Session Information
99 ERC SES 04 D, Interactive Poster Session
Poster Session
Contribution
Dual apprenticeship integrates classroom and work-based learning (WBL), promoting both theoretical knowledge and practical skills. Proponents, such as Beer and Meethan (2007), highlight its strategic advantage in customising skills training for industry demands and reducing youth unemployment. However, Guile and Okumoto (2007) highlight the importance of preventing employers from designing 'restrictive' skills content. In contrast, a lifelong skills approach favours transferable skills. Lassnigg (2011) calls for a balance between specific and broader educational goals. Capsada-Munsech and Valiente (2020) emphasise the necessity of both technical and ‘soft’ skills for successful employment and social integration.
Central to the dual model is the assumption that WBL in competitive sectors confers an advantage in the labour market, aligning with Human Capital Theory (HCT) as championed by Becker (1962). HCT underscores education's role in developing individuals' skills and competencies to augment their "capital," an intangible asset of social and economic value, motivating individuals to enhance their capital for improved labour market positioning and increased earnings. A rationale for extending dual apprenticeship into earlier education levels emerges based on the perceived value of capital accumulation and the positive relationship between education, skills development, and labour market outcomes. Under this premise, participation in secondary-level dual apprenticeship allows individuals to build capital earlier, acquire practical skills, and gain industry-specific knowledge from a younger age, enhancing future employability and facilitating a more seamless transition into the labour market.
Aggregate evidence suggests initial gains for vocational education and training (VET) graduates in terms of employability and earnings (Chankseliani and Anuar, 2019), but these advantages fade once university graduates enter the workforce (Brunello and Rocco, 2017). Low-level analyses reveal tracking mechanisms, formal or cultural, which amplify impacts of background factors such as gender and prior academic performance, exacerbating educational inequalities (Simon and Clarke, 2016; Smith, 2010).
When the model moves to lower schooling levels, increased demand for WBL placements may give already privileged individuals an advantage, especially when employers hold the right to select apprentices since they may not be held to the same equality, diversity, inclusion, and accessibility standards as education bodies (Smith et. al., 2021).
My study focuses on Foundation Apprenticeships (FA) in Scotland. I assess who benefits most or least from apprenticeship, taking contextual factors into account. This inquiry tests HCT assumptions about capital accumulation and socioeconomic outcomes. Research questions (RQ1-RQ3) explore post-FA outcomes, socioeconomic variations, and sectoral differences, and compare with other (post)secondary options, addressing the impact of dual training on younger apprentices.
Several factors make the case of FA noteworthy. First, FA coexists with more vocationally oriented Modern Apprenticeships (MA), providing youth with a choice between more academic or workplace-oriented apprenticeship options. FA participants remain in school as students, while MA participants are classified as workers. Second, FA facilitates pathways into higher education, as its qualifications are recognised by Scottish universities. However, differences in the acceptance of sector-specific FA qualifications vary by educational institution.
My study raises questions aimed at assessing the effectiveness of dual apprenticeship in building capital and tests HCT assumptions associating capital accumulation with socioeconomic outcomes by controlling for individual characteristics. I ask:
How do post-FA employment and education outcomes vary across socioeconomic groups?
Are there sectoral differences?
How do these outcomes compare to those related to other education options?
RQ1 explores variations in post-FA employment rates, income levels, and destinations across gender, region, and socioeconomic status. RQ2 addresses potential sectoral differences, acknowledging that different industries may exhibit varying outcomes related to FA participation. RQ3 directly compares the outcomes of FA with those of other (post)secondary options, e.g., apprenticeships at International Standard Classification of Education (ISCED) levels four and five.
Method
Utilising statistical methods, I examine patterns of participation in FA across socioeconomic groups, analysing potential biases towards candidates from higher social class backgrounds amongst sectors. Investigating outcomes for individuals who have participated in FA versus other education options/levels can contribute to an assessment of whether there is a discernible advantage in employment, wages, and career advancement for individuals from certain social backgrounds. Exploring the intersection effects of social class with other demographic factors such as gender, socioeconomic status (using the Scottish Index of Multiple Deprivation/SIMD), or geography may identify compounded effects contributing to unequal opportunities. Finally, comparing FA/MA outcomes and selection processes with other educational pathways, such as higher education (HE), provides a broader context for understanding disparities. I investigate short to mid-term (<10 years) FA outcomes across sectors with existing secondary quantitative survey data. The Scottish Household Survey contains indicators relevant to my study across the full period of FA provision (2008-2022). This data is freely accessible through the UKDataService and is suitable for academic use. After cleaning and processing the data for analysis (addressing outliers and missing observations, identifying variable types, etc.), I define the dependent variables as employment status, wage, and highest qualification level/type achieved, and the independent variables as gender, SIMD, sector, and region (Scottish local authority/LA). Initially, I will calculate descriptive statistics (means, medians, and standard deviations) for the outcomes of interest in each sector and LA, and explore variations in outcomes across IV categories. Data visualisation will also aid my analysis. Bar charts, box plots, or heat maps can be used to illustrate differences in outcomes across sectors and regions. Drawing on emerging patterns, I will perform statistical tests (e.g., t-test/ANOVA) to assess the significance of differences between groups. Using the exploratory analysis as a guide, my analysis centres around the relationship between apprenticeship participation (at European Qualifications Framework/EQF level 4) and socioeconomic outcomes. To address RQ1-3, I use multiple linear regression models to quantify differences in wages and occupational attainment across economic sectors by educational level, paying particular attention to differences by social background. This correlative exercise is performed to create a quantitative foundation outlining post-FA trajectories. An important element of my analysis will be to explore interaction effects between gender, sector, and region using interactive terms in the various regression specifications. This exploration of contextual factors will be crucial to inform subsequent qualitative inquiry.
