Abstract
The increasing use of information and communications technologies (ICT) in education has raised concerns about exacerbating existing educational inequalities, particularly for students who lack interest or confidence in using digital devices. Drawing from data of the Programme for International Student Assessment (PISA), this chapter documents the extent to which school-aged children in Europe are digitally disengaged and/or lack digital confidence. We also analyse the socio-economic and demographic characteristics that describe both profiles. By shedding light on these challenges, this research can inform policies and interventions aimed to ensure equitable access and success in digital learning environments.
You have full access to this open access chapter, Download chapter PDF
Similar content being viewed by others
Keywords
Introduction
A public debate has been raging since the 1970s (Tichenor et al., 1970) regarding digital transformations as well as the digital divides caused by them. Concerns have been raised about the consequences of the digital divide which can lead to new forms of social disadvantage and/or inequality (Wong et al., 2015; Datta et al., 2019; Goggin, 2019). The COVID-19 pandemic and the unprecedented worldwide health emergency associated with it acted as an accelerator leading to a paradigm shift and a series of digital transformations around the world.
Generally, the lack of access to ICT has been seen as a major cause of social exclusion—especially nowadays, when there are increased expectations of ICT being used in education. Factors that explain digital divides are linked to geography, gender, disability, age, and socio-economic status (Ayllón et al., 2023; Kuc-Czarnecka, 2020; Livingstone et al., 2005; Livingstone & Helsper 2007; Ragnedda & Muschert, 2019; Senkbeil et al., 2019). There is growing public concern that children, particularly those with fewer technological resources or unreliable Internet access, could fall behind in their educational development (Lai & Widmar, 2021; Cullinane & Montacute, 2020; Frenette et al., 2020; Lourenco & Tasimi, 2020; Ayllón et al., 2023). This body of research has been referred to in the literature as the ‘first-level’ digital divide.
Moving beyond access, and despite the high levels of Internet diffusion across countries (van Deursen et al., 2011), students of today are still not equally equipped for their technology-rich future: various kinds of digital divides persist in society and affect the young generation and their digital futures (Ivari et al., 2020; van Deursen & van Dijk, 2019). Hargittai (2002) considers such differences to be ‘second-level’ digital divides. In this respect, ICT interest and confidence both play an essential role in the acquisition of digital skills, which are, in turn, fundamental in terms of eradicating digital inequalities (Areepattamannil & Santos, 2019; Hu et al., 2018). New measures to prevent a widening of the digital gap are therefore crucial in alleviating the significant existing differences in digital competence and knowledge of ICT and in preventing further marginalisation.
Drawing on data from the Programme for International Student Assessment (PISA) from 2015 and 2018, this chapter provides evidence-based insights that seek to explain some aspects of digital skills polarisation and existing differences in terms of both interest in ICT and confidence in using it among school-aged children in Europe. It is important to stress here that analysing data for these years can provide valuable information into the impact of the COVID-19 pandemic on children and a historical perspective for the post-pandemic era, assisting us in understanding the challenges that children face in the digital world. Data from 2018 can be used for baseline comparisons to help us understand the extent of the shift in children’s online behaviour and digital habits. The data can reveal existing disparities in children’s access to ICT and how the pandemic exacerbated them. This information can provide valuable knowledge about children that were disproportionately negatively impacted by the pandemic and how to help them in the future.
The next section introduces the data and the methodology used, as well as our definition of digital disengagement and lack of digital confidence. Section “Results” shows our main results. Finally, section “Conclusions” summarises our main findings, proposes some policy recommendations, and discusses avenues for future research.
Data and Methodology
We use data from the 2015 and 2018 waves of the OECD’s PISA survey, which is designed to measure 15-year-old students’ ability to use their reading, mathematics, and science knowledge and skills to meet real-life challenges.Footnote 1 In particular, we use the 2018 ICT familiarity questionnaire, which asks children about digital media and devices and students’ attitudes towards them. We only consider children who have access to a desktop computer, portable laptop (or notebook), or tablet (e.g., iPad, BlackBerry, PlayBook) with an Internet connection, or to a smartphone (with Internet access) either at home or at school.Footnote 2 Table 2 in the Appendix shows the total number of observations by country.
