluated by this study as disruptive environmental stimuli (i.e., stressors): perceived school neglect of teaching autonomy, perceived school neglect of teaching competence, and perceived school emphasis on competitive relationships during the COVID-19 pandemic.

Studies shown that burnout is often conceptualized as a strain in response to environmental stimuli in SSO model [ 42 , 43 ]. The construct of job-related burnout was proposed by Freudenberger [ 46 ] to describe the extreme physical and emotional exhaustion experienced by individuals due to excessive workloads. Maslach et al. [ 29 ] later defined burnout as "a prolonged response to chronic emotional and interpersonal stressors on the job," characterized by exhaustion, cynicism, and inefficacy. Emotional exhaustion, in particular, is considered the central component of burnout [ 42 , 47 ]. In the context of the COVID-19 pandemic, emotional exhaustion maybe a negative reaction to teachers’ perceived instructional leadership [ 48 , 49 ].

As per the SSO model, stressors produced by three perceptions of instructional leadership may result in psychological distress (outcome) in teachers, with burnout (strain) mediating the relationship between the two. In the following subsections, the hypothesized relationships between these variables are presented sequentially.

2.2 Operationalizing perceived instructional leadership during the COVID-19 pandemic: A tripartite categorization based on SDT

Instructional leadership is widely recognized as the cornerstone of school leadership [ 40 , 41 ]. Narrow conceptions of instructional leadership focus solely on teacher behaviors that augment student learning, whereas broader interpretations encompass issues related to both organizational and teacher culture [ 50 ]. According to Alig-Mielcarek and Hoy [ 51 ], instructional leadership comprises three primary components: (1) defining and communicating goals, (2) monitoring and providing feedback on the teaching and learning process, and (3) promoting and emphasizing the significance of professional development. Consequently, instructional leadership has emerged as an indispensable element of school reform and enhancement [ 51 ]. It influences a myriad of factors pivotal to the resilience of educational institutions, ranging from "organizational silence" (where crucial events or concerns remain unvoiced) to "organizational attractiveness" (reflecting positive sentiments towards an institution) [ 52 ].

The construct of instructional leadership in this study differs from the predominate perspective, which emphasizes leaders’ roles in stimulating teachers’ effectiveness in teaching and learning and improving students’ outcomes [ 53 ]. During the COVID-19 period, a more directive leadership style is indispensable to efficiently guide teachers in adapting to the unfamiliar task of online teaching [ 54 , 55 ], and it can be considered a special form of "instructional leadership" under pandemic conditions. It is uniquely adapted for the pandemic context and can reflect the teachers’ perceived instructional leadership in the context of epidemic. Specifically, drawing from the SDT, this study categorizes teachers’ perceptions of instructional leadership during school closures into three distinct categories: perceived school neglect of teaching autonomy, perceived school neglect of teaching competence, and perceived school emphasis on competitive relationships. As posited by SDT, every individual harbors three fundamental psychological needs: autonomy, competence, and relatedness [ 56 , 57 ]. The fulfillment of these needs is essential for an individual’s holistic development, and any deficiency can adversely impact their psychological well-being [ 57 ]. In this context, perceived school neglect of teaching autonomy denotes teachers’ sentiments that schools overlooked their online teaching autonomy, compelling them to adhere to specific teaching standards and methodologies, thereby affecting perceived autonomy. Perceived school neglect of teaching competence signifies teachers’ perceptions that schools disregarded their online teaching competence during the closure, marked by a lack of provision for necessary online teaching training and an apparent indifference to the challenges of online/distance teaching, thereby affecting perceived competence. The perception of the school emphasizing competitive relationships suggests environments where competition among teachers was unduly promoted, engendering a detrimental atmosphere concerning relatedness. These constructs, which pertain to the neglect of teacher autonomy and competence and the prioritization of competition over collaboration, can be considered stressors in pandemic context. They have largely remained unexplored empirically. In contrast, supportive instructional leadership styles, which have been linked with a sustainable sense of agency, teacher expertise, and positive peer relationships, are documented in sustainable education literature [ 58 , 59 ].

