Fairness in machine learning: A design research study for secondary education

This conceptual paper presents a design research study that explores fairness in machine learning (ML) as an interdisciplinary learning opportunity for secondary education. Drawing on the societal relevance of algorithmic decision-making systems, the study emphasizes the importance of integrating technical and ethical perspectives within a cohesive teaching-learning arrangement – an approach that is still rarely implemented in practice. The paper provides an overview of fairness definitions and algorithmic intervention strategies, alongside a review of relevant educational research on ML and fairness in both school and higher education contexts. It outlines the methodological foundations of the design research study and introduces preliminary ideas for a prototypical teaching-learning arrangement, accompanied by guiding research questions that frame the study.