Transformative insights? An exploration of critical data literacy with undergraduate learners from Southern India

Abstract

The Civic Statistics (CS) approach promotes critical data literacy for engaged citizens; however, empirical evidence of its effectiveness remains limited. This study examines how participation in a civic statistics informed Data Science (DS) and Artificial Intelligence (AI) course relates to changes in learners’ descriptions of their technical and critical data literacy and whether these changes persist over time. The study examines a 24-hour online DS and AI course, with an extended 40 hour in-person immersion for a subset of participants. Twenty-one undergraduate engineering and computer science students from Southern India participated in the study (nine completed the extended programme). Self-report surveys were administered before the course, immediately after the online course and six months later. Thematic analysis was used to examine open-ended responses for critical data literacy dimensions (cognitions, dispositions, actions). Four themes emerged: Developing Understanding, Learner Enthusiasm, Real-world Engagement and Critical Evaluation . Respondents’ reflections on learning shifted from descriptive toward context-rich, application-oriented perspectives and more nuanced understandings of DS and AI. These insights persisted, potentially indicating a transformation in understanding across learner responses.