2.3 Perceived instructional leadership and burnout

In this study, we examine the impact of perceived instructional leadership on teachers’ job burnout during the school closure period. In the previous research, it was found that principals’ leadership was related with teacher burnout [ 35 – 37 ]. Eyal and Roth [ 35 ] found that while transactional leadership (which seeks efficiency through monitoring and ensuring compliance through rewards and punishments) was positively correlated with burnout, transformational leadership (characterized by empowering and fostering individuals’ sense of mission through encouragement of innovation based on individual needs) was negatively correlated with burnout. Collie’s findings [ 36 ] highlighted that autonomy-supportive leadership (which refers to practices that promote individuals’ self-initiation and empowerment) was associated with lower emotion exhaustion and autonomy-thwarting leadership (which refers to practices that exert external control and reduce individuals’ self-determination) was positively associated with emotional exhaustion. Based on instructional leadership has been accepted as the core of school leadership [ 40 , 41 ], our first hypothesis (Hypothesis 1) is that teachers’ perceived instructional leadership would be positively associated with teachers’ job burnout. Specifically, we propose three sub-hypotheses based on the dimensions of instructional leadership that have been suggested as significant stressors, based on the SSO.

H 1a : Perceived instructional leadership that neglects teaching autonomy will have a positive relationship with job burnout. Previous research has shown a strong relationship between burnout and autonomy [ 29 , 36 , 60 , 61 ]. Teachers who are unable to choose their own teaching methods during remote teaching may experience negative attitudes towards teaching activities, dissatisfaction with their work, and depression [ 62 ].

H 1b : Perceived instructional leadership that neglects teaching competence will have a positive relationship with burnout. During the school closure period, teachers were not provided with required training for online teaching, and some may feel that the school was not paying attention to their teaching abilities. This lack of support may result in increased teaching pressures and a sense of incompetence, leading to burnout [ 34 , 63 ].

H 1c : Perceived instructional leadership that emphasizes competitive relationships will have a positive relationship with burnout. Instructional leadership that emphasizes competition among teachers may lead to a lack of feedback from colleagues and leaders during online instruction, which has been shown to contribute to burnout [ 64 ].

2.4 Burnout and psychological distress

Job burnout is a persistent, negative, and work-related psychological condition that can lead to turnover intention [ 65 ] (for example, among Chinese high school teachers during the pandemic), reduced productivity [ 66 ] (for example, among primary and secondary school teachers in English), and psychological distress such as anxiety and depression both in the general population [ 29 , 67 ] and among schoolteachers [ 68 ]. Teachers belong to a profession that is more likely to experience work-related stressors and psychological distress than other occupations [ 69 ]. As a group at high risk of job burnout [ 70 ], teachers have drawn extensive attention from researchers [ 14 , 71 , 72 ]. Shin et al. [ 38 ] used a three-wave longitudinal data to show that burnout among Korean middle and high school teachers predicted subsequent depressive symptoms. Similarly, in a scoping review, Agyapong et al. [ 39 ] found that teacher burnout could provoke symptoms such as anxiety and depression.

Based on the above facts, we propose the second research hypothesis: teachers’ burnout will be positively associated with psychological distress (Hypothesis 2). This hypothesis suggests that the experience of burnout in teachers is likely to result in psychological distress, given the high prevalence of psychological distress among teachers and the evidence linking burnout to subsequent depressive symptoms and other negative mental health outcomes.

2.5 The mediation of burnout between perceived instructional leadership and psychological distress

According to the SSO model, job stress does not necessarily lead directly to specific outcomes but may act on outcomes through a mediating mechanism (in this case, burnout) [ 42 ]. This mediating effect of burnout has been documented in various studies. For instance, Koeske and Koeske [ 73 ] found that emotional exhaustion mediated stressful events experienced by students and their physical and mental health symptoms. In two other studies, Dhir et al. [ 74 ] and Pang [ 75 ] found that social media fatigue mediated excessive media use and anxiety and depression as well as perceived information overload and emotional stress and social anxiety.

The independent variables from the above literature [ 73 – 75 ], including stressful events experienced by students, excessive media use, perceived information overload, and the three types of teachers’ perceived instructional leadership assessed in this study, are all prominent stressors. The dependent variables, such as anxiety and depression, represent different forms of psychological distress. Therefore, we hypothesize that burnout may mediate the relationship between teachers’ perception of instructional leadership (neglect of teaching autonomy, neglect of teaching competence, and emphasis on competitive relationships) and psychological distress (Hypothesis 3).

