Education technology and data science for inclusive systems
Co-convenors: Patrick Montjourides and Kate Radford
Much attention is given to the potential for education technology and data science in development settings to improve educational outcomes. As technology develops and spreads, education data becomes a new and valuable commodity with important consequences for education systems. The potential of education technology has attracted new private sector investment in education, but with the risk that commercial interests could conflict with equity goals. Education technology has the potential to provide solutions to reach the most vulnerable, support teachers in under-resourced classrooms, enable wider participation in higher and adult education and provide real time monitoring data. However, the relationship between inclusion and education technology is not always straightforward. Education technology requires an enabling technological and social environment which might not be found where the needs are greatest, and those most in need, including marginalised girls and people with disabilities, may have the least access. What evidence is emerging on the effectiveness and efficiency of technological solutions to educational ‘problems’? Is there potential for education technology to transform the landscape of education systems? And if so, how? Are education technologies contributing to exclusion and marginalisation of educational opportunities?
The use of technology in education demands a new set of skills from both practitioners and policy makers. What efforts have or could be made to build competency with education sector actors? How has the global education development sector worked together to develop appropriate policies at national and international level which take into account competency development requirements, data protection, child safeguarding and research ethics in the digital age? What are the future recommendations for policy makers?
In academia the exponential increase in the production and availability of data has the potential to substantially influence research methods and cross-disciplinary collaboration. In other fields, data scientists have become a staple of methodological approaches at the knowledge frontier. Ability to handle big data, machine learning algorithms and advanced visualizations are becoming increasingly important with the development of computational social sciences and digital humanities. What are the implications of the increasing prevalence of education technology and education data for academics and the topics/issues they research? Does it favour specific topics and epistemological approaches over others? Do we see changes in agency among academics and education stakeholders? What are some of the new approaches that have been used? Has data science contributed to bridge between policy, research and practice?
We welcome theoretical or conceptual ‘think-pieces’ as well as empirical research and lessons from practice that address these questions and topics.
For any questions on this theme please contact Kate Radford
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