Impact of COVID-19 on participation and barriers in nonformal adult education in the Czech Republic

Eur J Educ. 2023;58:681–698. | 681 wileyonlinelibrary.com/journal/ejed DOI: 10.1111/ejed.12580 ORIGINAL ARTICLE Impact of COVID19 on participation and barriers in nonformal adult education in the Czech Republic Jan Kalenda1 | Ilona Kočvarováa1 | Ellen Boeren2 1Research Centre of the Faculty of Humanities, Tomas Bata University, Zlín, Czech Republic 2School of Education, University of Glasgow, Glasgow, UK Correspondence Jan Kalenda, Research Centre of the Faculty of Humanities, Tomas Bata University, nám. T. G. Masaryka 5555, Zlín 760 01, Czech Republic. Email: [email protected] Abstract The impact that the COVID19 pandemic has had on nonformal adult education has become a frequently discussed issue in lifelong learning. Nonformal adult education is understood here as all organised adult learning outside formal education that usually does not result in official certification. Many scholars have considered the pandemic as the leading cause of both decreased participation in nonformal adult education and increased inequality among adults. Nevertheless, it has not yet been empirically established how profound this outcome has been for participation patterns, inequality and perceived barriers to involvement in nonformal adult education. Accordingly, this study explored how much the pandemic contributed to a decrease in overall participation, changes in participation patterns, as well as contributed to an increase in related inequalities in the Czech Republic. This article reports on results from a national representative survey in June 2020 (N = 1013) conducted between the first and second wave of the pandemic. Trends in participation in nonformal adult education along with barriers were mapped for the 12 months preceding the survey. To establish trends, we compared our results with data from the Adult Education Survey conducted in 2011 and 2016, respectively. Our analytical approach is primarily based on descriptive statistics and modelling factors influencing the involvement of adults This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2023 The Authors. European Journal of Education published by John Wiley & Sons Ltd. 682 | KALENDA et al. 1 | INTRODUCTION The consequences of the COVID19 pandemic, as understood today, are worse than anyone could have imagined in the fall of 2019. The reported number of cases reached over 460 million worldwide, with over 6 million deaths registered (Hopkins, 2021). The global economy suffered an estimated mediumterm economic loss of approximately sixteen trillion dollars (Cutler & Summers, 2020). Whether the COVID19 pandemic is considered a disjuncture (Bjursell, 2020), a catalyst (Käpplinger & Lichte, 2020), a disruption (Paciorek et al., 2021), or as something that exposed the “fragility of education systems” (Milana et al., 2021, p. 111), it has profoundly changed the landscape of adult education and learning. As a leading international expert noted in an interview for an ongoing international Delphi project investigating the outcomes of the pandemics, “the lockdown of physical cooperation touches the heart of adult education” (Käpplinger & Lichte, 2020, p. 782). The worldwide spread of the disease has led to an interruption of longstanding practices of adult education and training based on in person interaction of instructors and learners in classroom settings, with tuition often provided at the workplace itself. The effects of the COVID19 pandemic represent a topic that is increasingly discussed in the context of lifelong learning. Yet, relatively little direct empirical evidence has been accumulated on how it has shaped the immediate pattern of participation in nonformal adult education as well as barriers to this type of adult education. Accordingly, the main purpose of this study was to explore how governmental health measures and restrictions put in place during the first wave of the pandemic in the Czech Republic affected participation in nonformal adult education. In this article, nonformal adult education is understood as learning activities conducted outside the formal education system that usually do not result in official certification. Nonformal adult education includes all organised and planned development learning opportunities for adults, such as courses, workshops, private tuition as well as guided training in the workplace or at an offsite location. From a content point of view, this includes both joboriented or vocational as well as nonjoboriented learning, e.g., civic, community, or leisure activities (Eurostat, 2016; UNESCO, 2020). The results of many policy papers (EC, 2021; OECD, 2019; UNESCO, 2020) and scholars (e.g., Boeren, 2016; Field, 2012; IñiguezBerrozpe et al., 2020; Van Nieuwenhove & De Wever, 2021) agree that nonformal adult education helps individuals to develop the skills and qualifications needed for a particular job, as well as to adapt to real or potential difficulties on the labour market, e.g. worker obsolescence. Furthermore, nonformal adult education also increases opportunities for civic participation and improves overall health and wellbeing. Understanding changes in the pattern of participation is important given the transformational significance of these patterns on the microsocial characteristics of adults' access to nonformal adult education. The