We measure students’ interest in ICT using their answers to the following six questions: (1) ‘I forget about time when I’m using digital devices’; (2) ‘The Internet is a great resource for obtaining information I am interested in (e.g., news, sports, dictionary)’; (3) ‘It is very useful to have social networks on the Internet; (4) ‘I am really excited discovering new digital devices or applications’; (5) ‘I really feel bad if no Internet connection is possible’; and (6) ‘I like using digital devices’. All the questions have four possible answers—‘strongly disagree’, ‘disagree’, ‘agree’, and ‘strongly agree’—which we grade from 1 to 4. From the six questions and the four possible answers, we proxy each student’s interest in ICT using a Likert-type scale to total up the values of the defining items. We classify a child as ‘digitally disengaged’ if he or she has a score of 12 points or below. Such a score means that the children have mostly responded that they ‘strongly disagree’ or ‘disagree’ on all six questions.
We measure students’ confidence in ICT in a similar fashion, using their responses to the following group of questions: (1) ‘I feel comfortable using digital devices that I am less familiar with’; (2) ‘If my friends and relatives want to buy new digital devices or applications, I can give them advice’; (3) ‘I feel comfortable using my digital devices at home’; (4) ‘When I come across problems with digital devices, I think I can solve them’; (5) ‘If my friends and relatives have a problem with digital devices, I can help them’. Again, answers range from complete disagreement to total agreement; we coded these as explained above and similarly computed a Likert scale. We classify a child as ‘digitally unconfident’ if he/she has a score of 10 points or below.Footnote 3
A significant psychometric property of attitude measurement is reliability. By definition, such measurement is reliable if it is constant over time, provided the repeated measurements are conducted under consistent conditions and there has been no definite change in attitude. To assess reliability, Cronbach’s alpha reliability coefficients for the overall scale are calculated (Fabrigar et al., 1999). According to Nunnally and Bernstein (1994) and Revelle and Zinbarg (2009), a scale or subscale is reliable if Cronbach’s alpha coefficients are at least 0.70. The reliability analysis performed on the data does not indicate the need to exclude any questions, since Cronbach’s alpha reliability coefficients for the overall scale are greater than 0.70 for the whole of Europe and for each country, for both the ICT interest measure and the ICT confidence measure—being 0.91 for the former and 0.93 for the latter. See further details by country in Table 2 in the Appendix.
Table 1 shows the summary statistics of our sample. About 49.4% of the students were girls; 13.8% were of immigrant origin; and 10.1% reported having parents with a low level of education. As for a low level of family wealth and a low level of home possessions, 16.2% and 17.3%, respectively, of the children reported being in those situations. Moreover, 12.6% of the children were repeating a course. Finally, 10.5% of students had been bullied and 4.1% had no sense of belonging at school. See the exact definition of each variable in Table 3 in the Appendix.
Results
The main results indicate that, at the European level, the ICT interest score is 17.9 on average. In addition, Fig. 1 presents the scores by country. The choropleth map shows two country clusters, displaying a certain West-East divide. On the one hand, in Southern, Western, and Northern Europe, the ICT interest scores are high: for example, in Spain, France, and Sweden, the figures are 18.3, 18.7, and 18.3, respectively. On the other hand, in Eastern Europe, the ICT interest scores are as low as 16.3 in Albania and Bulgaria.
Furthermore, Fig. 2 shows the percentages of digitally disengaged children in Europe—which naturally is a mirror image of Fig. 1: where the ICT interest score is high, the percentage of digitally disengaged children is low, and vice versa. In Europe as a whole, 5.7% of children are digitally disengaged. However, the figures differ considerably for individual countries: whereas in Belgium (3.5%), France (4.8%), Germany (3.9%), and Spain (5.2%) the percentages of digitally disengaged children are low, in Eastern Europe digital disengagement is relatively high, with 17.3% in Bulgaria and 15.2% in Albania.
