Formal Lifelong E-Learning for Employability and Job Stability During Turbulent Times in Spain

In recent decades, international organizations have developed initiatives that incorporate lifelong learning as a tool to increase the employability of citizens. In this context, the goal of this research is to test the influence of formal e-learning on estimating employment status. The research made use of a sample of 595 citizens in 2007 and 1,742 citizens in 2011, using microdata from Eurostat's Adult Education Survey (AES) implemented by the Spanish Statistical Office [Instituto Nacional de Estadística] (INE) in Spain. Controlling for socio-demographics and formal education-level information, multiple binary logistic and ordinal regression models on formal education activities are used to check the separate effects of independent variables and demonstrate that Spanish people who have done formal lifelong e-learning activities are more likely to have an employment contract: i) in 2007, before the start of the economic crisis, for all individuals; ii) in 2011, during the economic crisis, for all individuals; iii) in 2011, for individuals with any level of computer literacy; iv) in 2011, for individuals whose highest education level is primary, secondary, or post-secondary non-tertiary; and v) in 2011, for individuals having more stable employment contracts, understood as a combination of duration (temporary, permanent), and working hours (part-time, full-time). Consequently, after inferential judgements based on the empirical results, it is shown that one of the most important factors for estimating employability in times of economic crisis has to do with lifelong e-learning. Moreover, formal e-learning activities can be a strategy for obtaining better job stability.

In recent decades, international organizations have developed initiatives that incorporate lifelong learning as a tool to increase the employability of citizens. In this context, the goal of this research is to test the influence of formal e-learning on estimating employment status. The research made use of a sample of 595 citizens in 2007 and 1,742 citizens in 2011, using microdata from Eurostat's Adult Education Survey (AES) implemented by the Spanish Statistical Office [Instituto Nacional de Estadística] (INE) in Spain. Controlling for socio-demographics and formal education-level information, multiple binary logistic and ordinal regression models on formal education activities are used to check the separate effects of independent variables and demonstrate that Spanish people who have done formal lifelong e-learning activities are more likely to have an employment contract: i) in 2007, before the start of the economic crisis, for all individuals; ii) in 2011, during the economic crisis, for all individuals; iii) in 2011, for individuals with any level of computer literacy; iv) in 2011, for individuals whose highest education level is primary, secondary, or post-secondary non-tertiary; and v) in 2011, for individuals having more stable employment contracts, understood as a combination of duration (temporary, permanent), and working hours (part-time, full-time). Consequently, after inferential judgements based on the empirical results, it is shown that one of the most important factors for estimating employability in times of economic crisis has to do with lifelong e-learning. Moreover, formal e-learning activities can be a strategy for obtaining better job stability.

