Associate Professor Kalervo N. Gulson

Associate Professor, Associate Dean - Research Training
BA, Grad Dip Ed, MEd(Hons), PhD (Macq)
School of Education


+ 61 2 9385 3744
Room 349, Morven Brown
Fields: Human Geography, Education Policy, Sociology and Social Studies of Science and Technology
Tags: School/Institution Policies and Development, Education and Training Systems Policies and Development


My research is located across social, political and cultural geography, education policy studies, and science and technology studies. My current research programme examines CODE, DATA, SCIENCE and EDUCATION POLICY. The premise of this programme is that the launch of journals such as Big Data and Society, and BioSocieties, and the growth of software studies, point to the ways that increasingly the future of education will be debated and shaped in fields external to education. What I am positing is that there is an urgent need for education to grapple with and form responses to these changes, both in the academy and in public debates. 

My programme includes three interrelated projects: 

1. Data infrastructures, mobility and network governance. This is an Australian Research Council funded project in collaboration with University of Queensland, University of New England, University of British Columbia and the University of Illinois.  This project focus on data infrastructures, mobility and network governance in education, and examines how multiple data sets now drive education systems and schools, as well as smart city programs and the role of schooling in urban planning. This study is investigating the role of data infrastructures in education policy, in schools, systems, nations and globally. The focus is on four related policy contexts in the Asia-Pacific region (Australia, Canada, Japan, USA) and the data mobilities flowing from the release of PISA 2015. The study is interested in the sociological and political ‘life’ of data (a) the concepts of data infrastructure and data mobility; (b) how data creates new spatialised modes of educational governance; and (c) how social and political relations between governments, NGOs and corporations are reconfigured through data use. 

2. The postgenomic age, molecular biopolitics, and education policy. This is a time when following the sequencing of the human genome, where the gene is ‘dynamic’ and flexible leading to a breakdown of biology vs society and biology vs culture.  This is leading to calls for new types of biosociality, and the need to understand the implications of such a biosociality, for education (e.g., Youdell, 2016). The focus of the overall project is on governance, control, commercialisation and eugenics, and engaging with how we might respond to this context. The premise of this project is that postgenomic thinking (e.g., neuroscience and epigenetics), and postgenomic features such as digitalisation and molecularisation, will, and can be, seamlessly integrated into contemporary education policy agendas relating to choice, self-responsibilisation, accountability and performativity. The implications for education and education policy will include the creation of increasingly influential roles for biological and software code, data and metrics, and new forms of commercialization that are emerging (e.g., the use of personal functional magnetic resonance imaging (fMRI) in the classroom). Additionally, new authorities are emerging in education policy, both as rationalities and embodied experts, and these authorities, as part of molecular biopolitics, are creating new subjects and objects of policy and new predictive claims in education policy analysis. 

3.  Machinic learning: Pedagogy, policy and Artificial Intelligence. This project involves a sociological and philosophical investigation of the use of machine learning to inform policy and augment pedagogy. The project consider issues of algorithmic governance, the role of the education technology industry in education (including the software development/statistical analysis pedagogies that shape how people think about education data analysis and its possibilities) and the potentials and constraints of learning with/from machines in the classroom. This project looks at how machine learning makes explicit human's co-constitutive relationship with technology and the potentially shifting balance between ‘tools' and ‘users’. 

I am interested in supervising research students in areas related to the above areas and projects, and anything that is interesting.


Professional contribution

Book series editor, with Trevor Gale (University of Glasgow,  ‘Education policy and social inequality’ (Springer publishers) (,

Regional editor (Asia-Pacific region) for  Journal of Education Policy and Race, Ethnicity and Education

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