lack of access is considered the most pertinent factor of educational inequality in adult education and training in nonformal adult education. We found that overall participation in nonformal adult education decreased from June 2019 to June 2020 to its lowest recorded level. Furthermore, the results indicate that inequality based on educational attainment, as well as the perception of substantial institutional and situational barriers have significantly increased. KEYWORDS adult education and learning, barriers to participation, COVID19 pandemic, Czech Republic, inequality, nonformal education, participation 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 683 KALENDA et al. (see e.g., Allmendinger et al., 2011; Boeren, 2016, 2017; Cincinnato et al., 2016; Dämmrich et al., 2014; Hovdhaugen & Opheim, 2018; Lee & Desjardins, 2019). Current research about the impacts of the COVID19 pandemic on nonformal adult education has produced evidence on how educators have applied new types of pedagogies for social solidarity (Smythe et al., 2021); new modes of community learning has emerged in cities (Webb et al., 2020); and the issue of exclusion of certain social groups from learning activities. Exclusion is an issue especially for those who before COVID had already been highly or at least partially excluded (Milana et al., 2021; Waller et al., 2020). A recent OECD report titled Adult Learning and COVID19: How much informal and nonformal learning are workers missing? (Paciorek et al., 2021) provides estimates for the consequences of COVID19 restrictions on the involvement of adults in informal and nonformal learning. The only other recent largescale data on relationships between pandemics and the participation of adults in nonformal adult education can be found in Eurostat's Labour Force Survey (LFS). This EU monitoring tool traditionally maps participation rates in both formal and nonformal education and training, in the 4 weeks preceding the survey, among adults aged 25– 64 years. Table 1. summarises the development across the last few years along with crucial changes from 2019 to 2020. The table shows that some countries in Europe experienced a higher decline during the first two waves of the pandemic than did other nations. The participation rate in adult education fell at an especially high rate in France, Czech Republic, Poland, and Austria, with all these countries undergoing a relative decrease in participation of higher than 20 percent. Interestingly, these countries do not fall into the same categories with regard to participation rate, or skillformation regime (Busemeyer, 2015), welfarestate model (Rubenson & Desjardins, 2009), or adult education system (Desjardins et al., 2006; Desjardins & Ioannidou, 2020). The pandemic also hit hard in the Scandinavian countries of Denmark, Sweden, and Norway, where a decrease in participation of between 15 and 17 percent was noted. In contrast, participation rates in other states decreased significantly less; a number of countries experienced stagnation or even modest growth in 2020— Spain, Portugal, Greece and Lithuania (see Table 1.). Statistics from the Labour Force Survey can provide a general overview of COVID19 related trends throughout Europe. However, these data cannot tell the whole story of how the pandemic impacted the participation patterns in nonformal adult education; that is, the significance of microsocial factors influencing the involvement of adults in this kind of organised learning and the barriers that they face. Such patterns subsequently determine the involvement of different social groups in nonformal adult education, with the result being a further deepening of already existing inequalities. Data from the Labour Force Survey also cover a shorter time frame (4 weeks) compared to other international surveys measuring participation in adult education and training such as the Adult Education Survey (AES) and the Programme for the International Assessment of Adult Competencies (PIAAC). Both AES and PIAAC are carried out over the course of 12 months. Additionally, these surveys collect extra information on barriers preventing participation. 1.1 | Context and aims of the study There are significant differences among European countries regarding the impact of the COVID19 pandemic on nonformal adult education from late 2019 to 2020. For this reason, we begin by briefly describing the context of the spread of the virus in the Czech Republic and the concomitant governmental reactions. Since February 2020, the COVID19 pandemic has affected adults and their families in many ways in the Czech Republic. The main part of the first wave lasted only 4 months (March to June). There was a low number of casualties compared to other countries in Europe (e.g., Italy or Spain). Still, the Czech government introduced many social contact restrictions also typical for other Central European countries such as Germany, Austria, Slovakia, and Poland (Barberia et al., 2021). The main directives took effect on 12 March 2020, when the government declared a 30day state of emergency that was later extended until 30 April 2020. From 12 March, all formal and official nonformal adult educational facilities such as private language schools and reskilling organisations were closed, with events organised 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 684 | KALENDA et al. TABLE 1 Development of participation in adult education in Europe from 2015 to 2020. 