A Case Study of Gender-Sensitive Data Literacy Education : Focusing on the Course 〈Big Data and Gender〉 at E University

This study emphasizes the necessity of gender-sensitive data literacy education in the digital society through an action research analysis of the course “Big Data and Gender” at E University. Data bias can be embedded in algorithms and artificial intelligence, reproducing social inequalities. In particular, gender bias can marginalize the voices of women and minority groups, further deepening discrimination. Therefore, gender-sensitive data literacy education goes beyond the technical utilization and interpretation of data; it fosters critical awareness of biases and problematic patterns inherent in data, encouraging its use as a tool for social change. This study presents a gender data literacy education model based on gender-disaggregated statistics and the concept of intersectionality, exploring educational approaches to address social inequalities. The “Big Data and Gender” course consisted of theoretical lessons on gender and practical sessions using gender statistics for data analysis. The course was designed to help students develop the ability to analyze and understand data from a gender perspective, recognize biases, and enhance their critical thinking and analytical skills to contribute to building a more gender-equal data society.