Keywords

Introduction

The importance of international large-scale assessments for education policy and research has emerged in the last decades. Processes of international assessment are embedded in the broader context of the so-called globalization of educational data (Mundy et al. 2016), expressing the need of a numerical-based expertise. These have fostered comparative analysis and evaluation among countries and have been embraced by main international organizations. Large-scale international comparative surveys are designed to offer quantity-based measures that help policy to foster skills seeking to improve national evaluation. Broadly defined, those represent surveys of knowledge, skills, and behaviors that help to better understand how those are related to educational, economic, and social outcomes (Kirsch et al. 2013). There are different examples such as the OECD Survey of Adult Skills, Programme for International Student Assessment (PISA), the Progress in International Reading Literacy Study (PIRLS), or the Trends in International Mathematics and Science Study (TIMSS), among others. The Program for the International Assessment of Adult Competencies (PIAAC) is part of the OECD Survey of Adult Skills and is considered the largest and most innovative international assessment of adults’ skills (Kirsch and Lennon 2017). This is the first international large-scale computer-based assessment of adult population skills in 33 countries. Moreover, PIAAC has large sample size and include three domains of adults’ skills.

The conceptualization of each assessment and the decisions about which skills domains and which target group should be assessed are temporal and strategic. Like all concepts in the social sciences, the act of constructing measures implies a selection of dimensions (in Ancient Greek κατηγορια) (in Latin “category”.) which should be operationalized and thus leads to a simplification of the object of study. This means a transformation of some qualities into a metric which is not just a technical process but an important feature of social life (Desrosières 2008; Hacking 1999). This process is generally called commensuration and has been largely examined by different historians, statisticians, sociologist, and philosophers (Espeland and Stevens 1998). However, the selection of what counts as relevant information and how the information is processed is a crucial topic that rarely has been noted in the educational large sets through a Capability Approach. A main point in Amartya Sen’s Capability Approach is the concept of informational basis of judgment (IBJ).

The informational basis of judgment identifies the information on which the judgment is directly dependent – and no less important – asserts that the truth or falsehood of any other type of information cannot directly influence the correctness of the judgment. The informational basis of judgment of justice thus determines the factual territory over which considerations of justice would directly apply. (Sen 1990: 111)

For instance, the skills domains that PIAAC assesses and identifies as competences are part of a non-deliberatively discussed, but unanimously taken for granted, as foundational for maintaining competitiveness in a global knowledge economy, increasing the flexibility and responsiveness of labor markets, stimulating workforce participation, and dealing with issues of population aging (Schleicher 2008). While its main focus is to collect information about skills, PIAAC also collects data on educational, socioeconomic background and demographic of the respondents, as well as information on their labor market situation and participation in both formal and informal training.

Having noted the strategic importance of large-scale assessments such as a PIAAC where foundational skills are assessed, the interest in using this particular one and taking Spain as country of reference is the following. The global economic crisis and its large impact beyond economic spheres have proven that there is no simple way of fixing problems through economic stimuli. Particularly, Spain is a paradigmatic example. It has been well reported how the implications of the 2008 global crisis in Spain have had negative effects on employment, social equity, labor conditions, and health. With indicators scoring among the highest of the EU in terms of corruption, youth unemployment, and early school leaving (OECD 2017), the country’s best bet has been to embrace the EU and OECD slogan of “more skills for better jobs” (OECD 2013a).

The unequal impact of the crisis that considerably affected the workers with lower skills (Felgueroso 2016) has increased the awareness for training needs. There is a hope that better skills can lead to improvements of Spain’s economy, and this brings back to the traditional equation of skills, jobs, and growth that the human capital advisors have been claiming for decades. In terms of education, it puts vocational education and training into a new light, while for the education policy agenda, it gives greater relevance to the outputs of large-scale and comparative analyses.

The revival of a longtime neglected path of education, VET, has been noted by the European Commission as well as by the Spanish legislative attempts to influence the economy through modifications of the educational system.

