EdTech Engineers And the Making of Machine Learning in Education

Project dates (estimated):

October 2022 - June 2026

Name of the PhD student:

Meenakshi Mani

Supervisors:

Ben Williamson – Centre for Research in Digital Education, Moray House School of Education & Sport

Sian Bayne – Centre for Research in Digital Education, Moray House School of Education & Sport

Project aims:

The purpose of this study is to explore how Indian EdTech engineers incorporate ideas about teaching and learning into the development of AI education technologies for K-12 classrooms. The study also aims to understand how machine learning infrastructures interact with and influence engineering practices in AI EdTech development, and to contextualize these insights within the larger political and economic machinery of Indian EdTech.

Disciplines and subfields engaged:

  • Digital Education

  • Critical Data Studies

  • Software Studies

  • AI Ethics

  • Platform Studies

  • International Education

Research Themes:

  • Ethics of Algorithms

    • Bias and Discrimination in Machine Learning

    • Ethics of Algorithmic Decision-Making

    • Algorithmic Accountability and Responsibility

  • Ethics and Politics of Data

    • Ethical Data Science and Data Practice

Related outputs:

Publications:

  • Molnar, A., Boninger, F., Noble, A., & Mani, M. (2023). We need better education policy. Summit Public Schools shows why. Boulder, CO: National Education Policy Center. 🔗

Conference Presentations:

  • Accepted to present ROYBI: Investigating how machine learning infrastructures influence what gets built in EdTech at the British Educational Research Association conference. University of Manchester. September 9, 2024.

  • Accepted to present Investigating the influence of Machine Learning infrastructures and processes on the building of EdTech at the Association of Internet Researchers conference. University of Sheffield. Nov 1, 2024.

Grants & Awards:

  • EFI Student Research Awards (Feb 2024, £800, w/ Elif Doyuran): AI at (software) work: perils, promises, realities

Other Outputs:

  • Funded participant at the summer school: Doing Qualitative Education Research in/of/through Algorithmic Environments held at Helmut Schmidt University. September 2022.

  • Participant at the Digital Humanities Research Software Engineer summer school organized by the Edinburgh Centre for Data, Culture & Society, Cambridge Digital Humanities, King’s Digital Lab and The Alan Turing Institute. July 2024.

PhD ResearchCTMF AdminEthics of Algorithms, Ethics and Politics of Data, Digital education, critical data studies, software studies, Platform Studies, International Education