3.1 Participants

In this study, participants were recruited from Shangrao City, Jiangxi Province, China. Due to the COVID-19 outbreak in the city during October 2021, face-to-face teaching was cancelled for the city’s primary and secondary schools by the municipal government, beginning on November 3, 2021. After a month of strict restrictions, the outbreak was brought under control, and the campus reopened for face-to-face instruction. During this period, we conducted an online survey, with the assistance of the city’s education department, comprised of two waves. The first wave was conducted to investigate teachers’ perceived instructional leadership during school closures (Time 1: mid-November 2021). The second wave of the study examined teachers’ burnout and psychological distress within 2 to 3 weeks of resuming face-to-face teaching (Time 2: early-January 2022).

A priori sample size estimation was conducted using the Optimal Design Software [ 76 , 77 ]. With the support of the city’s education department, we were able to involve more than 100 schools in this survey. For the intended HLM analysis, given a cluster number of 100, a desired power of 0.8, an expected effect size of 0.30, and a significance level set at 5% (0.05), the a priori estimation yielded a requirement of five subjects per cluster (refer to S1 Fig ). Based on this outcome, we deduced that for cluster numbers exceeding 100, having 5 subjects per cluster would be adequate. This conclusion aligns with findings from previous studies [ 78 , 79 ]. These studies emphasized that to achieve adequate power, it’s more beneficial to increase the number of sampled clusters. Typically, sample sizes of up to 60 at the highest level and k+2 at the lower level (when there are k independent variables) are required.

This study was approved by the Jiangxi Association of Psychological Counselors (IRB ref: JXSXL-2020-J013), and with the assistance of the local education authority, data was collected via a hyperlink via convenience sampling. As participation was voluntary, participants were asked to include their email addresses if they wished to participate in a follow-up survey. There were 1,642 teachers who provided their email addresses and completed the longitudinal survey. To ensure data quality, we eliminated participants whose reported age was less than 18 and whose response time to all questions was less than 150 seconds. Additionally, we decided to exclude schools with participants of less than 4, considering the issue of representativeness and the required sample size [ 78 , 79 ]. As a final sample, 103 schools and 927 primary and secondary teachers were included, with a minimum of five teachers per school.

3.2 Measures

Demographic variables such as gender, teaching experience, subject of instruction and school type (primary school or secondary school), were collected. At Time 1, participants were asked to rate their perception of instructional leadership in the context of mandatory online instruction. At Time 2, participants were asked to report their levels of burnout and psychological distress over the preceding two weeks. The following subsections provide a detailed description of the measurement tools used in this study, and the items of the questionnaires are listed (see S1 – S3 Tables) in appendix.

3.2.1 Perceived instructional leadership.

To our knowledge, there isn’t a tool specifically designed to measure teachers’ perceptions of instructional leadership during periods of mandatory online teaching, such as those experienced during the pandemic. In the context of epidemic, a more directive leadership style is essential to guide teachers in the face of online teaching [ 54 ]. For the purpose of assessing teachers’ perceptions of this special form of instructional leadership at Time 1, we utilized the Psychological Need Thwarting Scale of Online Teaching (PNTSOT) developed by Yi et al. [ 80 ]. The alignment between perceived instructional leadership and the PNTSOT is illustrated in S2 Fig .

The PNTSOT was initially developed to assess the extent of psychological need thwarting during online teaching. In accordance with the CFA results in [ 80 ] (CFI = 0.966, NNFI = 0.955, RMSEA = 0.09, and SRMR = 0.05) and revised results in [ 72 ] (CFI, NNFI ranged from 0.960 to 0.999; RMSEA and SRMR were both less than 0.09), these results indicate that PNTSOT has ideal factorial validity among primary and secondary schoolteachers.