Member States and other stakeholders (have to) put into practice the reforms needed to exploit the potential of VET for growth […] Skills are a key driver for growth, employment and competitiveness: they lay the foundation for productivity and innovation. (European Commission 2012: 1–4)

The main difference of the Spanish educational system with others lies in the particularly low number of students in VET. This inevitably affects the employability and competitiveness of our economy, limiting the life choices of many young people. (LOMCE 2013, sec. XIII)

In this quote, one can read how the concept of development, understood primarily in economic terms, is the main reason for fostering VET. Additionally, the particularity of Spain is that despite an estimated increase of 4 years of schooling in the period 1980–2010 (De la Fuente and Domenech 2014), and tripling the percentage of higher education graduates during this period (Felgueroso 2016), the share of participants in adult learning in Spain remains below the OECD average. Additionally, Spain has the third lowest average number of years of schooling in the OECD, just ahead of Portugal and Mexico (De la Fuente and Domenech 2014).

The challenge of this chapter is to use PIAAC, a large-scale assessment designed under a human capital framework, to explore the potentialities of it in another framework: the Capability Approach (CA). While data is increasingly being centralized in VET systems within the human capital framework, the CA offers a human-centered approach that shifts the focus of importance from economics to human development.

While vocational education and training is and needs to be linked to broader social functions, this chapter looks at the value of the skills beyond its direct economic return. To do that, the article departs from a large body of literature that reveals the benefits of the Capability Approach as far as it allows for a paradigm shift from a focus on economic growth and national income to a focus on human well-being (Robeyns 2005; Walker and Unterhalter 2007; Tikly and Barrett 2011). Concretely, the chapter sets on the emerging group of authors that recognize the importance of the Capability Approach for VET. As Powell and McGrath (2014) have argued, the value of a human-centered approach in the study of VET implies a shift from the “productivist” approaches that have traditionally dominated VET policy. McGrath (2012) on his research about VET argues about the urge of leaving aside income generation and economic growth indicators that see VET as a mean to achieve those, for imagining VET through the capabilities lenses where the concept of development is broaden and economic growth is seen as necessary but not as a unique paradigm. Powell (2013) in her review about the VET institutions asks the core question about how the informational sets to evaluate VET are chosen. Following that line of research, this chapter looks at the Spanish data of the Program of International Assessment of Adult Competencies (PIAAC) and poses questions about how it will change if the capability lenses would have been included in the design of the PIAAC’s survey.

Focusing on the Spanish case, and more concretely on the PIAAC indicators of political participation and social participation, this chapter expands classic VET and skills development evaluations. The analysis through a capability perspective aims to explore the relationships between unemployment and training participation and VET qualification. It explores how having a VET qualification affects a broad range of issues such as income, political participation, and personal factors. The article uses seemingly unrelated regression methods to test for this set of effects and compares the data and results of Spain with the 16 OECD countries from which good quality data are available. By doing so, we intend to contribute to the use of comparative international data beyond a mere competitive scheme based on rankings and consider a plurality of VET outcomes. Therefore, we contribute to the design of more effective and socially fairer educational policies. The chapter ends with a current picture and evaluation of the genuine opportunities that VET students in Spain have to contribute to the economy in terms of skills such as effective work, as well as to societal aspects by being first-generation immigrant student, breaking gender work stereotypes, or being socially and politically active.

In conclusion, this chapter focuses on two questions:

  • What does a capability perspective may add to the design of PIAAC?

  • What does PIAAC tell us about the implications of education in the building of a society?

The structure is the following. The first section introduces the Capability Approach and its added value as a normative framework for a large-scale assessment. The second explains the selection of data and the methods used for the data analysis. The third presents the evidence using some concepts of the Capability Approach. Finally, a fourth section concludes with recommendations for further analysis.

How Can the Capability Approach Contribute to the PIAAC?

