Conference Agenda

The release of the language-based AI application ChatGPT in November 2022 attracted international attention and led to a nuanced scientific debate on the opportunities, challenges and implications of generative AI for research, practice and policy (Dwivedi et al. 2023). The 'big language models' were also found to have both benefits and risks for the dimensions of teaching and learning when used in differentiated educational contexts (Kasneci et. al. 2023). In the context of higher education, the changes brought about by technological developments have led to considerable uncertainty from the perspective of both teachers and students (Gimpel et. al. 2023). In addition to (examination) legal issues (Fleck 2023), the objectivity, reliability and validity of the information generated by AI is also viewed critically (Rademacher 2023). Like the general debate on the possible uses of AI technologies, the debate on AI at universities is also largely characterised by weighing up the opportunities and risks of such technologies in areas of application such as governance, administration, research and teaching. These issues relate to the support of decision-making processes as well as the promotion of innovation and the personalisation of learning processes (Wannemacher/Bodmann 2021).

Particularly in social science programmes, the question arises as to what importance will be attached to reflexive, ethical, social and pedagogical dimensions in AI-supported teaching in the future (Zawacki-Rinter et al., 2020, p. 513). Despite all these uncertainties, there is no question that the use of AI-based applications in digitised education at universities will intensify. AI technologies are now reaching a certain level of diffusion in research, study and teaching at universities (Wannemacher/Bodmann 2021). Particularly in the field of higher education, a far-reaching automation of didactic interaction patterns can be expected in the near future, with classic teaching formats being successively expanded or supplemented by the use of chatbots in the context of sophisticated learning scenarios (Schmohl/Löffl/Falkemeier, 2019).

In view of the growing number of students worldwide, concepts are also gaining in importance that use AI applications to provide as many students as possible with fast, individualised advice without having to accept a significant loss in quality compared to advice provided by humans. According to a study by the Georgia Institute of Technology, chatbots can be used successfully to provide such advice. The study showed that learners in selected online courses were unable to distinguish the chatbot from a "real" teacher (Kukulska-Hulme/Bossu/Coughlan et al., 2021, p. 23f).

At the same time, various studies in this field also show that many teachers and students at universities have a certain fundamental scepticism towards highly developed AI technology, which makes it difficult to use (Ferguson/Coughlan/Egelandsdal et al., 2019, p. 12 f.). Only a few studies have been conducted on the pure distance learning sector.

The initial situation for the empirical study in this paper is that "Synthea" has been used at IU International University since December 2023 to answer students' questions in distance learning. These primarily relate to the teaching materials provided so that the AI has a sound basis for answering them. This means that the uncertainty regarding the accuracy of the answers is already reduced. To further increase security, the teachers of the individual modules verify the answers provided by Synthea and can change them if necessary. The system is designed in such a way that the AI understands this as a learning process, further questions on the same subject area are then answered accordingly and no further verification is necessary. This means that students do communicate with an AI, but primarily to generate knowledge rather than for consultation processes.

Organizations can be identified as central actors in transition processes (cf. Truschkat 2013; Truschkat et al. 2019) and therefore play a central role in successfully shaping the passages characterized by uncertainty. On the one hand, transitions are considered to have great potential (cf. Dunlop 2017), as they support individual learning processes and biographically relevant changes (cf. Griebel/Niesel 2017). On the other hand, however, transitions are associated with the fact that they require the individual to make "a variety of adjustments" (cf. Mackowiak 2011, p. 21). Therefore, the individual and temporal uncertainties associated with transitions are often looked at and considerations of how to design transitions in a successful way are developed from this. Organizations play an important role here (cf. Krähnert et al. 2022; Truschkat/Stauber 2011). (cf. Krähnert et.al. 2022). This is because organizations themselves construct, control and accompany these uncertain processes through representatives of organizations (gatekeepers) (Behrens/Rabe-Kleberg 2000) by counselling or evaluation (cf. Truschkat/Stauber 2011).

At the same time the increasing digitalization, not least due to the digitalization of the working world, is also leading to reshaping the organization of transitions (cf. Heisler/Meier 2020). It is not only access to digital technologies and the availability of digital skills that are now a basic requirement for integration into work (cf. D21/Kanter 2023), transitions themselves are also increasingly organized and shaped in digital contexts i.e. by digital job markets, digital career networks or digital application portals. Accordingly, the acquisition and possession of digital skills can be considered central to the safe management of digitalized transitions into work.

By understanding digitalized transitions as a multi-actor and multi-situated process of uncertainty, the focus is on the constitutive conditions and negotiation processes between the individual actors (cf. Wanka et al. 2020). An organizational pedagogical perspective opens up the possibility of looking at organizations as co-actors in negotiation and support, as well as focusing on the organizational nature of digitalized transition processes. In the lecture, this perspective will be presented further on the basis of a future research project.

The digital transformation is not only leading to technological progress in everyday life and society, but is also changing the world of work. Digital technologies are increasingly influencing work processes and organization. This means that (vocational) schools are also confronted with the need to integrate digital technologies into school lessons in order to prepare learners for a digitalized world of work. In this context, schools usually act under uncertainty, as teachers often lack the essential skills, will or tools for pedagogically meaningful and authentic digitally supported teaching (Knezek & Christensen 2016).

The integration of digital technologies into the classroom is associated with changes at the administrative, organizational and cultural level of the school (Blau & Shamir-Inbal 2017; Pettersson 2018). Rather, digitalization in the school context means a fundamental change (Islam & Grönlund 2016). Digital technologies in education can be seen as an innovation, which entails a school innovation process when implemented in the classroom (Rogers 2003). This process takes place in the context of school development, which occurs in various dimensions (Eickelmann & Gerick 2017; Ilomäki & Lakkala 2018), which can be seen as an indication of a successful innovation process. The successful implementation of digital technologies in the classroom therefore requires a holistic innovation process in which, in addition to pedagogical adaptations, extensive changes are required in the school organization, particularly at an organizational and structural level.

The innovation process affects, for example, the design of structural and procedural areas of the school organization. Both hindering and facilitating factors play a decisive role at the school meso level, which can lead to school development succeeding or failing. Barriers to innovation can therefore occur in the change process (Reiß 1997), which can manifest themselves, for example, in a lack of digital skills among teachers or in a lack of IT equipment in schools (Fraillon et al. 2020). Barriers to innovation can change, delay or even prevent the implementation of innovation (Mirow 2010). The promoters in an organization play a decisive role in overcoming innovation barriers (Witte 1973). These are actors in the organization who intensively push the innovation process and want to successfully implement the innovation with personal commitment. The focus is on the promoter's contributions to innovation (e.g. training of colleagues) based on their sources of influence (e.g. expert knowledge). There are four different types of promoter: Expert promoter, power promoter, process promoter and relationship promoter. The success of an innovation process therefore depends on the conditional configuration of hindering innovation barriers and conducive promotional activities. Complex causal structures can be assumed. A successful school development process is influenced by several different conditions, which themselves are interconnected.

The aim of the study is to analyse which constellations of innovation barriers and promotional activities as conditions lead to (un)successful school development when implementing digital technologies in schools. In this way, the causal complexity of the innovation process should be considered. The research question to be addressed is which combinations of conditions in the implementation of digital technologies in schools lead to (not) successful school development?