2015 2016 2017 2018 2019 2020 Diff. 2015– 2019a Relative. Diff. 2015– 2019 Diff. 2019– 2020a Relative. Diff. 2019– 2020 EU 27 countries 10.1 10.3 10.4 10.6 10.8 9.4 0.7 6.0 −1.4 −13.0 Countries with high participation rates (over 15% in 2015) Denmark 31.5 28.0 26.9 23.5 25.3 20.4 −6.2 −25.0 −4.9 −19.0 Sweden 29.4 29.6 30.4 31.4 34.3 28.6 4.9 14.0 −5.7 −17.0 Norway 20.1 19.6 19.9 19.7 19.3 16.4 −0.8 −4.0 −2.9 −15.0 Finland 25.4 26.4 27.4 28.5 29.0 27.3 3.6 12.0 −1.7 −6.0 Netherlands 18.9 18.8 19.1 19.1 19.5 18.8 0.6 3.0 −0.7 −4.0 France 18.6 18.8 18.7 18.6 19.5 13.0 0.9 5.0 −6.5 −33.0 Countries with medium participation rates (8%– 15% in 2015) Austria 14.4 14.9 15.8 15.1 14.7 11.7 0.3 2.0 −3.0 −20.0 Estonia 12.4 15.7 17.2 19.7 20.2 17.1 7.8 3.0 −3.1 −15.0 Spain 9.9 9.4 9.9 10.5 10.6 11.0 0.7 7.0 0.4 4.0 Portugal 9.7 9.6 9.8 10.3 10.5 10.5 0.8 8.0 00.0 Germany 8.1 8.5 8.4 8.2 8.2 7.7 0.1 1.0 −0.5 −6.0 Czech Republic 8.5 8.8 9.8 8.5 8.1 5.5 −0.4 −5.0 −2.6 −32.0 Countries with low participation rates (under 8% in 2015) Lithuania 5.8 6.0 5.9 6.6 7.0 7.2 1.2 11.0 0.2 3.0 Hungary 7.1 6.3 6.2 6.0 5.8 5.1 −1.3 −22.0 −0.7 −12.0 Italy 7.3 8.3 7.9 8.1 8.1 7.2 0.8 10.0 −0.9 −11.0 Latvia 5.7 7.3 7.5 6.7 7.4 6.6 1.7 23.0 −0.8 −11.0 Serbia 4.8 5.1 4.4 4.1 4.3 3.7 −0.5 −12.0 −0.6 −14.0 Poland 3.5 3.7 4.0 5.7 4.8 3.7 1.3 27.0 −1.1 −23.0 Greece 3.3 4.0 4.5 4.5 3.9 4.1 0.6 15.0 0.2 5.0 Note: Data provided as percentages; participation measured as involvement in all adult education activities as of 4 weeks prior to survey. aDifference in percentage points. Participation of adults aged 25– 64 years calculated together in both formal and nonformal education. Source: Table constructed by authors using 2021 data from Eurostat (LFS, 2021). 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 685 KALENDA et al. by these institutions prohibited. Furthermore, the governmental measures also included stringent restrictions for brickandmortar business establishments involved in retail sales and other services, with physical premises generally ordered to close or their activities strictly regulated (Czech Government, 2021). In an attempt to alleviate the negative social and economic effects of these directives, the government quickly developed and instituted support programs for companies and workers, e.g., by compensating workers for lost wages and implementing online learning initiatives across the formal education system. Only after 30 April, when the first round of protective measures began to be relaxed, were businesses gradually permitted to reopen their brickandmortar locations and other institutional activities were allowed to resume. For example, in midMay pupils in the last year of primary education were permitted to return to school as well as students in the last year of secondary schools and conservatories. The slow reopening of universities and other educational institutions soon followed. Despite the gradual easing of restrictions, many measures remained in place until the end of July, when government officials declared that the Czech Republic had overcome the first wave of COVID19 (Czech Government, 2021). The aim of this study was to contribute to an assessment of the direct impact of the COVID19 pandemic on participation patterns in nonformal adult education in a more detailed way. This article presents our analysis of findings from a nationally representative questionnaire survey among adults in the Czech Republic (N = 1013). It is important to note that the survey was carried out from June 2019 to June 2020. This was before the surge of the second wave of the COVID19 pandemic in August 2020. The twelvemonth period leading up to the survey was in the study used as a reference period for participation in nonformal adult education. Based on the data from this survey along with data from AES 2011 and 2016, the article describes and analyses the effects of governmental health measures and restrictions during the first wave of the pandemic in terms of three key interrelated phenomena: 1. level of participation in nonformal adult education 2. pattern of participation in terms of those who participated and who did not (inequality in participation based on crucial microsocial variables) 3. pattern of perceived barriers to involvement among nonparticipants We propose that by targeting these three interrelated topics, our findings will contribute to understanding how the COVID19 pandemic has reshaped participation patterns as well as obstacles connected with involvement in nonformal adult education. The data from the analysis can help institutions formulate effective education policy and practices for dealing with the adverse outcomes of the pandemic. In the context of international comparative research (e.g., Cabus et al., 2020; Cincinnato et al., 2016; Dämmrich et al., 2014; Lee & Desjardins, 2019), our results show the impact of the first wave of pandemic on the adult education system in one of the most negatively affected European countries in terms of the participation in nonformal adult education as well as how responses to the pandemic reinforced the inequality already existing in the system. Used here as in the AES and PIAAC survey, the term participation denominates involvement, during 12 months leading up to the survey, in any nonformal adult education activities as defined above. This operationalisation enabled us to cover a broader period than the LFS. This allowed us to compare the level of inequality and perceived barriers based on data from AES 2016 as well as data from before the outbreak of the COVID19 pandemic. 