The CA, developed by Amartya Sen and Martha Nussbaum, assesses well-being in terms of people’s ability to function and whether they are provided with the real opportunities – the capabilities – to choose the lives they have reason to value. This implies that an evaluation cannot be done merely in terms of outcomes, understood as the beings and doings of a person – such as working, studying, or being politically active. But rather, such evaluation will require looking at the capability space. The vector of capabilities or capability space are the combinations of valuable outcomes (functionings) that a person holds the possibility of achieving (Sen 1993: 31) – such as having the conditions for freedom of speech, having the conditions to attend education, having the opportunity for accessing a decent job, etc. So, capabilities are opportunities or freedoms to achieve what an individual reflectively considers valuable. Capabilities focuses on “what people are actually able to do and be and contrasts with other approaches to evaluation in which the emphasis tends to be on what people possess or do not possess, have done, or how they feel” (Brunner and Watson 2015: 5). As expressed by Powell and McGrath (2014), the Capability Approach provides a normative framework alternate to the output and efficiency measures usually centered on functionings (be these resources, qualifications, or abilities) as conventional VET evaluations do. The authors argue that these measures (2014: 133) do “not give us enough information on individual well-being as individuals might achieve the same functioning (for example a FET qualification) but have significantly different abilities to convert these into a functioning (for example employment).”

The most interesting aspect of this approach is putting to the forefront the individual and her/his desires alongside the context that shape the previous ones. The CA is a normative framework that differs from human capital approaches that measure skills or personal attributes without further digging into the aspect of context or personal diversity as pillar of social justice. The social justice principle that guides any CA design is equality of capabilities.

The information sets that guide current educational assessment are part of political strategies targeting at unemployment, poverty alleviation, and economic growth (McGrath 2012). This entails that the results obtained from a large-scale assessment as PIAAC will target education reforms for pursuing better results which are believed to lead to economic growth. Within the remits of this chapter, the CA aims to move from a human capital-centered approach to a human-centered one. It would ask to the data obtained from PIAAC to what extent a person is able to construct his or her “capability space” and in what terms have his or her individual and social context influenced the preferences and choices taken. As noted by Unterhalter (2017: 2) “the precision claimed for measurement may actually obscure the importance of what is not measured. There is thus a tension between what is easily measurable, but may not be significant, and what is of major importance, but cannot be measured.” This requires a broader informational base than traditional performance measurements, which are solely based on level of education, background, or economic context, and we are aware of the limitation that a quantitative analysis has in that aspect.

Difficulties in engaging in indicators have raised a number of discussions about the processes and selection of variables and information (Fukuda-Parr et al. 2014). As Unterhalter (2017) in her article about the limits of what is measurable points out, the discussions about measurement in education “have become part of a discourse of regulation linked to new public management, rather than a process to enhance democratic participation and review of decision-making” (Unterhalter 2017: 4).

Despite of this deficiency, the benefits of using the CA are present as it explores and links arguments of skills with issues of equity and sustainable development. The CA helps to formulate important questions at the individual level, in terms of how preferences are being formed, as well as at the policy level, in terms of what kind of development we are seeking to foster. Reformulating Sen’s famous question addressed in his Tanner Lecture of 1979 “Equality of What?” (1982), the role that the CA can play in this chapter as rethinking PIAAC is to ask “skills for what?” and at the same time present a social justice basis in which a developed society as one where individuals enjoy a broad space of capabilities as an alternative to the current human capital discourse that has inspired PIAAC.

There is a general consensus that without the right skills, people are left at the margins of society, technological progress does not translate into economic growth, and countries cannot compete globally (Barro and Sala-i-Martin 1995; Hanushek and Wößmann 2008). Regardless, a society is composed of citizens which are not merely workers producing economic outputs. CA provides a people-centered approach which considers the capability/opportunity space of everyone in relation to personal, social, and environmental aspects. Understanding sustainable development as something more holistic than economic growth, the CA stresses the importance of freedom of choice and the need to cultivate an active society that reassures the opportunity of each member to lead a meaningful life. From this, besides the concept of functioning and capability, two other concepts are key: the conversion factors and the aspect of agency.

The concept of conversion factors are aspects that enable, influence, and constrain the beings and doings of an individual (Robeyns 2003). Sen (2009: 255) identifies four factors that affect one’s choices and conversion of capabilities: personal heterogeneities (age, gender, disability, proneness to illness), physical environment (environmental conditions, including climatic circumstances, such as temperature ranges, or flooding), social climate (social conditions, public healthcare, community resources, policies and practices, public educational arrangements), and relational perspectives (patterns of behavior in a community that can affect one’s choices and capabilities). Everyone may vary greatly in their needs for resources or abilities to achieve their valued capabilities (Nussbaum 2000: 68). Therefore, the approach takes each human being as an end and rests on the idea of ethical individualism, which takes every individual as a subject of their own lives and “primary objects of moral concern” (Brighouse and Swift 2003: 258).