In this study, the three subscales of the PNTSOT (autonomy, competence and relatedness thwarting) were considered as direct reflections of perceived instructional leadership (perceived school neglect of teaching autonomy, perceived school neglect of teaching competence and emphasis on competitive relationships) by teachers. For each question, a seven-item Likert-type scale was used, ranging from "strongly disagree" to "strongly agree". The three variables for psychological need thwarting were aggregated into school-level variables which corresponded to the three types of perceived instructional leadership. Through HLM, high-level data can be derived from the aggregation of low-level data. To establish the plausibility of the aggregation, the values of within-group agreement ( r wg ) were calculated and they were found to have adequate consistency ( r wg values for perceived school neglect of teaching autonomy, neglect of teaching competence, and emphasis on competitive relationships were 0.77, 0.74 and 0.82). Values of r wg between 0.70 and 0.79 indicated moderate agreement, and values of .80 and above indicated strong agreement [ 81 ]. As a result, it is was deemed reasonable to aggregate teacher-level data to school-level data and use them as independent variables for this study. The following will explain the correspondence between the three sub-dimensions of the PNTSOT and the three types of perceived instructional leadership.

Perceived school neglect of teaching autonomy refers to instructional leadership in which teachers felt that schools did not value their teaching autonomy and forced them to use specific teaching methods during online teaching. Perceived school neglect of teaching autonomy can be described by the autonomy thwarting subscale of the PNTSOT in terms of the following four items: “During online courses during the pandemic, I cannot decide for myself how I want to teach”, “During online teaching work during the pandemic, I feel there is pressure that affects my behavior and requires me to comply in a certain way”, “I have to follow a prescribed online teaching style during the pandemic” and “During the pandemic, I feel pressure from the external environment that limited me in choosing a particular online teaching style”. The higher the score, the more pronounced the perception of neglected teaching autonomy. Teachers perceptions of school neglecting teaching autonomy in this study demonstrated a high level of internal consistency (Cronbach’s α = 0.79, McDonald’s ω = 0.79).

Perceived school neglect of teaching competence means that teachers believed their schools did not provide necessary online teaching training. They also paid little attention to their online teaching during the school closure period. Teachers felt that they had few opportunities to acquire more online teaching experiences. This sense of neglect can be described through competence thwarting in PNTSOT. The four items of competence thwarting included “There are some online teaching situations that make me feel incapable in my daily work environment during the pandemic” and “Due to the lack of training opportunities in my environment, I feel that I am not capable of performing online teaching tasks”. As a result of these items, it appears that schools may be neglecting teachers’ online teaching ability. A higher score indicates a higher level of perceived neglect of teaching competence. There is an acceptable degree of internal consistency from our data (Cronbach’s alpha = 0.84, McDonald’s alpha = 0.86) for perceived school neglect of teaching competence.

Perceived school emphasis on competitive relationship refers to teachers’ belief that schools value teachers’ competition. This variable can be assessed using relatedness thwarting in the PNTSOT, in which the four items include “I feel disconnected from other colleagues and leaders when teaching online during the pandemic” and “I feel that my colleagues and leaders are jealous of me when I achieve good results in online teaching during the pandemic”. A higher score indicates a higher level of perception of school competitive relationships. Teachers perceptions of school competitive relationships in this study demonstrated good internal consistency (Cronbach’s α = 0.89, McDonald’s ω = 0.88).

3.2.2 Burnout.

Based on the fact that emotional exhaustion contributes most significantly to burnout [ 47 , 82 ], this study used the "Emotional Exhaustion Subscale" (8 items) of the Chinese version of the Primary and Secondary School Teachers’ Job Burnout Questionnaire (CTJBQ) [ 83 ] to assess teacher burnout at Time 2. A modified version of the CTJBQ scale was developed on the basis of the Maslach Burnout Inventory [ 82 ] to accommodate the cultural and linguistic background of mainland Chinese teachers. The CTJBQ scale includes subscales measuring emotional exhaustion, including "After a day at work, I feel exhausted" and "I feel that teaching has exhausted me emotionally and mentally." Based on a 7-point Likert-type scale, responses ranged from 1 (strongly disagree) to 7 (strongly agree). A higher score indicates a greater degree of job burnout. This study found that good internal consistency for burnout scores (Cronbach’s alpha = 0.95, McDonald’s ω = 0.95).

3.2.3 Psychological distress.

In order to assess psychological distress at Time 2, this research utilized the Chinese version of the Depression, Anxiety, and Stress Scale (DASS-21) developed by Chan et al. [ 84 ]. It has been demonstrated that the Chinese version of the DASS-21 scale has satisfactory psychometric properties [ 85 , 86 ]. In addition, recent studies have shown that DASS-21 scores are a valid indicator of general psychological distress [ 87 , 88 ]. A four-point scale was used to evaluate items on the DASS-21, with higher scores indicating more severe psychological distress. DASS-21 scores demonstrated excellent internal consistency in this study (Cronbach’s alpha = 0.96, McDonald’s alpha = 0.96).