Introduction
The recent progress in accessing and using information and communication technologies (ICT) has led to numerous social changes. The study of working life and technological developments and their relationships with educational contexts have attracted the interest of researchers (Aceto, Borotis, 262 Devine, & Fischer, 2014). Specifically, this is true in countries such as Spain, traditionally associated with low levels of innovative, technological, and knowledge intensity, and great problems of youth employability (Moreno Mínguez, 2015).
On the one hand, institutions like UNESCO, OECD, and the European Union have been implementing lifelong learning initiatives for decades, such as the Faure Report and the Delors Report, which have been oriented to the development of abilities and professional skills to increase the competitiveness of countries (Manuelli & Seshadri, 2014). These actions have been designed for formal, non-formal, and informal adult education (Kaufmann, 2015). They aim to develop the skills needed by professionals in the 21 st century, and to improve the employment security of citizens and workers (Morgan, Genre, & Wilson, 2001).
On the other hand, in a context of growth constrained by the onset of the economic crisis at the end of the last decade, many young people have not found it easy to choose between studying to develop themselves professionally or gaining work experience directly (Maiolo, Cortini, & Zuffo, 2013).
Specially, this is true because the new approaches to the world of work and education are related to work-related learning (Kyndt & Baert, 2013), and labor legislation has favored temporary contracts for young people which has damaged their professional development and long-term welfare (García-Pérez, Marinescu, & Vall-Castelló, 2016).
Considering all this, the study of the relationship between education and manpower is relevant for great social issues. It was demonstrated through research related to the concept of employability, which suggests several relationships with dimensions related to emotions, commitment, and selfesteem (Fugate & Kinicki, 2008). Moreover, various strong relationships exist between training, employment security, and subjective measures in people with low education levels (Bassanini, 2006).
Moreover, trends towards flexicurity as a way of job security have been placed on the table (Muffels & Luijkx, 2008). All of this occurs in a context of relationships between dispositional employability and e-learning (Torrent-Sellens, Ficapal-Cusí, & Boada-Grau, 2016).
In this sense, there is a need to research the factors that influence the employability of citizens throughout different periods and economic cycles, and their links with new possibilities of e-learning in the context of lifelong learning. This is due the necessary stimulation that less educated people need to be enrolled in training (Sanders, Oomens, Blonk, & Hazelzet, 2011), the impact that vocational training has on the productivity of countries (Sala & Silva, 2013), and the great importance of elearning for vocational education and training (Inayat, Amin, Inayat, & Salim, 2013). This study focuses on this gap by exploring human capital factors, such as education, that affect the employability of citizens before and during periods of economic crisis. It takes into account two kind of types of factors: socio-demographic variables, and formal e-learning as a tool for being employable in the 21 st century.

Theoretical Context and Hypotheses
only through education, but also in terms of transversal and personal skills beyond those typically associated with specific and technical skills (Andrews & Higson, 2008).
Moreover, there is a context where the existence of a skill-biased technical change (SBTC) explains the increase in the level of employment of the most educated workers and better skills (Sanders, 2013), a wage growth and purchasing power of workers in the knowledge society (Peracchi, 2006), and the existence of skill mismatching (Desjardins & Rubenson, 2011). Furthermore, the relationship between level of education and work are not always direct, both from a standpoint of overqualification existing in society (Leuven & Oosterbeek, 2011) and investment in education (Davidson & Sly, 2014). As expected, new technologies and their associated processes are changing current and future jobs (Frey & Osborne, 2017;Hodgson, 2016).
The research also fits into existing trends and projections about the future of education. Thus, areas such as lifelong learning -hinted early last century by John Dewey, Alfred E. Smith, and Basil Yeaxlee (Jarvis, 2004)-, applications and uses of ICT in educational contexts, and the globalization of training (Stoyanov, Hoogveld, & Kirschner, 2010), are essential elements for the development of human capital through different educational processes.
In addition, scenarios in which the acquisition of different skills and abilities (professional, learning, social, personal) through new pedagogies (focused and student-centered, interactive, social, at in any time and place), are also theoretical elements taken into account in the future of the world of education and learning (Redecker et al., 2011). And all this within constraints, challenges, and considerations of learning through distance methodologies developed on the Internet (e-learning), such as the globalization of knowledge, the development of open educational resources, and seamless learning (Wong, 2012).
Taking into account all this, it is important to note that the Global Financial Crisis has changed labor conditions and human resource development policies related to training. Companies do not offer training as before but they are using low cost-based online learning (Keeble-Ramsay & Armitage, 2015), which needs new successful and pedagogical approaches in order that mid-career workers contribute to economic revitalization (Booker & Tucker, 2014). Moreover, e-learning is considered a good tool for the efficiency of higher education in countries affected by the crisis (Rennie, Jóhannesdóttir, & Kristinsdottir, 2011).
In the same way, the economic downturn has changed adult education's purposes and knowledge that can be classified as useful for life (Brown, 2010). Lifelong learning has to be understood as a way for reflexive activation in transition between work and education, helping to gain respect, dignity, and self-esteem (Tuama, 2016). For instance, Spanish youth face many problems in school-to-work transitions because there is an educational exclusion for people without compulsory secondary 264 education, many difficulties in returning to formal learning, and a lack of public policies for them (Salvà-Mut, Thomás-Vanrell, & Quintana-Murci, 2016).
Noting a trend where universities are widening social inequalities related to neoliberalism (Holmwood, 2014), it becomes relevant to analyse the outcomes of employability gained through online education. Especially since this learning mode is not being analysed from both the standpoint of adults in higher education (Broek & Hake, 2012) and in organisations (Frerichs, Lindley, Aleksandrowicz, Baldauf, & Galloway, 2012). Moreover, this is happening within an economic and social context that changes how career development is managed (Barabasch, Merrill, & Zanazzi, 2015), and where students have the possibility to choose between face-to-face or e-learning systems, according to several successful factors and research approaches that do not include employability outcomes (Broadbent & Poon, 2015;Lin & Wang, 2012;Mohammadi, 2015).
So, it is necessary to investigate the value of formal lifelong e-learning activities for employability and job stability in times of economic crisis, i.e., whether e-learning influences the employment status of citizens, both in times of economic crisis and not in crisis. For this, five hypotheses were developed. These will be tested by using multivariate regression analysis with official data from Spain: The stratification criteria used were the size of the municipality to which the section belonged, as well as the main socio-demographic characteristics thereof. The strata considered municipalities with respect to their number of inhabitants. For each Autonomous Community and Autonomous City -a first-level geographical, political and administrative division in Spain, according to the nomenclature of territorial units for statistics (NUTS 2), which is a hierarchical system for dividing up the economic territory of the European Union-an independent sample was designed to represent it. Therefore, the samples were distributed among Autonomous Communities and Cities, assigned one uniform part and another part proportional to the size of them, obtaining the distribution shown in Table 1 Table 1 shows the corresponding ratios of samples in the research dataset and AES microdata in 2007 and 2011. As can be seen, the differences between the sample distributions were ±5.1% in 2007 and ±1.7% in 2011. The population density of regions was taken into account to show that the samples had geographical representation of rural and urban areas, one of the most important issues related to employment. This ensured that the samples obtained from the microdata were representative of the Spanish population as a whole.