2 | REVIEW OF THE IMPACT OF THE COVID19 PANDEMIC ON PARTICIPATION AND BARRIERS TO NONFORMAL ADULT EDUCATION The lockdown restrictions for physical interactions, and other social distancing restrictions, in combination with the rapid proliferation of digital learning resulted in more negative outcomes for nonformal adult education than was the case for the formal (higher) education system. The reason for this seems to be that universities 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 686 | KALENDA et al. were able to adapt to the new digital learning circumstances more quickly, effectively and efficiently (AguileraHermida, 2020; BacherHicks et al., 2021). The change to online learning has intensified the ongoing decline in nonformal adult education participation since 2019. Remarkably, according to some authors (Milana et al., 2021), it has also increased inequality between prospective participants in formal education and those who could take part in nonformal adult education. Those in the second category may face more constraints as well in terms of a reduced supply of educational opportunities (Paciorek et al., 2021). Drawing on these circumstances, we formulate a first hypothesis: Hypothesis 1. Governmental measures related to the COVID19 pandemic led to a greater decrease in participation in nonformal adult education than in formal adult education. The COVID19 pandemic affected negatively the participation rates in nonformal adult education. But it also affected the pattern of participation, i.e., how groups of adults participate, or do not participate. According to numerous studies (e.g., Bonal & González, 2020; Milana et al., 2021; Stanistreet et al., 2021; Waller et al., 2020), the pandemic situation has profoundly increased social inequality in nonformal adult education as well as in other adult educational areas. First, overall inequality has expanded. Those already disadvantaged before the onset of the pandemic have been hit the hardest. These are loweducated adults, lowskilled workers, older adults, immigrants, people from rural or peripheral areas, and women (Boeren et al., 2020; Käpplinger & Lichte, 2020; Waller et al., 2020). Most of these adults were already in a difficult position within the labour market; others were completely outside the market, with even fewer opportunities for learning and development. The 2021 OECD report (Paciorek et al., 2021, p. 3– 4) details how much informal and nonformal learning workers have missed. The report estimates that loweducated employees (with schooling up to ISCED level 3c) have experienced a reduction in nonformal adult education learning opportunities at a rate of over twice as much as is the case for tertiaryeducated adults (ISCED 5– 8). Second, the previous trend was made even worse by the proliferation of digital inequality (Stanistreet et al., 2021). In practice, already disadvantaged social groups were often not sufficiently equipped with adequate digital technology or access to the internet, or they lacked the skills to use these tools. As a result, those with a lower participation rate also tended to have lower skills with regard to using digital tools to find, evaluate and compose information on digital platforms (see Milana et al., 2021, p. 112). In light of the previous examples, we conclude that the pandemic represents a chain of compound effects increasing an existing pattern of inequality. A pattern that draws on occupation status, education level, and age of the adults. Based on this summary, we propose three additional hypotheses. Hypothesis 2. Governmental measures related to the COVID19 pandemic led to an increased inequality in nonformal adult education participation by labour status. Hypothesis 3. Governmental measures related to the COVID19 pandemic led to an increased inequality in nonformal adult education participation by highest attained education. Hypothesis 4. Governmental measures related to the COVID19 pandemic led to an increased inequality in nonformal adult education participation by the age of the adults. Following the ChainofResponse model created by Cross (1981) adult education research has traditionally distinguished three types of perceived barriers that hinder participation in nonformal adult education (e.g. Hovdhaugen & Opheim, 2018; Rubenson & Desjardins, 2009; Van Nieuwenhove & De Wever, 2021): (1) dispositional, (2) institutional and (3) situational barriers. The first type of barrier is associated with the negative attitudes of 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 687 KALENDA et al. adults to education and low levels of selfefficacy regarding organised learning (Cross, 1981). In contrast, institutional barriers are obstacles associated with the supply of adult education (e.g., Cross, 1981; Hovdhaugen & Opheim, 2018). These usually include lack of educational opportunities within or outside the workplace, lack of information about learning opportunities, and perceptions regarding the quality of the education and training quality offered. According to Cross (1981), situational barriers are directly connected with obstacles found in the everyday lives of adults, for