STudieS: STS in education

Despite its status as an eclectic, multi-disciplinary field of enquiry, research in education has been relatively slow to recognise the rich potential of STS. The field has arguably been dominated by theoretical perspectives from social science that assume a priori sociopolitical structures as organizing forces in the practices of education and knowledge. This has led to an elision of the emergent, the sociomaterial and the more-than-human in research.

However, several strands of educational research have drawn on insights, perspectives and methods from STS leading to fine-grained analyses of the processes and practices of education. These have included analyses of relationships between states and knowledge, the sociomateriality of epistemic and regulatory practices, regimes of discipline and audit, big data and learning analytics, the political economy of educational technology, and the unfolding assemblages of educational institutions, classrooms and online spaces. Especially within a policy environment that increasingly requires educational knowledge of ‘what works’ from the research community, STS theories contribute to educational research from a distinctive angle, by making visible the enormous work that is required to make certain understandings of truths and rationalities stick as scientific beliefs (Sismondo, 2010). The international STudieS-network brings together researchers who are active across a range of STS research in education. As we grapple with increasing inequities, growing standardisation and internationalisation, the deprofessionalisation of teachers, the entrenchment of detrimental neoliberal practices of governance and accountability, the erosion of institutions and the increasingly unquestioning trust in numbers (Porter, 1995), STS is needed to make sense of, and to respond to, the unique pressures facing the field of education as the approach provides means for engaging with the ontological politics of these phenomena.

In the varied use of STS-studies in education, we see confidence and evidence of a certain maturity and development of the field. We hope this network will provide a space for new debates, new thinking and new and interesting intersections with other theories, which are much needed to engage with the many interesting – and often somewhat terrifying – issues that confront us in the field of education.

Please make sure to submit to the 2023 4S conference

We particularly recommend you to submit to the following Open Panel:

55. Writing machines: large language models, knowledge practices and technoscientific practices of authorship.


Advances in natural language processing have led to the development of 'large language models' (LLMs) capable of generating texts by predictive algorithms, and 'writing' convincing essays, computer code, and even poetry. Their performance has led to claims that they can replace human authorship, and even that AIs have become 'sentient' beings. However, a range of risks has been identified; that they lead to environmental degradation, that synthetic text reinscribes discriminatory language and viewpoints, that they encourage plagiarism, and more fundamentally that they threaten the concept of human authorship itself. This development clearly has profound implications for society, education, knowledge and our relationship to texts, learning, and authority, and raises questions about human co-existence with these technologies as their capacities increase. This proposal is for a panel to consider this 'more-than-human' form of authorship, providing insights into the manifold implications of LLMs. This will generate theoretical and practical insights, setting the agenda for this emergent field of enquiry in STS, interrogating the following themes and more: What sociotechnical imaginaries are expressed regarding LLMs in society? How do LLMs reinscribe or amplify social and epistemic injustices? What are the risks to 'sea, sky and land' brought about by LLMs? How are LLMs are changing texts and how we generate, interpret, and use them? What are the effects in terms of knowledge practices in education and beyond? What are the ontological implications for human authorship and texts themselves? What are the future research agendas for STS in terms of theory and methodology?


Keywords: University-Society Relations, Disciplines and the Social Organization of Science and Technology, Big Data, AI, and Machine Learning, Large Language Models