Agency is a key concept that intertwines with the aspect of freedom as well as with other capabilities such as the capability for voice (Bonvin 2012). As Sen remarks, people need to be understood as “active participants in change rather than passive and docile recipients of instruction or of dispensed assistance” (1999: 281). Thus, an agent is an individual who is willing to have a shared responsibility for building a process that ensures everyone’s capabilities to decide, to self-determine, and to bring about change in the world (Crocker 2008). Concretely, capabilities can be generated through individual efforts and collective processes, and, similarly, agency can be individual as well as collective (Ibrahim 2011). Here, the collective agency means individuals responsible for the development and empowerment of their own community and country (Crocker 2008). These two aspects of conversion factors as well as collective agency force us to see the individual with the duty of being a builder of the context where he or she belongs.

Consequently, the four concepts outlined briefly above are capability, as space of valuable opportunities; functionings, as valuable outcomes; conversion factors, as individual, social, and environmental conditions that influence in the ability of an individual to transform resources into valuable outcomes; and agent, as someone who is leading change. These require an intersectional or crossing data approach and going beyond the analysis of numeracy or literacy skills. Henceforth, the contribution of the CA is to expose the need to have a social justice framework since the moment of the design of the survey. It is relevant to know what the skills of people are but to act upon those one needs to consider data outcomes as the result of choices and then investigate the relation of those with their aspirations and contexts.

What Is PIAAC? Data, Methods, and Shortcomings

PIAAC is a large-scale assessment that seeks to test adult skills. The antecedents of this program were the International Adult Literacy Survey (IALS) (1994–1998) and the Adult Literacy and Life Skills Survey (ALL) (2004–2006). Global assessments of this kind are becoming more and more influential in international policy-making and are an important tool in the reform of education and training systems (Grek 2010; Meyer and Benavot 2013). Moreover, they are rapidly establishing themselves as a tool of governance that can influence the decisions of the actors involved (Desrosières 2002; Espeland and Sauder 2007; Grek 2009). In this chapter, we consider PIAAC as a source of valuable information for comparative analyses but do not repeat discussions concerning the reliability of adult skills measurement (Further information on measurement can be found in Gebhardt and Adams (2007), Goldstein (2004), and Svend (2011).). For a broader discussion on this topic, we refer the reader to Goldstein (2015) and OECD (2013b).

For the purposes of this analysis, we limited the sample to the population aged between 25 and 55 years. We restricted the analysis, therefore, to central age groups, to have the best estimate of the social outcomes of the active population. Older cohorts were excluded because they are likely to have experienced very different socialization process through the school system and they are likely to be out of the labor market. Younger cohorts were excluded because they are still attaining their highest education level. A robustness analysis confirmed the relevance of this sample restriction (In the Annex, “Determinants of Social Goals. Reference is Spain. PIAAC 2012, Population Aged 25–65 years” and “Determinants of Social Goals. Reference is Spain. PIAAC 2012, Population Aged 15–65 years” show the results for the population between 15–65 years and 25–65 years. The results are very similar except the effect of age is lower, and it has a less accentuated logarithm shape when younger and older cohorts are included.). We use the first wave of PIAAC to ensure comparability between Spain and the rest of the OECD. In fact, the field work of the two waves of PIAAC was made between 2012 and 2014; this has an effect in terms of labor market participation and other aspects of the interviewees. Australia was excluded from the analysis owing to the public unavailability of data, while data on Russia were omitted for reasons of data quality and the absence of certain crucial variables used in the model.

The final analytic sample consisted of approximately 75,000 individuals with full availability of data. Discrepancy between the sample sizes is given by the different number of missing values among the dependent variables. Political efficacy was the dependent variable with higher missing values which account for 1.8% of OECD and Spain samples. The objective of the model was to disentangle the effect of education, parental background, migration status, labor market status, and adult skills on different social goals or outcomes.