example a person's health status, family responsibilities (e.g., care for children), available economic resources, and the amount of time the adult has for learning. It is evident that the COVID19 pandemic has impacted both the overall structure of the barriers and the strength of several of them. In many countries, including the Czech Republic, the initial implementation of governmental restrictions directly influenced institutional barriers— mainly adult learning opportunities in the workplace and community settings. When the supply of such opportunities becomes more limited, perceptions of institutional barriers increase. In addition, a number of previously described adverse outcomes of COVID19 for adults with comparatively fewer years of schooling may negatively impact the perception of institutional barriers in segments of this population. Generally, because of the nature of their work, lack of digital skills, and typically less investment in their training from employers (Brunello et al., 2007; Paciorek et al., 2021; UNESCO, 2020), we can expect that institutional barriers to participation would show more significantly increases in this group. We thus formulate the following hypotheses: Hypothesis 5. Governmental measures related to the COVID19 pandemic led to an increased perception of institutional barriers to nonformal adult education among adults, especially among those with comparatively fewer years of education. Furthermore, governmental restrictions have changed the daytoday lives of adults, a factor inseparably linked to situational constraints. For example, many parents were forced to take more responsibility for their children's education during the lockdown, transforming the family responsibilities of parents. Additionally, the pandemic increased the importance of situational barriers related to health. Human contact was restricted. There was fear of infection, and rising distrust in institutions— possibly one of the most significant sets of situational barriers (Adolph et al., 2021; Kubinec et al., 2020). Therefore, a marked increase in the perception of situational barriers— especially barriers related to health as well as to family responsibilities and concerns— was expected. To make matters worse, these barriers tend to be more robust in two groups who are already disadvantaged— older adults and adults who have family responsibilities, usually women. In this context, Lewis and Duch (2021) reported that according to their mateanalysis, men consistently express a lower perceived risk of contracting COVID19 and less concern about the potential health consequences compared to women. Consequently, we would expect a higher perception of healthrelated barriers among women. Recent studies (Andersen et al., 2022; Del Boca et al., 2020) have also found that women were forced to personally take on more duties for childcare and housework in their own household than they had before the COVID19 pandemic. Due to school lockdowns and the distribution of many women in sectors of the economy that enable remote work, women were put into a situation in which they had to fulfil two demanding roles at the same time. On the one hand, women had to help their children cope with learning in the home, while on the other, they were still responsible for completing their employment tasks and duties. Such a situation made the involvement of women in nonformal adult education more difficult. Based on this discussion, we have formulated the following, and final, three research hypotheses. Hypothesis 6. Governmental measures related to the COVID19 pandemic led to an increase in the perception of situational barriers to nonformal adult education across all sociodemographic groups. 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 688 | KALENDA et al. Hypothesis 7. Governmental measures related to the COVID19 pandemic led to an increase in the perception of situational barriers to nonformal adult education related to health, especially among older learners. Hypothesis 8. Governmental measures related to the COVID19 pandemic led to an increase in the perception of situational barriers to nonformal adult education related to family responsibilities, most significantly among women. 3 | METHOD The analysis draws on a stratified random sample (n = 1013) that represents the age range 18– 69 years, as well as the gender and education ratios of the Czech population. Data collection was financed by The Czech Science Foundation (GACR), with research for this study financed by an internal university fund. Data collection was conducted in the Czech Republic during June 2020, between the first and second wave of the COVID19 pandemic. Data was collected by a professional agency using the Computer Assisted Personal Interviewing (CAPI) method. The questionnaire included basic sociodemographic characteristics (gender, age, highest education level, and regional affiliation based on level 2 in the Nomenclature of Units for Territorial Statistics, etc.). Questions on information about participation in nonformal adult education and other types of education were included. A battery of 29 scale items covering different barriers to participation in nonformal adult education was also included (Kočvarová et al., 2022); and other items not used in the present study. In all phases of the survey process, emphasis was placed on the ethical principles of research, especially