3.3 Data analysis strategy

In terms of data analysis, a descriptive analysis was first conducted to analyze the background characteristics of the participants. This was followed by Pearson correlation analysis to determine the means of all variables and their correlations. As a next step, HLM 6.08 software was used to analyze the data to test the hypotheses H 1 (H 1a , H 1b , H 1c ) and H 2 . HLM applies when observations in a study grouped in some way and the groups are selected randomly; therefore, it is commonly used to analyze nested data [ 79 ]. Model testing proceeded in four phases: null model, random intercepts model, means-as-outcomes model, intercepts- and slopes-as-outcomes model [ 89 ]. In this research, an intercepts-as-outcomes model was implemented, as we intended to examine the impact of school-level perceived instructional leadership on job burnout and psychological distress, rather than focusing on the moderating effect of variables. Based on this model, all the demographic variables investigated were treated as control variables except for subject of instruction, which is a category variable. Thus, more dummy variables were generated. Also, the variable for subject of instruction did not have a significant impact on the dependent variables or mediator variables and different subject teachers did not differ significantly in the means of these variables. The specific formulae for HLM are as follows:

Teacher level:

To verify H 3 , a bootstrapping method was applied with 5000 random samples in order to test the indirect mediating effect of job burnout. Specifically, this path is labeled as a 2-1-1 model, with these three numbers representing the levels of the independent variable, mediator variable, and dependent variable. Specifically, the independent variable was at the school level (level 2) and both the mediator and dependent variable were both at the teacher level (level 1) (burnout and psychological distress). The indirect effect was tested using model 4 of Hayes’ PROCESS macro [ 90 ] by placing all variables at the teacher level, as in [ 91 ]. As a result of using the bootstrapping method, the path coefficient and confidence interval were obtained. It can be concluded that a mediation effect is established if the confidence interval does not contain 0 [ 92 ].

HLM essentially serves as an extension of regression analysis [ 79 ]. Before delving into the primary statistical analysis, we rigorously assessed key assumptions tied to regression, including linearity, multivariate normality, and the absence of autocorrelation and multicollinearity. We employed Quantile-Quantile (QQ) plots (refer to S3 and S4 Figs) to evaluate linearity and multivariate normality, with the plots closely following a straight line, indicating an approximately linear and normal distribution of residuals. For the dependent variable "burnout", the Goldfield-Quandt test (statistic = 1.08, p = 0.22) and the Durbin-Watson test (DW statistic = 1.93, p = 0.26) confirmed the absence of heteroskedasticity and significant autocorrelation, respectively. Similarly, for "psychological distress", the Goldfield-Quandt test (statistic = 0.83, p = 0.98) and the Durbin-Watson test (DW statistic = 2.03, p = 0.71) yielded consistent results. Additionally, all Variance Inflation Factor (VIF) values were below 1.7, indicating no multicollinearity issues.

4.1 Descriptive statistics and Pearson correlations

Before presenting the results of this study, a confirmatory factor analysis (CFA) was performed using diagonally weighted least squares estimation (DWLS) in light of the fact that DWLS is more suitable to the analysis of ordinal Likert-type scales [ 93 ]. The results of the CFA were presented in the appendix (see S4 and S5 Tables). Both the model fit (CFI = 0.985, NNFI = 0.984, RMSEA = 0.037, SRMR = 0.057) and the factor loadings (larger than 0.5) demonstrated satisfactory factorial validity in this study. Furthermore, the average variance extracted (AVE) values (see Table 1 ) are generally greater than 0.5, indicating acceptable convergent validity.

https://doi.org/10.1371/journal.pone.0305494.t001

Table 1 displays the demographic characteristics of the study participants, including their gender, teaching experience, subject of instruction, and school type (primary or secondary). It is estimated that 81.4% of participants are females. Regarding teaching experience, 24.2% of the participants had less than 5 years of experience, while 25.8%, 18.3%, 9.9%, and 21.8% had 6–10 years, 11–15 years, 16–20 years, and more than 20 years of experience, respectively. Among the participants, 35.8% taught Chinese, 33.1% taught mathematics, 12.7% taught English, 6.1% taught natural sciences (physics, chemistry, biology, geography), and 11.3% taught other subjects. Of the participants, 30.4% were from primary schools, and the remaining were from secondary schools.