As for children’s confidence in using ICT, Fig. 3 shows the ICT confidence scores by country (the European average is 14.9). In the Mediterranean and Eastern Europe, ICT confidence is low: for example, in Italy, Bulgaria, and Albania, the ICT confidence scores are 14.5, 13.9, and 13.9. Meanwhile, in Northern and Anglophone Europe, the scores are relatively high: 15.4 in Sweden and 15.6 in the United Kingdom.
In Fig. 4, we display the percentages of digitally unconfident children by country (at the European level, 8% of children are digitally unconfident). As with the ICT confidence scores, again a certain West-East divide is to be seen. In Bulgaria, 16.8% of children said they did not feel comfortable using digital devices. It is the same story in Albania, where 14% of children are digitally unconfident. This phenomenon is to be found across much of Eastern Europe, whereas in Continental and Northern Europe—with the exceptions of Finland (11.1%), Austria (12.2%), and Iceland (12.7%)—the percentages of digitally unconfident children are relatively low.
Next, we want to analyse changes in the percentage of digitally disengaged children and those who lack digital confidence across European countries over time. For this exercise, we draw on PISA 2015 and calculate the percentages of digitally disengaged and unconfident children, as in Figs. 2 and 4. This trend analysis shows that, while some countries have moved towards increased levels of digital engagement and confidence, in others the situation has deteriorated, so that there are higher numbers of children who lack interest and confidence in the digital world.
Figure 5 shows the percentages of digitally disengaged children in 2015 and 2018. Countries that already had low percentages in 2015 generally maintained this level in 2018. However, a slight increase can be found in, for example, Estonia, Greece, Spain, Finland, and where the figures for digitally disengaged children increased by between 1 and 2 percentage points. In Poland, Slovenia Iceland, and the Slovak Republic, the figures increased by between 2 and 3 percentage points. Bulgaria, with an increase of 6 percentage points, stands out as the country where the number of digitally disengaged children increased the most. By contrast, in Austria, Belgium, and Luxembourg, the percentages dropped. Finally, Germany managed to reduce its digital disengagement by 2.8 percentage points.Footnote 4
Similarly, Fig. 6 displays the percentages of digitally unconfident children in 2015 and 2018. We see a decrease in their number in Austria, Germany, and Luxembourg. Again, Bulgaria is the country where the number of digitally unconfident children increased the most, by about 6.6 percentage points. Iceland, too, saw an important increase of 4.1 percentage points.
Now that we know where digitally disengaged and unconfident children live and how the phenomenon has evolved, we can try to find out which socio-economic and demographic characteristics define a digitally disengaged and digitally unconfident child. With that in mind, we run a series of logistic regressions, in which we consider seven vulnerable groups: (i) children of immigrant origin; (ii) those who cohabit with low-educated parents; (iii) those whose families have a low level of wealth; (iv) those whose families have a low level of home possessions; (v) those who need to repeat a year; (vi) those who have been bullied; and (vii) those who do not feel a sense of belonging at their school. As for ICT interest, our dependent variable takes the value 1 if the child is digitally disengaged and 0 otherwise. In the case of ICT confidence, again our dependent variable takes the value 1 if the child is digitally unconfident and 0 otherwise. Control variables include gender and the child’s age.Footnote 5 We also use country-fixed effects (to control for time-invariant country characteristics). Standard errors are robust and clustered at the country level and the results are weighted.
As shown in Fig. 7 and in Table 4 in the Appendix, at the European level one characteristic stands out as being very closely linked to children’s lack of interest in ICT: having to repeat a school year. On average across Europe, that increases the risk of suffering ICT disengagement by a factor of 1.7. Also, being bullied and having a low level of home possessions multiply the risk of digital disengagement by a factor of 1.7 and 1.4, respectively. A lack of sense of belonging at the school they attend is positively associated with digital disengagement: it increases the risk of suffering such problems by a factor of 1.4. The same is true for having low-educated parents: that multiplies the risk by a factor of 1.2. As for immigrant origin and level of wealth, we find that neither of those variables is statistically significant; meanwhile, being a girl and being older reduces the likelihood of being digitally disengaged.Footnote 6
The same analysis is performed by country cluster (see Fig. 8 and Table 4 in the Appendix).Footnote 7 We find that most of the risk factors considered are positively linked to digital disengagement. However, the relevance of the associations varies by country cluster, and, in general, such associations are weak, preventing us from reaching any very strong conclusions at the country-cluster level. In all country groups, the characteristics most associated with digital disengagement are the repetition of a school year and a low level of home possessions. In Northern Europe, having to repeat a year and having fewer family possessions increase the risk of being digitally disengaged by factors of 1.6 and 1.7, respectively, while in Anglophone Europe the figures are 3.2 and 2.0. No sense of belonging at school is also positively related to digital disengagement—except in Southern Europe, where the relationship is not statistically significant. The coefficient for low-educated parents is statistically significant and positively related to digital disengagement, as is being bullied, which increases the probability of being digitally disengaged in all contexts—except in Baltic Europe. As for immigrant origin, in Northern and Baltic Europe, the probability of being digitally disengaged increases with this characteristic, whereas in Anglophone Europe it decreases. Family wealth is not statistically significant in most country clusters.
