One of the earliest practical attempts in Germany towards the recognition of informally acquired competences was a sector specific one in the metal and electrical industry of the German state Baden Württemberg. Although the relevance of the formal VET system in Germany has often been highlighted there is a remarkable number of employees who do not have a formal qualification and cannot prove their competences (in Baden-Württemberg 13.65 % of all employees in 2020).

It is a generally shared assumption that many competences - and especially work-relevant competences - are acquired through learning in the process of work (Boreham et al. 2002, Fischer et al. 2004). However, informally, non-formally and formally acquired competences are difficult to distinguish from each other. The same competence, e.g. mastery of a certain machine, may have been acquired informally (e.g. by "copying" from colleagues), non-formally (e.g. in a course) or formally (e.g. in initial vocational training). And competences are also acquired informally in formal settings, e.g. teamwork skills when learning in groups, or foreign language skills in specialised training. Formal/informal/non-formal learning are therefore – in contrast to many definitions (CEDEFOP 2009, OECD 2006, BMBF not discrete categories that can be completely separated from each other, but attributes that have been assigned to learning by the state and society (Colley et al. 2003). It follows from this: If one wants to record informally acquired competences, one cannot exclude anything from the spectrum of relevant competences from the outset.

The task of recording competences of employees in the metal and electrical industry was posed in several projects funded by the state of Baden-Württemberg and supported by the social partners. Against this background, an online tool was to be developed and then made available to any person interested in taking stock of their competences. Under such a premise, it quickly became apparent in an empirical study involving ten companies that employees in the metal and electrical industry have little use for the competence designations discussed in vocational education (Fischer et al. 2014) - at least as a means of self-assessment.

What people can give more information about are the tasks they perform or have performed and mastered in gainful employment. However, one encounters the fact that these tasks are described differently from person to person: What for one person means "maintaining machines and equipment" is for another "repair” and for a third "keeping the machines running". Therefore, task descriptions as a structure for classification and a framework for self-reflection must be presented in a generally understandable form so that people can express themselves in terms of "I can" or "I can't" and so that these statements can then be compared. This is done through so-called task inventories (Frieling et al. 2000), whereby work tasks in a professional field of activity are described and presented in a structured form. In the presentation it will be described how such task inventories were developed and transposed into an online tool, which is now freely available and translated into five languages. Advantages and disadvantages of using such a tool for the recognition of prior learning will be discussed in a final conclusion.

The instrument for making informally acquired competences visible was developed and tested in a participatory technology development process (cf. Fischer 2000, p. 249 et seq.) with the involvement of social partners, personnel managers, works councils, chambers, employment agencies, scientists and those affected. In order to identify work tasks in the metal and electrical industry, an interview study and workplace observations were carried out. The project involved 75 interviews in 10 companies. The analysis of work activities focused mainly on semi-skilled and unskilled workers, but also on skilled workers. Technical supervisors were also interviewed where they could provide information on the nature, extent and systematisation of the work involved. It was important to include in the study people who were actively involved in the work activities, i.e. who either carried them out themselves or were supervisors of those who carried them out. Human resources staff, managers and works councils were also involved, as these are the people involved in personnel decisions. Regardless of whether competences have been acquired through learning in the process of work or in institutional learning environments, it always requires a separate reflection on what kind of skills have emerged from the respective learning process. If it is and should be the subjects themselves (as in our projects) who document and make visible their skills, then a framework must be provided that simultaneously offers a stimulus for reflection and a structure for classification. This framework is provided by a task inventory. However, such an inventory of tasks did not exist for the metal and electrical industry. We had to develop it first. All kinds of information were used for this purpose (training regulations, framework curricula, (company) qualification profiles, job advertisements, German Industrial Standards and the collective wage agreement). Expert surveys were conducted to validate the task inventory. Furthermore, interested workers were able to test the competence tool for the recognition of informally acquired competences in a participatory pre-test phase and thus help to optimise the usability of the tool. These tests were accompanied scientifically and served to further develop, test acceptance and validate the task inventory.

The developed tool AiKomPass (www.aikompass.de) is available online in five languages (German, English, French, Italian and Swedish) and can be used free of charge. With AiKomPass, users can select from a structured list those tasks that they are able to perform and/or that they are currently still performing. The tasks come from the fields of work preparation, production, maintenance and production and warehouse logistics in the metal and electrical industry. So-called digital competences have been added in the meantime. This specialist task inventory is expanded to include activities that are important in their free time, as well as the option to store a CV including references, certificates, etc. The result is an individual overall profile that can be used for personal and professional development and in the validation of informally acquired competences. However, the validation of self-assessed competences requires further analysis and interpretation by relevant experts. The test phase and subsequent pilots have shown that interested people (even without a formal vocational qualification) can use AiKomPass and create an individual competence profile for themselves. However, the problem with this type of competence diagnostics qua self-assessment is that the possible scope of mastered work tasks alone says little about the quality of task processing. But at least information is provided on the scope of an individual competence profile, and this scope can be compared with the scope required in a training occupational profile, whereas all known procedures of vocational competence diagnostics in Germany attempt to derive statements for the overall vocational qualification from a more or less small section of competences tested in greater depth (cf. Fischer 2018). For future research and development, the question therefore arises as to how self-assessment procedures can interact with "objective" procedures of competence diagnostics.

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