Table 2 presents the means, standard deviations (SD), and Pearson correlation coefficients for the variables included in the study. The correlation coefficients show a significant positive association between perceived instructional leadership (perceived school neglect of teaching autonomy, school neglect of teaching competence, emphasis on competitive relationships) and burnout and psychological distress ( r = 0.15 to 0.59).

https://doi.org/10.1371/journal.pone.0305494.t002

Table 3 presents the results of HLM analysis. The null model with job burnout and psychological distress as outcome variables yielded ICC values of 0.035 and 0.005. Despite the small ICCs, HLM was not abandoned since additional dependence on higher-level grouping can arise after including explanatory variables into the models [ 94 ]. The use of multilevel analysis is not precluded by small ICCs [ 10 ]. Therefore, we continued to use HLM for our research objectives.

https://doi.org/10.1371/journal.pone.0305494.t003

The results of the intercepts-as-outcomes model, displayed in Eqs ( 1 ) and ( 2 ), reveal that, after controlling for relevant variables, perceived school neglect of teaching autonomy has a significant positive impact on teachers’ job burnout ( β = 0.38, SE = 0.17, p = 0.02), which supports H 1a . However, perceived school neglect of teaching competence and emphasis on competitive relationships did not significantly impact burnout negatively, indicating that H 1b and H 1c were not supported. Additionally, the model shows that job burnout significantly and positively impacted psychological distress ( β = 0.18, SE = 0.01, p <0.01), supporting H 2 .

To test the third hypothesis, the mediating effect of job burnout between perceived school neglect of teaching autonomy and teachers’ psychological distress was examined based on the results of the first hypothesis. The bootstrapping method was applied with 5000 random samples, and the indirect effect was found to be significant [indirect effect = 0.046, 95% CI (0.031, 0.061)], which supports the proposed model wherein perceived school neglecting: teaching autonomy had a significant indirect effect on teachers’ psychological distress through job burnout. Therefore, it can be concluded that perceived school neglecting: teaching autonomy has a significant impact not only on teachers’ job burnout but also on their psychological distress, highlighting the importance of addressing this issue in schools.

5 Discussion

The educational landscape has been profoundly affected by the COVID-19 pandemic, with the closure of schools presenting a myriad of challenges for educators. A plethora of studies have underscored the multifaceted challenges teachers faced, ranging from the rapid adaptation to novel teaching technologies [ 95 ] to an escalation in workload [ 9 , 96 ]. Furthermore, a palpable lack of administrative support [ 10 , 28 , 32 ] has exacerbated the psychological distress experienced by educators. This research augments the existing body of knowledge by elucidating the ramifications of instructional leadership that overlooks the essence of teaching autonomy. Such neglect has been identified as a salient precursor to psychological distress, with burnout serving as a mediating factor. Notably, the study did not discern any significant effects stemming from the perceived neglect of teaching competence or the emphasis on competitive relationships within educational settings.

A pivotal revelation of this investigation is the detrimental impact of perceived institutional disregard for teaching autonomy during school closures. This adverse effect manifested prominently in the form of burnout and persisted even as educators transitioned back to traditional, in-person teaching modalities. This aligns with prior research which posits that diminished autonomy can be a catalyst for protracted burnout [ 27 , 36 , 60 , 61 ]. Conversely, some studies [ 36 , 97 ] have championed the protective role of perceived autonomy against burnout, particularly during the pandemic. These studies have enumerated several avenues to bolster teacher autonomy, encompassing flexibility in curriculum delivery, platform selection, and scheduling. Empirical evidence has consistently shown a positive correlation between teacher autonomy and pivotal outcomes such as motivation, instructional quality [ 98 ], empowerment [ 99 ] and job satisfaction [ 100 ], while inversely correlating with burnout [ 62 ]. The significance of autonomy in pedagogical settings cannot be overstated, especially given its pivotal role in teacher retention [ 100 ]. The deprivation of such autonomy, particularly in online pedagogical settings, can precipitate a cascade of negative outcomes, including diminished motivation, dissatisfaction, and pronounced burnout [ 62 ]. It’s noteworthy that the autonomy under scrutiny pertains to the latitude teachers had during online instruction, encompassing their discretion in pedagogical methodologies. The enduring impact of this neglect on educators’ mental well-being resonates with findings from Besser et al. [ 8 ] and Wakui et al. [ 101 ].