Expected Outcomes
HCT presumes that obtaining qualifications earlier will improve economic outcomes. The literature demonstrates that VET graduates typically secure employment faster and have higher initial earnings than their non-VET counterparts (Chankseliani and Anuar, 2019). This prediction leads to H1. Hypothesis 1: Positive association between education level and employment status, wage with higher returns for workers in the labour <10 years with FA qualification. Differences in outcomes have been associated with gender (Simon and Clarke, 2016; Bridges et. al., 2022) and socioeconomic status (Klatt, Clarke and Dulfer, 2017). H2 considers variations by gender, LA, and SIMD. Hypothesis 2: Differences in outcomes are associated with gender and socioeconomic status. Strathdee and Cooper (2017) emphasise the highly contextual nature of gender and the intersectionality of ethnicity, socio-economic status, and gender in affecting participation and achievement in VET. H3 highlights interaction effects amongst gender, LA, and SIMD. Hypothesis 3: There are significant interactions between employment, wage and sector, gender, LA, SIMD. Several studies investigate how initial labour market advantages of apprenticeship may diminish or even reverse over time (e.g., Brunello and Rocco, 2017; Neyt, Verhaest and Baert, 2020). While WBL increases employability in the short term (Hanushek, et. al., 2017), occupation-specific skills may become obsolete (Weber, 2014), are sensitive to labour demand changes (Golsteyn and Stenberg, 2017) and may become increasingly exposed as automation and digitisation lead to rapid technological change (Neyt, Verhaest and Baert, 2020). This prediction leads to H4. Hypothesis 4: Earnings for households with SVQ qualifications will be lower than those for households/individuals with (academic) SCQF qualifications, exhibit a positive association with higher educational attainment, and vary across high/low-growth sectors. My work contributes to debates surrounding the utility of HCT in assessing dual apprenticeship, concerns around sectoral skills patterns, and gaps in gender and socioeconomic patterning of VET outcomes.
References
Becker, 1962. Investment in human capital: A theoretical analysis. Journal of Political Economy, 70(5). Beer and Meethan, 2007. Marine and maritime sector skills shortages in the South West of England: Developing regional training provision. Journal of Vocational Education and Training, 59(4). Brunello and Rocco, 2017. The labor market effects of academic and vocational education over the life cycle: Evidence based on a British cohort. Journal of Human Capital, 11(1). Bridges, Bamberry, Wulff and Krivokapic‐Skoko, 2022. “A trade of one's own”: The role of social and cultural capital in the success of women in male‐dominated occupations. Gender, Work & Organization, 29(2). Capsada-Munsech and Valiente, 2020. Sub-National Variation of Skill Formation Regimes: A Comparative Analysis of Skill Mismatch Across 18 European Regions. European Education, 52(2). Chankseliani and Anuar, 2019. Cross-country comparison of engagement in apprenticeships: A conceptual analysis of incentives for individuals and firms. International Journal for Research in Vocational Education and Training, 6(3). Golsteyn and Stenberg, 2017. Earnings over the life course: General versus vocational education. Journal of Human Capital, 11(2). Guile and Okumoto, 2007. ‘We are trying to reproduce a crafts apprenticeship’: from Government Blueprint to workplace‐generated apprenticeship in the knowledge economy. Journal of Vocational Education and Training, 59(4). Hanushek, Schwerdt, Woessmann and Zhang, 2017. General education, vocational education, and labor-market outcomes over the lifecycle. Journal of Human Resources, 52(1). Klatt, Clarke and Dulfer, 2017. Working their way to school completion: a snapshot of School-based Apprenticeships and Traineeships for young Australians. Journal of Vocational Education & Training, 69(4). Lassnigg, 2011. The ‘duality’ of VET in Austria: institutional competition between school and apprenticeship. Journal of Vocational Education & Training, 63(3). Neyt, Verhaest and Baert, 2020. The impact of dual apprenticeship programmes on early labour market outcomes: A dynamic approach. Economics of Education Review, 78. Simon and Clarke, 2016. Apprenticeships should work for women too!. Education+ training. Smith, 2010. Teaching assistant apprentices? English TAs' perspectives on apprenticeships in schools. Journal of Vocational Education and Training, 62(3). Smith, Taylor-Smith, Fabian, Zarb, Paterson, Barr and Berg, 2021. A multi-institutional exploration of the social mobility potential of degree apprenticeships. Journal of Education and Work, 34(4). Strathdee and Cooper, 2017. Ethnicity, vocational education and training and the competition for advancement through education in New Zealand. Journal of Vocational Education & Training, 69(3). Weber, 2014. Human capital depreciation and education level. International Journal of Manpower, 35(5).
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