anonymity respecting the ICC/ESOMAR International Code (ESOMAR, 2016). For comparison, we also worked with Czech data from AES 2011 and 2016, which we formally obtained for research purposes from the Czech Statistical Office. We included in the analysis only respondents who showed no missing values within the monitored variables (n = 10,168 for 2011; n = 12,245 for 2016). In 2020, the perception of barriers towards participation in further adult education was measured only among nonparticipants in nonformal adult education. To acquire similar results for this part of our investigation, we utilised data from AES 2011 and 2016 only for nonparticipants with no missing values within the monitored variables. As a result, we included the following number of respondents for the testing of hypotheses five and eight (n = 7009 for 2011; n = 2017 for 2016; n = 761 for 2020). The sociodemographic distribution of the three samples (each for 1 year of investigation) can be found in Table 2. For the purposes of the analysis, it was first necessary to bring together the three datasets to compare the results. For this, we carried out a harmonisation of the data, or unification, in three steps: (1) setting unit parameters across datasets (age 18– 69, no missing values for investigated variables); (2) choice of questionnaire items with the same focus (gender, age, highest level of education, participation in education, items representing barriers to participation); (3) unification of alternative answers to questions related to items measuring barriers to participation. The answers yes or no were used for responses in AES 2011 and 2016 questionnaires. Meanwhile, in our survey from 2020 answers on a 6point scale of three positive and three negative options were used— these were recoded into yes or no answers. Nevertheless, even after unification of the data files, it was not possible to merge files. The files were for this reason analysed separately. To assess the first hypothesis, on participation in education, we compared descriptive statistics (frequencies, percentages) over time. The second and fourth hypotheses, both related to inequality in participation in nonformal adult education, were assessed using three models of binary logistic regression (each for one dataset). We used participation in nonformal adult education as a dependent variable. Employment status, highest educational attainment, and age were used as independent variables. The models were evaluated using statistical parameters 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 689 KALENDA et al. related to their quality, by following their factual results, and a comparison of the parameters over time. The fifth and eight hypotheses, which relate to barriers of nonparticipation in nonformal adult education, were evaluated using descriptive statistics and a comparison of results over time. 4 | RESULTS 4.1 | Overall participation The results are presented by three themes that correspond with the three main aims of the study. We start by presenting, in Table 3, results for the first hypothesis relating to participation rates. In the context of developments to date, a rapid decline in participation in nonformal adult education in 2020 is revealed. In contrast, participation in formal education appears to be higher than in previous years. Based on this, we can confirm our first hypothesis TABLE 2 Sociodemographic distribution of the three samples. Year of investigation 2011 2016 2020 n%n%n% Gender Male 4861 47.8 5845 47.7 480 47.4 Female 5307 52.2 6400 52.3 533 52.6 Age 18– 29 1945 19.1 1887 15.4 184 18.2 30– 50 4118 40.5 4863 39.7 439 43.3 51– 69 4105 40.4 5495 44.9 390 38.5 Highest education level ISCED 3c or lower 4851 47.7 5769 47.1 494 48.8 ISCED 3ab 3640 35.8 4369 35.7 358 35.3 ISCED 5– 8 1677 16.5 2107 17.2 161 15.9 Reduced samplesa Gender Male 3348 47.8 773 38.3 359 47.2 Female 3661 52.2 1244 61.7 402 52.8 Age 18– 29 1276 18.2 475 23.5 126 16.6 30– 50 2428 34.6 830 41.2 318 41.8 51– 69 3305 47.2 712 35.3 317 41.7 Highest education level ISCED 3c or lower 3961 56.5 975 48.3 416 54.7 ISCED 3ab 2287 32.6 720 35.7 251 33.0 ISCED 5– 8 761 10.9 322 16.0 94 12.4 aSamples used for testing perception of barriers to nonformal adult education. Source: Authors. 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 696 | KALENDA et al. Another limitation is the fact that the analysis focusing on the participation pattern is based on three different datasets. Although it was possible to merge the data from AES (2011 and 2016), we do not consider this connection to be apposite with the dataset from 2020. Merging the data from all three surveys would have had a negative impact on the results of statistical inference. Therefore, all comparative results are only indicative and cannot be unambiguously generalised. The same can be said for the measurement of perceived barriers, for which response items had to be recoded. Despite these study limitations, we believe that our empirical results present substantial new evidence of how much and how deeply the first phase (2019– 2020) of the COVID19 pandemic has affected the participation pattern in nonformal adult education in the Czech Republic. Based on our methodology and these results, we anticipate revisiting the recovery of this type of lifelong learning in of our next research project. DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. ENDNOTES 1 The item Offer was defined as “no suitable education or training activity available”; the item Prerequisites was defined as: “respondent not qualified for participation due to prerequisites”. 