Contrastingly, this study’s findings diverge from the anticipated outcomes regarding the neglect of teaching competence and the emphasis on competitive relationships among educators. Such factors did not emerge as significant contributors to burnout. This observation is buttressed by findings from Huang et al. [ 102 ] and Yang and Huang [ 103 ], which highlight the plethora of resources available to educators during the pandemic, enabling continuous pedagogical skill enhancement. Consequently, it can be inferred that perceived school neglect of teaching competence might not be a salient determinant of burnout. Moreover, while competitive relationships can undoubtedly engender a less collegial environment, the virtual nature of instruction during the pandemic might have attenuated the impact of such competition on burnout. However, as educational institutions gravitate back to traditional teaching modalities, fostering a collaborative ethos among educators, underscored by mutual support and feedback, is paramount. This collaborative approach, coupled with the evident significance of autonomy, is pivotal for the holistic well-being of educators [ 104 ].

Further buttressing the findings of this study is the established linkage between educators’ burnout and psychological distress [ 38 , 39 , 71 , 72 ]. Burnout, typified by sustained negative affect related to pedagogical duties, can culminate in enduring psychological distress among educators [ 105 ]. This study’s findings also corroborate the mediating role of burnout between the perceived neglect of teaching autonomy and psychological distress, aligning with the conceptualization of burnout as a strain in SSO models [ 42 , 43 , 74 , 75 ]. Specifically, the study spotlighted the neglect of teaching autonomy by instructional leadership during school closures as a prominent stressor, culminating in protracted burnout and psychological distress.

Furthermore, the results derived from hierarchical linear modeling (HLM) underscored that perceived instructional leadership (perceived school neglect of teaching autonomy and competence, and emphasis on competitive relationships) did not have a direct bearing on psychological distress. Thus, this investigation substantiates the mediating role of burnout between perceived instructional leadership and educators’ psychological distress, aligning seamlessly with the SSO model.

Despite the valuable insights this study offers, there are several limitations to consider. Firstly, our sample was not randomly selected, which might constrain the generalizability of the findings to all middle and high school teachers in mainland China. Moreover, we did not include other teacher categories, such as kindergarten or university educators. Secondly, in order to efficiently access teachers’ perceived instructional leadership under pandemic conditions, we used a directive leadership as the special form of instructional leadership, which lead that our measurement of perceived instructional leadership is limited by epidemic. Future research would benefit from the development of a dedicated scale to assess perceived instructional leadership.

6 Conclusions

This study underscores the significant role that instructional leadership can play as a stressor for teachers over the long term in the pandemic, especially when it overlooks teaching autonomy. The findings indicate that when teachers perceive instructional leadership as neglecting their autonomy, it can have a profound and lasting impact on their job burnout. This, in turn, can detrimentally affect their mental well-being.

While strategies such as bolstering teacher resilience and ensuring more robust support from colleagues and managers are essential, our study also emphasizes the importance of enhancing teaching autonomy. Schools should prioritize giving teachers more ownership over their teaching methods, facilitated by sustainable leadership practices that emphasize life-long learning. Given the intricate nature of teaching, sustainability in the profession undoubtedly requires the autonomy that allows teachers to adaptively address students’ needs. This is especially true considering the challenges posed by the pandemic on teachers’ motivation and job satisfaction. As schools transition back to in-person teaching in the post-pandemic era, it becomes imperative to respect teachers’ pedagogical choices, grant them increased autonomy in the classroom, and nurture their self-efficacy and innovative capabilities. Such measures are crucial for the long-term mental health and overall well-being of teachers.

