The pandemic has shown how quickly our world can change. In both our professional and private lives, digital media have helped us a lot to adapt to this new situation. This brought to light how much our lives are already permeated by digitality on a global and local level. Accordingly, research in educational science is shaped by digitalisation. Large-scale studies in particular depend on digital algorithms in order to process large amounts of data. The algorithmisation of research processes makes it possible to standardise large amounts of data and at the same time to locate and highlight particularities in the data. Educational science is and has been for a long time dependent on (digital) algorithms and digitalisation in general. But it is not only the easily handable management and dissemination of research, nor the amount and type of data that is collected that has changed massively. The algorithmisation of our lifeworlds also calls for a rethinking of the concepts of knowledge and education.

The internet in particular has led to major changes from the very beginning. It makes vast amounts of knowledge theoretically available to everyone at all times. Moreover, knowledge is no longer exclusive but increasingly inclusive, as many people not only have access to knowledge resources but they can now participate in the production of knowledge themselves (e.g., Wikipedia). Yet knowledge content is not limited to online encyclopaedias and news websites, but is to a large extent also negotiated in social media. Through these channels, news can achieve a vast outreach. With each “share” the shared news is subject to an interpretation and appears in a new light. In talking about news on social media, these very news change. Knowledge and information thus each have a subjective meaning for the individual. Advanced technologies such as social bots or deepfake technology make it possible for news and knowledge to be manipulated and disseminated on a large scale, making it harder to distinguish between real and fake news.

How knowledge is structured and how we deal with it has implications for what we mean by the concept of education and what we mean by calling a person well-educated. The main change in the understanding of education comes with the end of the digital revolution (Negroponte 1998, Cramer 2015) and the entry into the post-digital age, which places new demands on post-digital education (Schmidt 2020). Following Haraway’s situated knowledge (Haraway 1988) or Latour’s actor-network theory (Latour 2005), it becomes clear that the role of digital algorithms for education is not to structure educational content passively and neutrally for us. On the contrary, algorithms themselves can be understood as actors that significantly influence educational processes (Monnin 2018). In doing so, the algorithms proceed in a strongly generalising way while at the same time forming individual knowledge networks for each person according to their social situation, their research history, and their living environment. Education takes place in a dynamic network of relations between knowledge content and learners. These relations change during the learning process, so that the learning process must be constantly adapted to its fluid learning object.

Based on these considerations, the planned contribution focuses on the following questions:

1. Which understanding of knowledge and education is viable in the post-digital age?
2. To what extent is the trend towards homogenisation as well as individualisation due to or driven by digitality?
3. What is the resulting focus for future research in educational science?

The planned contribution focuses on basic theoretical considerations that are influenced by philosophy and educational theory. The underlying conceptual work is based on a thorough literature review on the topics of changes in the understanding of knowledge and education in relation to digitalisation and algorithmisation. The changed and new forms of knowledge and their influence on education will be thought through in terms of their consequences for future research in educational science. Regarding knowledge, the research focuses on the questions of how and whether knowledge contents change during their digitalisation. Particular attention is paid to those contributions that address the ontological relation between learner and knowledge or discuss the extent to which the basic human claim to acquire knowledge changes when knowledge is potentially accessible at any time. Based on the findings, new forms of knowledge are discussed in their specific relation to digitality and their significance for educational processes. In a broad sense, the research is based on an understanding of education as an ongoing learning process that concerns the changing relationship between the learner and the world in the sense of the acquisition of “external” content. In a narrower sense, the considerations are led by the question of a kind of topology of knowledge: In the learning process, knowledge is no longer something that changes its place or is passed on from one person to another. Instead, especially against the background of digitalisation, knowledge must be understood as something dynamic that manifests itself differently and is dependent on the way it is referred to. The contribution focuses mainly on those research findings that share this premise. The keywords digitalisation and algorithmisation are not intended to be used to discuss the didactic possibilities of using digital technologies for teaching purposes, but to address the influence of these technologies on our fundamental understanding of education and reconsider our own understanding approach to the world and the other in a post-digital age. For this purpose, approaches that address these underlying dynamics of learning processes are linked to theories of the digital to highlight the specificities of learning in the post-digital age.

1. In their situatedness, knowledge contents are context-sensitive and products of individual relations that are increasingly formed by digital algorithms. The conceptualisation of education in a post-digital age benefits from theories that highlight the productive interconnectedness between the subject and its surroundings. This applies to post-humanism (Taylor/Hughes 2016; Barad 2006), post-phenomenology (Verbeek 2015) and structural anthropology (Rombach 1987) as well as to theories of phenomenological pedagogy that define learning processes as a restructuring of previous horizons of experience (Meyer-Drawe 1982). 2. For better or worse, digital, algorithmic media mostly reinforce patterns that already exist (Muuß-Merholz 2019; s. e.g. Noble 2018 on discriminatory algorithms). Therefore, the technological possibilities are a mirror of basic human needs to connect and feel similar to others as well as to differ from them in their own singularity. Instead of blaming social media, for example, for promoting egocentricity, one must ask where the desire for self-expression comes from (Kneidinger-Müller 2017). Education has always been context-sensitive and dependent on the situatedness of the learners. This dependency is made more visible by digital, algorithmic media. 3. There are many promising attempts to do justice to the particularities of the digitalisation in educational research. These attempts range from general competence models (Huwer et al. 2019; Koehler et al. 2013) to specific differentiations of the required computer and information-related competences (Eickelmann et al. 2019) or 21st century skills (OECD 2018). These conceptualisations are primarily concerned with the sensible use of digital media in educational contexts or, more generally speaking, with an independent orientation in digitalised lifeworlds. What is missing is a fundamental discussion about whether knowledge and education still mean the same thing and to what extent these concepts can be the basis of future research in educational science. This contribution tries to lay the foundation for such a discussion.

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