RPF Seminar: Data-related concepts and practices for AI education in K–12

Curricula around the world have started to include content related to AI into their agendas. This process is timely and important, but it is also challenging because the elaboration of the AI field for K–12 is still ongoing. Current efforts often underappreciate the critical role of data, despite it being a fundamental component of AI systems. If the goal is to enable students to understand how AI systems work and what their implications are, it is crucial to understand what data underpins these systems, and how it is collected and processed.

To advance knowledge about the role of data in AI education, Viktoriya Olari conducted a comprehensive theoretical analysis of the AI field. In this seminar, she will present the results of her work: a model of key data-related practices and a collection of key data-related concepts that are essential for understanding how AI systems are created and function. She will also share insights from a design-based research study on implementing data-related concepts and practices in AI education in schools.

Viktoriya Olari is a researcher and PhD student in the Computing Education Research Group at the Free University of Berlin, with research interests in AI and data education. She has worked on various projects educating teachers and students on AI and data literacy, such as TrainDL. She served as a member of the AI literacy expert group at the Council of Europe and is currently an advisory board member of the Data Civic Lab in Germany