Conference Agenda

Increasing digitalisation throughout the world is significantly impacting work processes and activities as well as competence requirements for employees. In the context of nursing care, the introduction of ICT-supported documentation and communication systems and mobile end-devices is of particular importance (Daum, 2017). The transmission and documentation of patient care information (PCI) in healthcare institutions, which are essential to ensure continuity and quality of patient care (Daum, 2017; Güttler et al., 2010), are profoundly affected by the introduction of digital devices and digitalisation (e.g., Rouleau et al., 2017). This raises the question of what digital competences nurses need to successfully cope with PCI transmission.

Internationally, various catalogues of digital competences exist (e.g., Becka et al., 2020; Kuhn et al., 2019). Some of these catalogues address a generic population and not specifically nurses and other healthcare professions (Vuorikari et al., 2022). Furthermore, to date, the international catalogues of digital competencies for nurses and healthcare professions have not been formally integrated into Swiss national educational programmes (e.g., Brunner et al., 2018). Switzerland lacks a consensus on basic digital competences in the field of digital health (e.g., Kuhn et al., 2019). This study applied a work analysis approach to identify typical exemplary professional situations of PCI transmission with digital devices in Swiss hospitals and the competencies required to cope successfully with these situations (Volpe et al., in preparation). It is based on the so-called ‘course-of-action’ approach to work analysis (Durand & Poizat, 2015; Theureau, 2006). This is a theoretical tradition of work analysis inspired by Francophone ergonomics (Filliettaz et al., 2015), a key assumption of which is that the design of learning environments and programmes should be based on a detailed understanding of workplace practices and requirements (e.g., Daniellou, 2005; Durand & Poizat, 2015; Guerin et al., 2007). To analyse real work practices and identify typical situations of PCI transmission, the researchers applied a video ethnography approach, which was performed with on-site observations and video recordings of the professional activities of 24 nurses in six hospitals. Subsequently, the nurses were invited to participate in individual self-confrontation interviews. During these interviews, the nurses were shown video footage of their professional practices and asked to identify the meaningful aspects of their lived experiences using a semiotic approach. Each video clip consisted of a selection (made by the research group) of observed situations relevant to the PCI transmission theme.

The researchers identified six key moments in the transmission and documentation of PCI with digital devices, represented by selected and validated situations and a set of digital competences that the nurses applied or would have been required to successfully deal with these situations.

The results of this study are of high practical relevance, as they can guide the development of nursing competency frameworks and the conception of training content that closely mimics real work situations. They contribute to the existing literature by concretizing the existing international catalogues of digital competences.

The importance of involved stakeholders and the resulting social networks in international VET cooperation is highlighted in a large number of empirical studies (see e.g., Gessler, 2019). While social network analysis has a broader range of empirical use cases in a wide variety of educational settings (see e.g., Hodge et al., 2020; Jan & Vlachopoulos, 2018), the state of research related to VET (see e.g., Ditchman et al., 2018) is found to a much lesser extent, as is the coverage of social capital within international VET research (see Gessler & Siemer, 2020; Siemer & Gessler, 2021). This paper focuses on the development of social capital in the course of network building and its sustainability in an international consortium using the case study of the funded Erasmus+ project AI Pioneers. The following research questions will be pursued in the context of the submission:

1) Which actors play a central role at the beginning of network building in the field of vocational education and training?

2) What is the intensity of the relationships over the course of the network formation?

This paper will draw on various theoretical approaches in network research to build the theoretical and conceptual framework of the study. As the funded project is an innovation project, the promoter model is used to apply the "content-related dimension of support" (Gessler & Siemer, 2020, p. 46) within the egocentric networks to be analysed with the roles of power promoter, expertise promoter, process promoter and relationship promoter (Witte, 1999). The basic idea of the promoter model is the assumption that promoters are able to overcome barriers in the innovation process due to suitable resources, which has a promising effect on the implementation of projects (e.g., Gessler, 2019; Witte, 1999). Furthermore, the differentiation between bridging and bonding social capital, and thus the intensity of relationships, is crucial (Patulny & Svendsen, 2007). The distinction between strong and weak ties can be traced back to Granovetter (1973). Following on from Granovetter (1973), Marsden and Campbell (1984) empirically addressed the question of which further indicators can be used to capture the strength of social relationships. The authors primarily identified indicators for the closeness of relationships and also refer to the frequency of contact as well as the duration described as the years of acquaintance (Marsden & Campbell, 1984). Following on from this, Gessler and Siemer (2020; see also Siemer & Gessler, 2021) introduce a specification in the form of a level model for measuring the closeness of social relationships which is applied in the course of the present work: 1) Pure exchange of information, 2) Mutual exchange but distanced, 3) Goal-oriented coordination, 4) Cooperation, and 5) Trust in each other. The different levels are characterised to varying degrees by the features of relevance, reciprocity, intentionality, interdependence and consistency, so that the intensity increases over the five levels and the attributes of the subordinate levels are to be assigned to the superordinate levels as well.

Since the broad public launching of artificial intelligence (AI)-based large language models in autumn 2022, a debate about potential benefits and risks of AI in education, including vocational education and training (VET) arose (cp. Chiu et al. 2023, Nemorin et al. 2023, Windelband 2023). But, as there is only little experience and almost no evidence referring to this technology in education, most publications discuss potential developments and are based on estimations. A broad consensus is, that AI will have serious influence on teaching, training and learning – but if this influence appears as threat or potential often depends strongly on the beliefs of the authors. Additionally, the various dimensions of complex teaching and learning processes might be tackled very different by AI.

Against this background, a transnational consortium with colleagues from Spain, Portugal, Slovenia and Germany decided to deliver a small piece of evidence about the usefulness of AI in a very concrete setting:

Can AI support drop-out prevention in electronic learning (e-learning) via personalised tutoring?

Drop-out rates in e-learnings are high, cp. for example Khali & Ebner (2014) or Dopler et al. (2023). Among the various potential reasons for drop-out is one, that can be influenced by (human or artificial) tutors: If the learner is lost at a certain point, individual support might guide him or her back on the track.