Supporting information

S1 checklist. strobe-checklist..

https://doi.org/10.1371/journal.pone.0305494.s001

S1 Fig. The result of optimal design.

https://doi.org/10.1371/journal.pone.0305494.s002

S2 Fig. The corresponding relationship between perceived instructional leadership and PNTSIOT.

https://doi.org/10.1371/journal.pone.0305494.s003

S3 Fig. Q-Q Plot of residuals as burnout dependent variable.

https://doi.org/10.1371/journal.pone.0305494.s004

S4 Fig. Q-Q Plot of residuals as psychological distress dependent variable.

https://doi.org/10.1371/journal.pone.0305494.s005

S1 Table. Items of psychological need thwarting of online teaching scale.

https://doi.org/10.1371/journal.pone.0305494.s006

S2 Table. Items of emotional exhaustion subscale.

https://doi.org/10.1371/journal.pone.0305494.s007

S3 Table. Items of DASS-21.

https://doi.org/10.1371/journal.pone.0305494.s008

S4 Table. Model fit.

https://doi.org/10.1371/journal.pone.0305494.s009

S5 Table. Factor loadings of CFA.

https://doi.org/10.1371/journal.pone.0305494.s010

S1 File. Data source.

https://doi.org/10.1371/journal.pone.0305494.s011

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• 102. Huang R, Liu D, Tlili A, Yang J, Wang H. Handbook on facilitating flexible learning during educational disruption: The Chinese experience in maintaining undisrupted learning in COVID-19 outbreak. Beijing: Smart Learning Institute of Beijing Normal University. 2020; 46.

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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Blog Teaching

This blog post was published under the 2015-2024 conservative administration.

https://teaching.blog.gov.uk/2020/06/02/life-as-a-teacher-during-lockdown/

Life as a teacher during lockdown

Addison Brown, science teacher at Bedford High School in Leigh, shares his experience of juggling family life with the pressures of being a teacher during lockdown.

Like every teacher in the country my job has changed drastically over the past couple of months. Standing in front of 30 children to share my passion for science every day is what I love most about teaching. Dealing with not being able to do that has been a massive adjustment.

But, like everyone, I’ve got used to a ‘new normal’. I am at home with my 9-month-old son, Stevie, while my wife, an urgent care nurse, has gone back to work after maternity leave. It’s been amazing to spend so much more time with my son. At the same time, it has been hard to keep a family going while balancing the pressures of work.

Working from home I have to fit my job around my family - I try and find time to work whenever I can, while my son is napping or when my wife is back from her shifts. But my colleagues understand the difficulties of childcare and so they have been really great in helping me out during this time. I’m very grateful to have their support.

What I’ve really missed is talking to and interacting with the kids when I’m teaching. When you’re doing everything online during lockdown, it’s easy to forget that I’m doing a job that I enjoy so much. So when I’ve had the odd day in school it’s felt great to be back there with the children of key workers. Seeing them all reminds me how grateful and lucky I am to do a job that I love doing!

I’ve learnt a lot from all the ups and downs of this unusual time. Although there have been many challenges, there has also been a huge amount of positivity that has come out. For example, the appreciation for teachers and the way communities have come together. Now I’m really looking forward to going back to school and getting back into the classroom. But I hope we’ll all look back and take something from this time, which will shape the way we live our lives so that we all feel more grateful for what we have and what we do.

A week in the life of a teacher

I shared a glimpse of what life is like as a teacher during these unusual times by posting a video on the Department for Education’s Instagram page every day for a week. If you missed it, you can watch the combined compilation video below:

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Comment by Hanane posted on 02 June 2020

We all learnt from this unusual situation Addison! Teachers been our heroes as well. Keep sending work to children, feedbacks, offering help. it’s amazing!! . I Was struggling in the beginning as I’m a trainee teacher having two children. Big thanks to them and to all the teachers around the country for their superb help and support.

Comment by Mark Stevens posted on 18 June 2020

With my school closing due to COVID 19 I was landed with the task of no work as PPA cover as a Music specialist- so I have spent the last 13 weeks as a Home schooler with my 13 and 9 year old. I abandoned the idea of trying to recreate the school day as it didn’t really work. My children completed online lessons in the morning then I took over in the afternoon - my own designed lessons consisted of studying historical figures such as George Washington and Churchill , SPAG studies , got them to write reviews of their favourite films , studying healthy eating habits and yesterday we chose the song ‘Stand by me’ we learnt it , talked about it then wrote the lyrics down artistically and presented them. We’ve changed plugs , looked at acronyms and wrote surreal stories - the quest goes on.

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