Integrating data science education and responsible AI in teacher training: A pilot study within STEAM-based graduate learning
DOI:
https://doi.org/10.52041/iase25.129Abstract
This pilot study explores the integration of data science and responsible AI within a STEAM-based graduate course for education majors, developed as part of the EU-funded DataSETUP project. Focusing on a single module—Responsible AI & Data Science: Ethics, Society, and Citizenship—the research examines a group-based activity in which student teachers collaboratively built an image classification model using Google’s Teachable Machine. Participants engaged with core elements of the machine learning pipeline and reflected on issues such as data quality, algorithmic bias, and educational relevance. To analyze student learning, a five-dimension analytical framework was developed, synthesizing concepts from data science, statistics education, and critical data literacy. The framework captures both technical engagement and student teachers’ evolving understanding of the social and ethical implications of data-driven AI decision-making. Findings indicate that focused, hands-on experiences within a targeted module can meaningfully enhance student teachers’ data science literacy and their critical awareness of responsible AI use in education.References
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