2 The item Health was articulated as “health reasons”; the item Family was articulated as “family responsibilities”. REFERENCES Adolph, C., Amano, K., BangJensen, B., Fullman, N., & Wilkerson, J. (2021). Pandemic politics: Timing statelevel social distancing responses to COVID19. Journal of Health Politics, Policy, and Law, 46(2), 211–233. AguileraHermida, A. P. (2020). College students' use and acceptance of emergency online learning due to Covid19. International Journal of Educational Research Open, 1, 100011. https://doi.org/10.1016/j.ijedro.2020.100011 Allmendinger, J., Kleinert, C., Antoni, M., Christoph, B., Drasch, K., Janik, F., Leuze, K., Matthes, B., Pollak, R., & Ruland, M. (2011). Adult education and lifelong learning. Zeitschrift für Erziehungswissenschaft, 14(2), 283–299. Andersen, D., Toubøl, J., Kirkegaard, S., & Bang Carlsen, H. (2022). Imposed volunteering: Gender and caring responsibilities during the COVID19 lockdown. The Sociological Review, 70(1), 39–56. https://doi.org/10.1177/00380 26121 1052396 BacherHicks, A., Goodman, J., & Mulhern, C. (2021). Inequality in household adaptation to schooling shocks: Covidinduced online learning engagement in real time. Journal of Public Economics, 193, 104345. https://doi.org/10.1016/j. jpube co.2020.104345 Barberia, L., Plümper, T., & Whitten, G. D. (2021). The political science of Covid19: An introduction. Social Science Quarterly, 105(5), 1–9. https://doi.org/10.1111/ssqu.13069 Bjursell, C. (2020). The COVID19 pandemic as disjuncture: Lifelong learning in a context of fear. International Review of Education, 66(2), 673–689. https://doi.org/10.1007/s1115 902009863 - w Boeren, E. (2016). Lifelong learning participation in a changing policy context. An interdisciplinary theory. Palgrave Macmillan. Boeren, E. (2017). Understanding adult lifelong learning participation as a layered problem. Studies in Continuing Education, 39(2), 161–175. Boeren, E., Roumell, E. A., & Roessger, K. M. (2020). COVID19 and the future of adult education: An editorial. Adult Education Quarterly, 70(3), 201–204. https://doi.org/10.1177/07417 13620 925029 Bonal, X., & González, S. (2020). The impact of lockdown on the learning gap: Family and school divisions in times of crisis. International Review of Education, 66(2), 635–655. https://doi.org/10.1007/s1115 902009860 - z Brunello, G., Garibaldi, P., & Wasmer, E. (2007). Education and training in Europe. Oxford University Press. Busemeyer, M. R. (2015). Skills and inequality. Partisan politics and the political economy of education reforms in western welfare states. Cambridge University Press. Cabus, S., IlievaTrichkova, P., & Štefánik, M. (2020). Multilayered perspective on the barriers to learning participation of disadvantaged adults. Zeitschrift für Weiterbildungsforschungm, 43(2), 169–196. https://doi.org/10.1007/s4095 502000162 - 3 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License | 697 KALENDA et al. Cincinnato, S., de Wever, B., van Keer, H., & Valcke, M. (2016). The influence of social background on participation in adult education: Applying the cultural capital framework. Adult Education Quarterly, 66(2), 143–168. Cross, P. K. (1981). Adults as learners. Increasing participation and facilitating learning. JosseyBass. Cutler, D. M., & Summers, L. H. (2020). The COVID19 pandemic and the $16 trillion virus. Jama, 324(15), 1495–1496. https://doi.org/10.1001/jama.2020.19759 Czech Government. (2021). Measures adopted by the Czech government against the coronavirus. Government of the Czech Republic. Dämmrich, J., Vono, D., & Reichart, E. (2014). Participation in adult learning in Europe: The impact of countrylevel and individual characteristics. In H.- P. Blossfeld, E. KilpiJakonen, D. Vono de Vilhena, & S. Buchholz (Eds.), Adult learning in modern societies: Patterns and consequences of participation from a lifecourse perspective (pp. 25–51). Edward Elgar. Del Boca, D., Oggero, N., Profeta, P., & Rossi, M. (2020). Women's and men's work, housework and childcare, before and during COVID19. Review of Economics of the Household, 18, 1001–1017. https://doi.org/10.1007/s1115 002009502 - 1 Desjardins, R., & Ioannidou, A. (2020). The political economy of adult learning systems— Some institutional features that promote adult learning participation. Zeitschrift für Weiterbildungsforschungm, 43(2), 143–168. https://doi. org/10.1007/s4095 502000159 - y Desjardins, R., Rubenson, K., & Milana, M. (2006). Unequal chances to participate in adult learning: International perspectives. UNESCO. EC. (2021). Towards a sustainable Europe by 2030. In European Commission. Publication Office. Eurostat. (2016). Classification of learning activities manual. Publications Office of the European Union. Eurostat. (2021). Adult learning. Labour Force Survey. Field, J. (2012). Is lifelong learning making a difference? Researchbased evidence on the impact of adult learning. In D. Aspin, J. Chapman, K. Evans, & R. Bagnall (Eds.), Second international handbook of lifelong learning (pp. 887–897). Springer. Hopkins, J. (2021). COVID19 dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). Available at: https://coron avirus.jhu.edu/map.html