Research Interests
Sudha’s research interests include applying psychometric methodologies to the rich and complex data generated by digital assessments, including response-process data, to investigate differential item functioning (DIF), validity, equity and fairness in assessments. She is also interested in AI-based automated scoring in high-stakes assessments, including the transparency, explainability, fairness and validity of the resulting scores.
In particular, her research interests focus on the opportunities offered and challenges posed by digital assessments, and how technological advances can improve the quality, accessibility and fairness of assessments without inadvertently disadvantaging particular groups of learners.
Her doctoral research proposes to examine how response processes, such as time-on-task, number of actions and patterns of interaction with digital tasks, relate to assessment performance, and whether these processes reveal inequalities that may not be apparent from examination scores alone. She is also interested in inequalities arising from differences in familiarity with and access to digital technologies.
A further area of interest is automated scoring, particularly the transparency, explainability and fairness of AI-assisted marking. She is interested in exploring how automated scoring systems can improve assessment efficiency and consistency without compromising validity, introducing systematic bias or obscuring the reasons behind scoring decisions.
Drawing on her experience as a mathematics educator, she is keen to explore the implications of digital assessment and AI-based marking for pupils’ assessment experiences, with a view to informing pedagogy, educational policy and practice.
Academic Profile, Work experience & Awards
Sudha holds a BSc in Mathematics from Women’s Christian College (First Class with Distinction), a Postgraduate Diploma in Business Administration from Loyola Institute of Business Administration (First Class), and a Postgraduate Diploma in Educational Leadership from UCL Institute of Education.
In 2025, she completed an MSc in Educational Assessment at the University of Oxford, where her dissertation, supervised by Professor Jo-Anne Baird, was awarded a Distinction. Using Item Response Theory and qualitative analysis, her research investigated differential item functioning in A-level Mathematics between male and female candidates, with gender operationalised as sex at birth, analysing 435 items across 45 examination papers and data from over 300,000 candidates.
Before beginning her DPhil, she worked as a mathematics teacher and Key Stage 5 coordinator of mathematics. She is a Teach First Ambassador, a member of its inaugural Policy Fellowship cohort, and has contributed to assessment practice through her professional roles.
Sudha’s doctoral research is supported by the funding from ESRC–St John’s College Scholarship and the ESRC Grand Union DTP Data Skills Studentship.
Supervisors