As for children’s ICT confidence, Fig. 9 shows that, again, having to repeat a year and having a small number of home possessions are the factors most linked to the phenomenon: these increase the risk of being digitally unconfident by a factor of 1.5 and 1.4, respectively. Also, the subjective feelings of not belonging at school and of being bullied, and having a low level of wealth all increase the probability of a lack of digital confidence—by a risk factor of 1.8, 1.5, and 1.2, respectively. As for poorly educated parents, we find no statistically significant relationship. Immigrant origin and age again reduce the likelihood of being digitally unconfident, while being a girl increases it.
Finally, we move to the results by country cluster (see Fig. 10 and Table 5 in the Appendix). With very few exceptions, we find that most of the risk factors considered are positively linked to a lack of digital confidence. Again, having to repeat a year (with a risk factor ranging from 1.5 in Northern Europe to 2.0 in Anglophone Europe), a below-average number of home possessions (ranging from 1.2 in Continental Europe to 1.6 in Eastern Europe), and little sense of belonging at school (ranging from 1.4 in Baltic Europe to 2.1 in Anglophone Europe) are the strongest factors associated with lack of digital confidence. Baltic Europe is the only context in which having to repeat a year is not linked to ICT confidence. As for being bullied, the results are similar: that increases the probability of being digitally unconfident in all contexts. Low-educated parents and immigrant origin are not statistically significant in most clusters—except in Southern Europe, where those factors reduce the likelihood of being digitally unconfident. As for gender, in most countries being a girl increases the probability of lack of digital confidence. Finally, age reduces the probability in all the country clusters considered.
Conclusions
This chapter provides a detailed account of the number of digitally disengaged and digitally unconfident children in Europe. We use data from PISA from 2015 and 2018. Our indices capture students’ subjective opinions on both ICT interest and confidence, answering questions such as ‘I like using digital devices’ for ICT interest and ‘I feel comfortable using my digital devices at home’ for ICT confidence. Students had four possible answers, ranging from ‘strongly disagree’ to ‘strongly agree’, and based on these responses we define whether or not a child lacks digital interest and confidence.
Following our classification exercise for lack of digital interest and lack of digital confidence, we find that approximately 5.7% of 15-year-olds in Europe are digitally disengaged and 8% are unconfident about their ICT usage. However, across the countries of Europe, the figures vary in ways similar to the findings of Ayllón et al. (2023) regarding digital deprivation. For example, in Ireland, only 2.6% of children are digitally disengaged and 4% show no confidence, whereas in Bulgaria the figures are 17.3% and 16.8%. Despite the disparities between country clusters in terms of children’s socio-economic characteristics linked to ICT interest and confidence, we find that having to repeat a year and below-average home possessions (i.e., material deprivation) are the main determinants of digital disengagement and lack of confidence.
