Advanced technologies that can process complex biological data have transformed the human sciences, and are now being used to conduct studies and generate new knowledge in the field of education. The Leverhulme Trust has just awarded a research project grant to study the rise of data-intensive, computational biology in education to Ben Williamson (University of Edinburgh), Jessica Pykett (Birmingham) and Martyn Pickersgill (Edinburgh). We’re thrilled to be collaborating as a team on this project, which builds on previous work we have separately completed on the application of biology in education and policy, including epigenetics, brain-based teaching, neurotechnologies, and bioinformatics-based polygenic scoring. The project also represents an exciting opportunity to build interdisciplinary connections across our respective fields of education governance, social and political geography, and sociology of science and medicine.
As a way of initially characterizing the developments we will study, we see data-scientific biology in education emerging from three core developments. First, advanced computer technologies are transforming the biological sciences and leading to new ways of understanding and treating human bodies, such as in the biomedical field of ‘precision medicine’. Second, biological understandings of learning are returning to educational debates as new scientific knowledge about the biological underpinnings of learning and educational outcomes are produced by scientists working in fields of neuroscience, psychology, and genomics. And third, learning sciences and analytics experts increasingly use advanced computer techniques such as biosensors and brain scanners to assess the biological aspects of learning. As such, we will examine both data-intensive biology as a science-in-the-making and its positioning as a potentially policy-relevant science with significant practical and political implications in education.
The project is grounded in previous research studying such developments as data-centric biology, precision medicine, post-genomics, digital psychometrics, emotion analytics, neurotechnologies, and bioinformatics. Such work points to the considerable impact that data science and computation have exerted on biological discovery and knowledge production, and the scientific and ethical problems accompanying them. We will be asking questions about whether or how data-intensive biology in education constructs new knowledge about embodied learning processes, and whether novel biological conceptions of learners and learning produced through data science are being deployed as forms of policy or practice intervention.
The overarching objective of the study is to identify and interrogate the apparatuses, organizations, expertise, laboratory practices, and technological machinery that make data-scientific biology in education possible. This empirical objective will specifically enable us to understand the methodological and technical processes that underpin knowledge claims about learning and education emerging from data-scientific biology. The second key objective is to examine how new biological understandings and knowledge of learning might transform educational research, policy, practice, and public understandings of education, and to identify the practical, political and ethical consequences of these new ways of thinking about biology in education.
We’re delighted the Leverhulme Trust has awarded us a research project grant to start this program of work, including funding for a full-time postdoctoral research fellow for two years from September 2021. It will be a really exciting post for someone interested in the empirical social scientific study of data-intensive biology, and its implications for domains of public policy such as education.