The use of generative AI is accelerating the digital transformation of the world of employment and helping to bring about a shift in work contents and occupational tasks. Specific (new) specialist and cross-cutting competency requirements are arising within this context. The articles in this issue of BWP examine the nature of these requirements and look at which kinds of initial and continuing VET provision are in demand. They also explore how education and training processes are being changed by the use of AI applications and which innovative impetuses are observable.
This article investigates whether the conversation analysis technique recently adopted in labour market research can be transferred to education and training-related tasks. The general principle is guided by the self-determined role of learners. An exploratory empirical pilot study involving students at a business school is analysing the areas of potential for augmentation and automation offered by AI in the solving of complex tasks. The results show that this methodology is can also be used in an education and training context and that it can deliver valuable findings for AI-aided learning processes.
Artificial intelligence (AI) has now also become established in the world of work. As was the case with earlier technological innovations, questions are once again arising with regard to the replacement (substitution) and supplementation (augmentation) of human work. This article investigates the consequences of the use of AI for work outcomes from an employee perspective. For this purpose, current survey data from the Digital Transformation and the Changing World of Work project (DiWaBe 2.0) is evaluated and differentiated at the level of the main occupational groups of the 2010 Classification of occupations (KldB 2010). The results reveal varying degrees of exposure of occupations and a relevant correlation of substitution and augmentation effects.
Artificial intelligence (AI) is changing both what we do at work and how we do it. This article uses the 2024 BIBB/BAuA Labour Force Survey to show the current prevalence of AI on the labour market. AI is mainly being used in cognitive-analytical and non-routine tasks and is associated with future skills requirements such as problem solving, closing gaps in knowledge, being creative or presenting convincing arguments. Both specialist requirements and cross-cutting competencies are thus forming a closer focus within the context of AI. For this reason, employability skills need to continue to be fostered in a targeted manner.
How can the model of “human-centred AI” turn into operational practice? The WIRKsam Competence Centre is researching how human-centred design and use of artificial intelligence can be achieved. This article presents two case studies from fibre composite manufacturing and from the textile industry which exhibit areas of potential for efficiencies and quality gains. Requirements with regard to competency retention and development are highlighted at the same time.
This article presents the development and piloting of an additional qualification in AI and machine-based learning. Its aim is to illustrate how relevant qualifications can be firmly established in vocational education and training. The results of the piloting provide indications relating to the evaluation of the additional qualification and to transfer of learning from the perspective of the trainees, teaching staff and companies.
Marie Wagner; Martyna Biedrzycka- Schmidberger; Anne Ortner
This article analyses the planned use of artificial intelligence (AI) in inter-company training. Project outlines from the INex-ÜBA funding initiative form the basis for the analysis. The ideas relating to the deployment of AI described in these outlines make clear the manifold potential which VET centres see in it for the further development of their training provision. The results of the analysis show that AI should be deployed within the context of education and training technologies and also should be imparted to the trainees as learning content.
The use of artificial intelligence (AI) across almost all occupational areas is also changing the contents and processes of vocational education and training. This development had already been addressed in the first round of funding of the InnoVET innovation competition and is assuming more distinct shapes in the second round, which was launched in 2024. The article presents examples of how AI is being addressed by the projects.
Continuing training is key to keeping pace with the changes to the world of work being brought about by technological change and by the increasing prevalence of artificial intelligence (AI). This article investigates the contents of the continuing training pursued by employees using AI and also examines whether these contents differ depending on their job requirements level.
Recommendation systems can help learners and companies with the selection of continuing training provision by issuing personalised suggestions. However, complex correlations need to be considered during the design concept and development of such systems, and the present article seeks to raise awareness of these. This applies both with regard to the application of such recommendation systems and in respect of their effectiveness.
INVITE is embedded within the National Continuing Training Strategy and pursues the goal of advancing the digitalisation of continuing vocational education and training. The focus is on the development and piloting of technology-based innovations in order to deliver greater transparency on the continuing training market. This article provides an overview of the innovations developed and states some examples of findings obtained with regard to the deployment of “recommender systems” for matching continuing training provision and in respect of the design of personalised sequences of learning units (adaptive learning pathways) in continuing VET.
Artificial intelligence (AI) is bringing about a fundamental change to teaching, learning and administration in VET. The question is no longer whether AI is used in the first place. The issue now is how its use can be structured. The new EU AI Regulation contains important indications in this regard.
From research and practice
Alexander Christ; Caroline Neuber-Pohl; Sabrina Inez Weller
Prestigious occupations have a high standing on the training market. Training places in occupations accorded a high degree of social esteem are significantly less likely to have vacancies. Analyses conducted on the basis of the full BIBB survey of newly concluded training contracts as of 30 September 2024 and using the “Occupationally-Related Prestige Scale” (BAS) show a significant correlation. There are, however, exceptions from which we can perhaps learn.
The modernisation of training occupations requires an elaborate procedure which is coordinated between the stakeholders and which also needs to take account of both specialist occupational contents and the formal demands of a legal ordinance. Experts from practice discuss content requirements and work with the social partners to draw up training contents and examination requirements. BIBB provides technical support for the whole of the process. A BIBB project has investigated the extent to which artificial intelligence (AI) can be integrated into the procedures and examined the opportunities and challenges which emerge in respect of support for individual stages of the work. This article presents results on the basis of process steps selected as examples.
Training to become an electronics technician is a future-proof option. Nowadays, everything which functions in a technological, electronic and automatic way contains a contribution from the skilled electrical trades. Electronics technicians are professionals in electrical appliances, in energy and building technology and in automation solutions. Trainees in this occupation can choose between two specialisms. This occupational profile describes the key tasks and presents current training figures.
The summer Board Meeting was chaired by INA MAUSOLF, representative of the federal states. Consultations centred on the opportunities and risks of artificial intelligence within the context of the further development of initial and advanced training regulations. The European Commission’s “Union of Skills” and the current coalition agreement were also discussed.