We use ordinary least squares regressions , although given the nature of the outcome variables, ordered logistic regression could be considered more appropriate. However, we prefer OLS vs. ordered logistic regression for two reasons. First, the former regression model needs more sample size compared to OLS; and, second, there were small cells between categorical predictors and dependent variables which represent a shortcoming in using such method. Finally, by comparing the results of one set of predicted values versus another, we obtained similar results using OLS and ordered logistic.

Following the PIAAC framework, foundational skills assessed in this survey are a core set that is assumed to be essential for “an individual to function in the knowledge economy” leaving aside concepts such aspirations, choices, or agency that we noted above as central from a capability perspective.

PIAAC is presented as having the major advantage of gathering the key skills to “function in society, to achieve one’s goals and to develop one’s knowledge and potential” (OECD 2012). Moreover, these skills are considered relevant for acquiring higher-order skills and to facilitate the retraining of individuals. In keeping with this objective, PIAAC adopts a “competence” approach – where competence is defined as the ability to apply knowledge and skills across environments and in interactive contexts that involve understanding, reflection, and judgment (OECD 2012) – and explores whether people are able to implement their knowledge in multiple contexts.

The skills domains assessed in PIAAC are literacy, numeracy, and problem-solving in technology-rich environments. The first two domains are evaluated using items distributed across three main task characteristics (medium, context, and aspect) and differentiated between paper and computer-based questions. PIAAC uses item-response techniques (IRT) to generate ten plausible values of each domain examined. The resulting scores do not allow an interpretation at an individual level, because the derived scores are not the individual results of the tests. The proxies of adult skills are strongly correlated, with an individual-level correlation between numeracy and literacy (problem-solving) of 0.85 (0.76). In the data analysis, we use literacy and numeracy, because the domain of problem-solving was not implemented in all the countries in PIAAC.

Additionally, PIAAC offers data on a few items of social outcomes. In the models presented in this chapter, we have included three out of the four existing proxies. Apart from the items included in our models, political efficacy, social trust, and cultural participation, there is also general health status. These are subjective self-reported measures coded in a 5-point Likert scale with positive cardinality. The items collect information whether:

  • The respondents believe in having no influence on government (political efficacy)

  • Whether they trust few people (social trust)

  • Or their involvement in cultural and voluntary work for nonprofit organization (cultural participation)

Almost six out of ten respondents reported of not being involved in cultural activity for nonprofit organization (see “Descriptive Statistics of the Social Outcomes”). While those are not considered as skills or competences per se, they are presented in PIAAC as relevant for enhancing society’s well-being. Following the human capital logic that more education leads to higher returns (Hanushek et al. 2015), PIAAC expands classic market outcomes such as productivity or earnings to nonmarket outcomes such as civic participation or health.

An Analysis Using the Capability Approach

The Capability Approach, as a response to the limitations of assessments that measure education in an uncritical, linear (cause-consequence) and homogenous perspective, has been extensively discussed and used in the literature (Walker and Unterhalter 2007). Using CA, this chapter extends the evidence by inquiring other social aspects and that are strictly linked with skills. The human capital approach lacks attention to other social goals and attaches a mere instrumental value of education measured on the base of individual and collective advantages such as employment or income returns (Oreopoulos and Salvanes 2011). However, its logic still defines evaluation instruments and, hence, policies (or vice versa). The main findings on the relationship between education in its different forms (i.e., years of attainment, skills, and adult lifelong learning) and the four different social outcomes measured in PIAAC are “that for EU average estimations proficiency in literacy, numeracy and problem-solving in technology-rich environments and participation in adult lifelong learning programs are positively and significantly associated with the probability of reporting high social trust, believing to have some impact on the political process, participating in volunteer activities and reporting good health” (EC 2014: 8). Hence, more years of education have a positive impact as citizens become more politically or socially engaged and healthier. While those results can be taken as good news, the data is limited about the impact on a plurality of social goals and their distribution. Thus, in terms of analyzing issues of equity and social justice, a study on adults’ skills should include questions addressing aspects concerning choices (not only nonmarket outcomes). Consequently, attending to the limitations of the data available, the capability lenses do not take numeracy and literacy as a simple limited outcome, but look to other social goals of adult skills.