Hovdhaugen, E., & Opheim, V. (2018). Participation in adult education and training in countries with high and low participation rates: Demand and barriers. International Journal of Lifelong Education, 37(5), 560–577. https://doi. org/10.1080/02601 370.2018.1554717 IñiguezBerrozpe, T., ElbojSaso, C., Flecha, A., & Marcaletti, F. (2020). Benefits of adult education participation for loweducated women. Adult Education Quarterly, 70(1), 64–88. https://doi.org/10.1177/07417 13619 870793 Kalenda, J., Kočvarová, I., & Vaculíková, J. (2020). Determinants of participation in nonformal education in The Czech Republic. Adult Education Quarterly, 70(2), 99–118. https://doi.org/10.1177/07417 13619 878391 Käpplinger, B., & Lichte, N. (2020). “The lockdown of physical cooperation touches the heart of adult education”: A Delphi study on immediate and expected effects of COVID19. International Review of Education, 66(5– 6), 777–795. https://doi.org/10.1007/s1115 902009871 - w Kočvarová, I., Vaculíková, J., & Kalenda, J. (2022). Development and initial validation of the nonparticipation in nonformal education questionnaire. Journal of Psychoeducational Assessment, 40(3), 400–415. https://doi.org/10.1177/07342 82921 1060571 Kubinec, R., Carvalho, L., Barceló, J., Cheng, C., Messerschmidt, L., Duba, D., & Cottrell, M. S. (2020). Fear, partisanship and the spread of COVID19 in the United States. SocArXiv. Available at: https://osf.io/prepr ints/socar xiv/jp4wk/ Lee, J., & Desjardins, R. (2019). Inequality in adult learning and education participation: The effects of social origins and social inequality. International Journal of Lifelong Education, 38(3), 339–359. https://doi.org/10.1080/02601 370.2019.1618402 Lewis, A., & Duch, R. (2021). Gender differences in perceived risk of COVID19. Social Science Quarterly, 1– 10, 2124–2133. https://doi.org/10.1111/ssqu.13079 LFS. (2021). Participation rate in education and training (last 4 weeks) by sex and age. Labour Force Survey. https://ec.europa. eu/euros tat/datab rowse r/view/TRNG_LFS_01/defau lt/table ?lang=en Milana, M., Hodge, S., Holford, J., Waller, R., & Webb, S. (2021). A year of COVID19 pandemic: Exposing the fragility of education and digital in/equalities. International Journal of Lifelong Education, 40(2), 111–114. https://doi. org/10.1080/02601 370.2021.1912946 OECD. (2019). Getting skills right: Futureready adult learning systems. OECD Publishing. Paciorek, A., Manca, F., & Borgonovi, F. (2021). Adult learning and COVID19: How much informal and nonformal learning are workers missing? OECD Publishing. https://doi.org/10.1787/56a96 569en Roosmaa, E.- L., & Saar, E. (2017). Adults who do not want to participate in learning: A crossnational European analysis of their barriers. International Journal of Lifelong Education, 36(3), 254–277. https://doi.org/10.1080/02601 370.2016.1246485 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 698 | KALENDA et al. Rubenson, K. (2018). Conceptualizing participation in adult learning and education. Equity issues. In M. Milana, S. Webb, J. Holford, R. Waller, & P. Jarvis (Eds.), The Palgrave international handbook on adult and lifelong education and learning (pp. 337–357). Palgrave Macmillan. Rubenson, K., & Desjardins, R. (2009). The impact of welfare state requirements on barriers to participation in adult education: A bounded agency model. Adult Education Quarterly, 59(3), 187–207. https://doi.org/10.1177/07417 13609 331548 Saar, E., Ure, O. B., & Holford, J. (2013). Lifelong learning in Europe. National Patterns and challenges. Edward Elgar. Smythe, S., Wilbur, A., & Hunter, E. (2021). Inventive pedagogies and social solidarity: The work of communitybased adult educators during COVID19 in British Columbia, Canada. International Review of Education, 67(1), 9–29. https:// doi.org/10.1007/s1115 902109882 - 1 Stanistreet, P., Elfert, M., & Atchoarena, D. (2021). Education in the age of COVID19: Implications for the future. International Review of Education, 67(1), 1–8. https://doi.org/10.1007/s1115 902109904 - y UNESCO. (2020). Embracing a culture of lifelong learning. Contribution to the futures of education initiative. UNESCO Institute for Lifelong Learning. Van Nieuwenhove, L., & De Wever, B. (2021). Why are loweducated adults underrepresented in adult education? Studying the role of educational background in expressing learning needs and barriers. Studies in Continuing Education, 44, 189–206. https://doi.org/10.1080/01580 37X.2020.1865299 Waller, R., Hodge, S., Holford, J., Milana, M., & Webb, S. (2020). Lifelong education, social inequality and the COVID19 health pandemic. International Journal of Lifelong Education, 39(3), 243–246. https://doi.org/10.1080/02601 370.2020.1790267 Webb, S., Holford, J., Hodge, S., Milana, M., & Waller, R. (2020). Learning cities and implications for adult education research. International Journal of Lifelong Education, 39(5– 6), 423–427. https://doi.org/10.1080/02601 370.2020.1853937 How to cite this article: Kalenda, J., Kočvarováa, I., & Boeren, E. (2023). Impact of COVID19 on participation and barriers in nonformal adult education in the Czech Republic. European Journal of Education, 58, 681–698. https://doi.org/10.1111/ejed.12580 14653435, 2023, 4, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/ejed.12580 by Univerzita Tomase Bati In Zlin, Wiley Online Library on [05/01/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License