Formal Lifelong E-Learning for Employability and Job Stability During Turbulent Times in Spain
Martínez-Cerdá and Torrent-Sellens 266

Socio-demographics and individual-level information.
Participants were asked to report their gender, age, highest level of education successfully completed, and professional or labour status, which was grouped by employed or profession (temporary/permanent, and part-time/fulltime) or not (unemployed, student, retired, disabled for work, domestic tasks, caring for people, and other situations). These variables were combined to design several levels of their job stability. The rule for setting them was the greater the duration and the more working hours, the more stable the employment. Table 2 shows these levels according to not having an employment contract, and temporary/permanent and part-time/full-time characteristics of employment contracts.

Digital literacy.
Participants were asked to report about their level of expertise in using computers, with several possibilities related to tasks that can be performed by using computers (copying or moving a file or folder, writing a text using a word processor, using formulas in spreadsheets, installing devices and/or programmes, using databases, programming, etc.).

Data Analysis
Recoding. A dichotomous variable related to being employed was used as a dependent variable. Ordinal and dichotomous variables were created according to  Analyses of reverse causality were used in multivariate analysis of stability of employment contracts in 2011 as well. Specifically, ordinal and binary logistic regression models with exchanges between dependent and independent variables were tested looking for H&L. The results (Table 7 and Table 8) show that reverse causalities were rejected.

Means, Standard Deviations and Correlations Between the Observed Variables in Formal Lifelong
Learning Activities AES 2007 (N=595) and2011 (N=1,742) in Spain

Multivariate Analysis in 2011 of People With Non-Tertiary Education Levels
In order to analyse people without tertiary education, who are more likely to suffer in periods of economic crisis, a focused analysis was developed by filtering the education level of people. Table 6 shows two parallel multiple binary logistic regressions related to formal lifelong e-learning activities in 2011 and with three split-samples: primary and secondary, post-secondary non-tertiary, and tertiary education levels. The adjustment obtained for the proposed models had valid values: χ 2 with p=0.000, Finally, three aspects have to be highlighted: i) when a low level of education exists (primary and secondary), this predictor was the one with the greatest relative importance; iii) to be digitally literate was only relevant for having an employment contract in people with tertiary education; and iii) in post-secondary non-tertiary education, the relative importance of this predictor was surpassed only by being aged 35-54 years old. The results confirmed hypothesis H4.