According to the Digital Education Action Plan 2021–2027 (action 11) a key policy aspect is the collection of cross-national data on students’ digital skills. In this direction, the results of this study reveal existing disparities amongst European countries concerning children’s interest and confidence towards ICT, disparities that should be addressed to provide support to children who were also disproportionately impacted by the pandemic. Relevant strategic goals address the need for quality education and reduced inequalities, to ensure that everyone has the opportunity to participate in the digital world and reap its benefits. Closing the digital gap is imperative as it has the potential to perpetuate and worsen existing social and economic inequalities. Efforts should be made to ensure that all children and young people, regardless of their background, can have access to and develop the skills necessary to effectively use digital technologies and respective tools. Policy initiatives should enhance children’s digital skills, which are now an essential pillar of the educational system. If we are to ensure equal opportunities in education, we need to address the digital divide not only in terms of access but also in terms of skills. Knowing who the digitally disengaged and unconfident children in Europe are, and identifying what socio-economic characteristics they share, it is crucial to design effective policies that address digital inclusion. Current and future political efforts should be made in this direction.
Finally, some limitations of our analysis should be noted. First, the unavailability of data regarding both computer and Internet access in some countries prevented us from analysing all the European countries. Second, our analysis by risk factors was restricted to the socio-economic variables contained in the PISA database, which prevented us from taking account of all possible dimensions of vulnerability.
Notes
- 1.
The data from PISA is freely available on the OECD website (http://www.oecd.org/pisa/data/).
- 2.
Note the impossibility for children to be interested in or confident about using technological devices when they do not even have access to them (Ayllón et al., 2023). Data regarding digital access is not provided for Germany; however, as the percentage of digital deprivation is low there, we include it anyway in the analysis (Ayllón et al., 2023).
- 3.
Note that some children did not answer all the questions considered in both indexes. However, for each student, if there is only one question missing, we impute such missing information using the mean value of the answers for the other questions in the same index. Children with two or more unanswered questions in each index are not considered.
- 4.
All differences reported in the text are statistically significant.
- 5.
Even though PISA only interviews 15-year-old children, the database contains concrete data about the age in years and months of each individual. See Table 1 for summary statistics.
- 6.
- 7.
We consider six country clusters: Northern Europe (Finland, Iceland, and Sweden), Southern Europe (Greece, Italy, Malta, and Spain), Eastern Europe (Albania, Bulgaria, Croatia, Hungary, Poland, Serbia, and the Slovak Republic), Continental Europe (Austria, Belgium, the Czech Republic, Denmark, France, Germany, Luxembourg, Slovenia, and Switzerland), the Anglophone countries (the United Kingdom and Ireland) and the Baltic area (Estonia, Latvia, and Lithuania).
References
Areepattamannil, S., & Santos, I. M. (2019). Adolescent students’ perceived information and communication technology (ICT) competence and autonomy: Examining links to dispositions toward science in 42 countries. Computers in Human Behavior, 98, 50–58. https://doi.org/10.1016/j.chb.2019.04.005
Ayllón, S., Holmarsdottir, H. B., & Lado, S. (2023). Digitally deprived children in Europe. Child Indicators Research, 16, 1315–1339. https://doi.org/10.1007/s12187-022-10006-w
Cullinane, C., & Montacute, R. (2020). COVID-19 and social mobility impact brief# 1: School shutdown. The Sutton Trust.
Datta, A., Bhatia, V., Noll, J., & Dixit, S. (2019). Bridging the digital divide: Challenges in opening the digital world to the elderly, poor, and digitally illiterate. IEEE Consumer Electronics Magazine, 8(1), 78–81. https://doi.org/10.1109/MCE.2018.2867985
Fabrigar, L., Wegener, D., MacCallum, R., & Strahan, E. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. https://doi.org/10.1037/1082-989X.4.3.272
Frenette, M., Frank, K., & Deng, Z. (2020). School closures and the online preparedness of children during the COVID-19 pandemic. Statistics Canada/Statistique Canada.
Goggin, G. (2019). Disability and digital inequalities: Rethinking digital divides with disability theory. In M. Ragnedda & G. W. Muschert (Eds.), Theorizing digital divides (pp. 69–80). Routledge.