Despite the constraints of analyzing a survey, conceived under a given framework, this chapter analyzes three social goals reported in PIAAC of adult skills using capability lenses (the same model is reported in the annex in “Determinants of Social Goals. Reference is Spain. PIAAC 2012, Population Aged 25–65 years” and “Determinants of Social Goals. Reference is Spain. PIAAC 2012, Population Aged 15–65 years” for different age-cohorts. For a matter of readability, throughout the text, we present the results comparing Spain with the OECD (Spain excluded). All the tables are available upon request to the authors.). Table 1 summarizes the results: the coefficients refer to Spain, and a dummy variable is included allowing comparing with the OECD average (Spain excluded). The size of the estimated OECDs indicates the extent of divergence in the outcome variables between OECD and Spain.

Table 1 Determinants of social goals. Reference is Spain. PIAAC 2012, Population aged 25–55 years
Full size table

As pointed out by different national and international reports, Spain scores below the OECD average in numeracy and literacy results (MEDC 2013). As the literature has pointed out, in Spain there is a high share of lower educated adults particularly in older cohorts, and this correlates with lower level of skills (Gustafsson 2016). Nevertheless, younger cohorts also report lower level of skills compared to OECD members (Valiente and Scandurra 2015). In Spain, poor parental education background and lower access to education qualification play an important role in adults’ skills formation and labor market access (Calero and Choi 2017). These are similar results to Italy another South-European country assessed in PIAAC. Nevertheless, postsecondary education access in younger cohorts in Spain is similar to that of OECD partners.

Looking at the individual conversion factors such as age, gender, and immigrant status, the results show some interesting insights. Older cohorts tend to have lower social trust but higher cultural engagement. Gender differences are presented, while women have lower level of skills, they have higher level of social trust, political efficacy, and cultural engagement. The results show that women, in the same circumstances as men, perceive higher social trust and belief in political efficacy and cultural engagement than men. Lacking further information about what determines these higher score, it is not possible to conclude that the difference is due to higher education attainment of women in Spain in the considered age group (as the human capital logic tells us) or if it is the result of lower expectations and hence adapted preferences.

Other adscriptive conditions, such as being migrant, have negative associations with numeracy and literacy (Isphording 2014; OECD 2000), although no significant difference is shown in terms of social outcomes. Important differences are presented in terms of parental education, as individuals with poor educational background tend to have lower level in all outcome variables considered. This is particularly interesting considering that parental background is recalled from the time respondents were 15, showing long-term effects after 10–40 years. Parental education is one of the most important drivers in the acquisition of numeracy and literacy, and it has a strong association with individual education attainment in all OECD countries in the PIAAC study (Scandurra and Calero 2017).

As higher education attainment is associated with higher levels of social outcomes, having a tertiary degree between 0.112 and 0.228 in the social outcomes assessed in PIAAC. However, breaking that logic again, the attainment of a vocational education and training has a nonsignificant effect on social outcomes. While the attainment of VET has a positive effect ranging between 10.7 and 16.8 points advantage, respectively, in literacy and numeracy, however its educational purpose is put into question. This leads to questioning the type of skills being fostered in VET and broader social goals connected to such types of education. In every social goal assessed in PIAAC, there are big differences in terms of educational attainment. This means that educational attainment plays are highly correlated with adult skills and social outcomes. Compared to a lower secondary education, having attained tertiary education entails approximately 0.2 standard deviations for social trust and political efficacy and 0.11 for cultural engagement. Similar effects are reported when comparing employed versus unemployed population or skilled versus elementary jobs. These differences are large and statistically significant. The statistical fit of the model (R-squared) is low for the three outcome variables social trust, political efficacy, and cultural engagement, accounting between 5% and 7% variation of those items.

Other social factors impede the consecution of similar outcomes based on gender, migration, and parental background. This difference might also relate to social, economic, and cultural cleavage that the education and training system partially fails to reduce. Crocker (2008) highlights that for a well-functioning society, “individuals and collectives (need to) have the freedom to make choices for themselves” (p. 163). Thus, these aspects should be present in the survey for a deeper analysis of adult skills formation and their social goals to help drawing policy measures and assessing the aspect of choice and individual preferences formation.