Multivariate Analysis: Stability of Employment Contracts in 2011
In order to analyse the stability of employment contracts during an economic crisis, several analyses were developed following the classification in Table 2. The main results are shown below, which can be supplemented in Table 7 and Table 8. Specifically, Table 7 shows the main results of three ordinal regressions related to formal lifelong e-learning activities in 2011.
First, the ordinal regression model for stability by duration showed a good adjustment: Χ 2 with p=0.000, p-Pearson=0.128, and p-Deviance=0.400 higher than 0.05 (Agresti, 2010), p-Parallel Lines=0.183 higher than 0.05 (Tarling, 2009)  Finally, we used this process in stability by duration and working hours. We created three models according to   (Behrman, 2010).
In a context of job insecurity and precarious employment in Mediterranean countries (Kretsos & Livanos, 2016), Spain has more temporary contracts than other countries (Kahn, 2016)

Strengths and Limitations
This  (Blanco & Rodríguez-Martínez, 2015). It is important to understand that the links between lifelong learning and online education are fundamental in the current context with inclusive and humanistic initiatives developed by the United Nations (Majhanovich & Brook Napier, 2014) or via MOOCs (Steffens, 2015).
The research argues for the benefits of e-learning for less educated workers, and reaffirms approaches against its lower prestige in the labor market (Barberà Gregori, 2015;Rojas-Rojas, 2014). In this sense, it adds results aligned to its importance to employment factors, such as increasing the salary of the young (Castaño-Muñoz, Carnoy, & Duart, 2015) or integrating groups at risk of social exclusion (Storm, Uiters, Busch, den Broeder, & Schuit, 2015).
Although the study presents data and evidence on the effectiveness of the direct application of elearning to post-secondary education and university contexts (Bell & Federman, 2013), and adult education (Taha, Czaja, & Sharit, 2016), the study has some limitations. The results should be viewed as a first exploration of education and e-learning factors that affect employability. The findings help to establish a relationship between formal lifelong e-learning and having an employment contract by using the theory of human capital, which has several objections related to its exclusively economic, isolated, and utilitarian orientation of education (Gilead, 2012). On the other hand, the current changing nature of work, jobs, and psychosocial contracts should be considered as well (Alcover, Rico, Turnley, & Bolino, 2016).
Further studies are needed, because it is necessary to consider other situations, such as non-formal education activities and e-learning in work contexts (Tynjälä & Häkkinen, 2005), which may add more explanations to education predictors related to employment. Additionally, more complementary variables (level, number, fields, etc.) and countries would help to increase the understanding of linkages between formal lifelong education and having an employment contract. In this sense, these ideas are suggested for future research, where current findings could be compared to situations found in other European countries.

Conclusion
Research on the need for lifelong learning has been promoted and gradually developed over the past decades, where labor market and businesses have been demanding new skills and abilities in workers.
In recent years, the economic crisis has impacted the employability of people. Adding empirical findings to theory of human capital, the study presented here analyses the influence of formal lifelong online education activities on having an employment contract by using Spanish microdata from official European surveys before and during economic crisis. Accordingly, and controlling for sociodemographics and formal lifelong education-level characteristics, the findings suggest that formal lifelong e-learning is an important predictor of having employment. During the crisis years, it particularly helps Spanish citizens who do not have tertiary education. Moreover, it is a good strategy for having more stable employment contracts. In this sense, these results have to be taken into account by public policies aiming to improve human capital. In this sense, future training plans that customize the type of educational methodology are needed.