In the course of digitalisation, work and business processes in companies are changing worldwide. The networking structures inside and outside companies, the overall proceeding of a digitalised corporate world, and the concrete work processes of skilled workers are affected at different levels (Bourne, 2021; Hammermann & Stettes, 2015; Mütze-Niewöhner & Nitsch, 2020). These changes caused by digitalisation lead to changing competence requirements for employees (Becker et al., 2017; Hammermann & Stettes, 2015). The precise effects on the qualification requirements of skilled workers are not yet conclusively foreseeable. It can be assumed that the tasks of human labour will shift towards more complex tasks with increasing qualification requirements, as these cannot be automated shortly (Bonin et al., 2015). Dengler and Matthes (2021) state that increasingly more complex tasks (especially in manufacturing occupations) could also have substitutability potential through new technologies. However, the developments will look like, humans and their competencies will continue to be a decisive factor in the working environment. The relevance of these qualification requirements becomes evident in the meta-studies by Demary et al. (2016) or BSP Business School Berlin (2017). They identify a lack of knowledge among employees as one of the relevant digitalisation barriers in small and medium-sized enterprises (SME). Many policy and economics experts assume that skilled workers will play a crucial role in the implementation of Industry 4.0 (Bundesministerium für Bildung und Forschung [BMBF], 2016; Windelband & Spöttl, 2017).

Vocational education and training (VET) and the vocational trainers working in it are an important basis for the competence development of future skilled workers (Zlatkin-Troitschanskaia et al., 2009). In this context, there are extensive challenges for vocational education and training. In-company vocational training, in particular, must respond to changing demands on skilled workers to meet the goal of promoting occupational competence. First of all, the VET-system must react to the increasing complexity in work for all employees, but especially for medium and highly qualified personnel. In addition, supervisory activities with decision-making, coordination, and control functions are increasing in networked production processes (Frenz et al., 2016; Gerholz & Neubauer, 2021). It is expected that current job profiles will change and the importance of basic information technology knowledge and understanding will increase (Institut der deutschen Wirtschaft [IW], 2016).  

Currently, only a few studies deal with the consequences of the digital transformation for VET training personnel in companies. Exceptions are the qualitative studies by Gerholz and Neubauer (2021) and Gössling and Emmler (2019). Other previous studies mainly focus on the target group of skilled workers (Spöttl et al., 2016).

In this context, a cross-sectional study in Germany, Spain, and UK was carried out to record the digital competencies of employees in general and those involved in in-company vocational training from the perspective of company representatives. An initial analysis showed significant differences between the countries regarding the digital competence of employees overall (Müller et al., in print).

Following this, this article presents results of a country-specific comparison on the digital competence of vocational trainers in Germany, Spain, and UK from the perspective of company representatives. The digital competence of vocational trainers is assessed by company representatives (N = 547). Furthermore, possible influencing factors, such as the assessed degree of digitalisation, the number of employees and the number of trainees in the companies, are examined.

The data were collected as part of the EU project "WorkingAge" and the project "WissProKMU" at the Institute of Industrial Engineering and Ergonomics at RWTH Aachen University in May 2021. The target group of the survey consists of managers at different levels, employees from strategy departments, and vocational training managers. This group of people is assumed to have an overarching knowledge of digitisation processes and digital competencies in different functional areas in the company. The online questionnaire comprises 38 items, most of which have to be answered quantitatively and based on different assessment scales. Regarding the assessments of the requirements of digitalisation and the existing digital competencies, a distinction was made between employees working in primary processes, control processes, and support processes (Gadatsch 2015). For the present data analyses, only the assessments relating to people employed in the primary processes of the company are examined. These are assumed to be mostly people in industrial-technical professions (e.g., employees in production) who, against the backdrop of the situation described at the beginning, are of particular importance in the context of digital transformation in companies. To address the aspect of intrinsic data quality, which is considered critical in the context of online surveys, the raw data were cleaned concerning selected criteria according to Treiblmaier (2011) and Leiner (2019). After adjustment, the number of respondents in the present sample for the following analysis is N = 547. To examine first the factors influencing the assessed digital competence of vocational training personnel a multiple regression analysis is carried out and interpreted. For the more comprehensive analysis of possible significant factors (estimated degree of digitisation; number of employees; Turnover; number of trainees; sector; country) influencing the assessed digital competence, subsequent post-hoc tests are carried out.

The results provide an initial overview of how the digital competence of vocational training staff is assessed and how this might differ between the three European countries. With the study of the factors influencing the assessed digital competence, initial explanations for possible differences or similarities between Germany, Spain, and UK can be identified. These results will be interpreted against the background of current research. Following this, framework conditions will be described that lead to a high or low level of the assessed digital competence of vocational training staff. The findings on the current state of digital competencies of vocational training staff within the framework of a cross-sectional study can contribute to the targeted promotion of digital competencies of vocational training staff.

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