A relevant point to recall for interpreting the data is the period of data collection of PIAAC. The chapter uses first wave PIAAC data, which were collected in 2012. Therefore, it compares 16 of the OECD countries that participated in PIAAC within the same wave. We excluded countries of the second wave, for the time lag between the survey waves. The period of the assessment is very relevant because it is when the economic crisis hit harshest, and this had implications in terms of labor market participation and a plurality of social goals. Specifically, for Spain, during this period job losses were concentrated in low-educated low-skills workers, which before the Great Recession were attracted by a booming labor market particularly rich in low-skills occupation (e.g., real-estate; construction). This has implied a high rate of early school leavers and lower participation in VET students. (According to the data of the Ministry of Education the number of enrolments in VET in Spain has increased around by 40% since the 2009–2010 school year. Further information can be found at the Ministry web: https://www.mecd.gob.es/dms/mecd/servicios-al-ciudadano-mecd/estadisticas/educacion/no-universitaria/alumnado/FPI/Nota-14-15.pdf.) Those low-educated workers were the first to lose their job and found it increasingly difficult to get back into employment as the economic crisis affected them the hardest the labor market. At the same time, different political events took place, as the political 15 M movement in Spain spread a wave of pacific protests in the biggest Spanish cities. In this period, Spain experienced a dramatic economic downturn which is persisting as the labor market is relentlessly recovering the pre-Great Recession level. Overall, this has generated a human toll, as Stiglitz (2008) put it, which Spanish population is still paying nowadays.

Additionally, this period was a period of social change and increasing political involvement, with strong political discontent and mass protests. Some examples of this are the civil movements such as Los Indignados (the outraged) along with the Plataforma de Afectados por las Hipotecas (PAH). (This is a civic and social movement which defended at-risk or evicted people and support people who had financial difficulties to pay their mortgage.) Those were born as organized forms of social and economic discontent during the Great Recession. Their support was intense and, although it is hard to come with estimates of such support, a fifth of Spanish population (seven million) participated in some way, and it had an approval of four out of five of the population (Barnett 2011). These expressed the level of mass protest of the Spaniards against the society they were living in. The demand for another type of society, where people could be heard, can be seen, using Bonvin (2012), as an expression of their suppressed capability of voicing or demanding fair opportunities, spaces, and outcomes.

Some Conclusions and Further Thoughts

Capabilities has been applied internationally to elaborate policy recommendations (Bonvin and Farvaque 2004) and even to conceptualize indicators (the Human Development Index). It is clear from the literature that there is a growing interest in operationalizing the Capability Approach but also that at the policy level, the paradigms have a slower path for being changed. This chapter did not aim to be a prescription on how to employ capabilities for large-scale assessment surveys. However, it tried to present its basic features as well as potential contributions for the design as well as analysis of measurement surveys such as PIAAC.

The use of the Spanish case helps to illustrate how the human capital paradigm falls short of assessing the drivers and the outcomes of skills in a much broader extent. The Capability Approach offers a normative framework that puts the people at the center and shifts from economic outputs to human value ones. In the analysis, we have seen the limitations to apply the Capability Approach to a survey that has been done under a different framework due to the lack of information on some core aspects that the CA requires in terms of outcomes. The focus on the processes seeks for further methods to collect data that enable to collect individual plans to lead a valuable life. This implies to change the informational basis of judgment and take people as ends. In research, it is a change from objects to subjects of the study.

The consequences of applying a human-centered approach in the design of PIAAC are not necessarily focused on the type of skills assessed, but rather on the reason for choosing it. An adult skills assessment with a CA framework could provide a new Informational Basis of Judgment which still interrogate what skills are being acquired and also would seek to identify the variables that influenced the individual ability to transform resources into choices (conversion factors), the array of valuable options at hand (the capability space), the autonomy to lead a decision (agency), and the value that the individual gives to the final outcome (functioning). If these key aspects would be incorporated into an adult skills study, its potential will be far richer providing additional and informative tools, switching its practical use from a country comparison on education and labor skills to a tool that present and underline the different processes of skills formation. This could be broader educational debates by mobilizing and articulating all public policy spheres.