Hargittai, E. (2002). Second-level digital divide: Differences in people’s online skills. First Monday, 7(4). https://doi.org/10.5210/fm.v7i4.942
Hu, X., Gong, Y., Lai, C., & Leung, F. K. (2018). The relationship between ICT and student literacy in mathematics, reading, and science across 44 countries: A multilevel analysis. Computers and Education, 125, 1–13. https://doi.org/10.1016/j.compedu.2018.05.021
Ivari, N., Sharma, S., & Ventä-Olkkonen, L. (2020). Digital transformation of everyday life – How COVID-19 pandemic transformed the basic education of the young generation and why information management research should care? International Journal of Information Management, 55, 102183. https://doi.org/10.1016/j.ijinfomgt.2020.102183
Kuc-Czarnecka, M. (2020). COVID-19 and digital deprivation in Poland. Oeconomia Copernicana, 11, 415–431. https://doi.org/10.24136/oc.2020.017
Lai, J., & Widmar, N. O. (2021). Revisiting the digital divide in the COVID-19 era. Applied Economic Perspectives and Policy, 43(1), 458–464. https://doi.org/10.1002/aepp.13104
Livingstone, S., & Helsper, E. (2007). Gradations in digital inclusion: Children, young people and the digital divide. New Media and Society, 9(4), 671–696. https://doi.org/10.1177/1461444807080335
Livingstone, S., Bober, M., & Helsper, E. (2005). Inequalities and the digital divide in children and young people’s internet use: Findings from the UK Children Go Online project. London School of Economics and Political Science.
Lourenco, S. F., & Tasimi, A. (2020). No participant left behind: Conducting science during COVID-19. Trends in Cognitive Sciences, 24(8), 583–584. https://doi.org/10.1016/j.tics.2020.05.003
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
Ragnedda, M., & Muschert, G. W. (Eds.). (2019). Theorizing digital divides. Routledge.
Revelle, W., & Zinbarg, R. E. (2009). Coefficients alpha, beta, omega, and the glb: Comments on Sijtsma. Psychometrika, 74(1), 145–154. https://doi.org/10.1007/s11336-008-9102-z
Senkbeil, M., Drossel, K., Eickelmann, B., & Vennemann, M. (2019). Soziale Herkunft und computer- und informationsbezogene Kompetenzen von Schülerinnen und Schülern im zweiten internationalen Vergleich [Social origin and computer and information-related competencies of schoolchildren in a second international comparison]. In B. Eickelmann, W. Bos, J. Gerick, F. Goldhammer, H. Schaumburg, K. Schwippert, M. Senkbeil, & J. Vahrenhold (Eds.), ICILS 2018 #Deutschland. Computer- und informationsbezogene Kompetenzen von Schülerinnen und Schülern im zweiten internationalen Vergleich und Kompetenzen im Bereich Computational Thinking (pp. 301–333). Waxmann.
Tichenor, P. J., Donohue, G. A., & Olien, C. N. (1970). Mass media flow and differential growth in knowledge. Public Opinion Quarterly, 34, 159–170. https://doi.org/10.1086/267786
van Deursen, A. J., & Van Dijk, J. A. (2019). The first-level digital divide shifts from inequalities in physical access to inequalities in material access. New Media and Society, 21(2), 354–375. https://doi.org/10.1177/1461444818797082
van Deursen, A. J., Van Dijk, J. A., & Peters, O. (2011). Rethinking internet skills: The contribution of gender, age, education, internet experience, and hours online to medium- and content-related internet skills. Poetics, 39(2), 125–144. https://doi.org/10.1016/j.poetic.2011.02.001
Wong, Y. C., Ho, K. M., Chen, H., Gu, D., & Zeng, Q. (2015). Digital divide challenges of children in low-income families: The case of Shanghai. Journal of Technology in Human Services, 33(1), 53–71. https://doi.org/10.1080/15228835.2014.998576
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix
Appendix
Rights and permissions
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Copyright information
© 2024 The Author(s)
About this chapter
Cite this chapter
Ayllón, S., Lado, S., Symeonaki, M. (2024). Digitally Disengaged and Digitally Unconfident Children in Europe. In: Holmarsdottir, H., Seland, I., Hyggen, C., Roth, M. (eds) Understanding The Everyday Digital Lives of Children and Young People. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-46929-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-031-46929-9_2
Published:
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-031-46928-2
Online ISBN: 978-3-031-46929-9
eBook Packages: Social SciencesSocial Sciences (R0)