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  • 1
    Language: English
    Pages: 1 Online-Ressource (circa 157 Seiten) , Illustrationen
    Series Statement: OECD social, employment and migration working papers no. 244
    Keywords: Berufsbildung ; Absolventen ; Arbeitsmarktforschung ; OECD-Staaten ; Employment ; Social Issues/Migration/Health ; Amtsdruckschrift ; Graue Literatur
    Abstract: This working paper looks at the labour market outcomes of individuals who hold a medium-level VET qualification (defined as upper or post-secondary non-tertiary education with vocational orientation) today, as well as how they have changed in the past 10 to 15 years and what can be expected in the medium-term. It looks at indicators of job quality and quantity, and zooms in on the types of occupations that employ VET graduates. The outcomes of VET graduates younger than 35 years old are compared to those of general education graduates (at the same education level), tertiary education graduates and graduates without an upper secondary education degree. Finally, based on these findings, the report discusses key policy directions to improve VET graduates’ access to high-quality jobs.
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  • 2
    Language: English
    Pages: 1 Online-Ressource (68 p.) , 21 x 28cm.
    Series Statement: OECD Social, Employment and Migration Working Papers no.266
    Keywords: Education ; Social Issues/Migration/Health ; Employment ; Science and Technology
    Abstract: Technological developments are one of the major forces behind the need for retraining, but they can also be part of the solution. In particular, Artificial Intelligence (AI) has the potential to increase training participation, including among currently underrepresented groups, by lowering some of the barriers to training that people experience and by increasing motivation to train. Moreover, certain AI solutions for training may improve the alignment of training to labour market needs, and reduce bias and discrimination in the workplace. In order to realise the benefits of AI for training and ensure that it yields benefits for all, it will be necessary to address potential drawbacks in terms of changing skills requirements, inequalities in access to data, technology and infrastructure and important ethical issues. Finally, even when these drawbacks can be addressed, the introduction and expansion of AI tools for training is constrained by the supply of AI skills in the workforce and the availability of scientific evidence regarding the benefits of AI tools for training and whether they are cost-effective.
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