Addressing AI and Data Literacy in Teacher Education: A Review of Existing Educational Frameworks

Abstract

Being able to use data and AI technologies responsibly is considered increasingly relevant to all school subjects. Despite this trend, existing AI literacy frameworks used to design educational activities often barely cover data literacy. However, AI cannot be appropriately grasped without data literacy, and working with data requires knowledge of AI on multiple levels. To date, though, no framework has been created that considers AI and data literacy holistically. To address this gap, we examine the relationship between AI and data literacy competencies in existing educational frameworks and propose a preliminary approach that utilizes the data lifecycle to reflect on data literacy competencies relevant to AI. The findings provide a basis for developing a comprehensive approach to the education of K-12 teachers of all subjects in AI and data literacy.