Informatics in Education

While the urgency of AI literacy has been broadly acknowledged, little empirical research has examined how AI education supports the internalization of AI concepts. Whereas much AI education research reports short-term learning gains, this study investigates how students use AI concepts to mediate collaborative reflection and ethical reasoning after participation in a three-year co-design based cumulative AI education program. Drawing on sociocultural and cultural-historical activity theory, we qualitatively analyzed group interviews with 40 K–12 students in grades 6 and 9. The results show that students fluently used AI concepts as mediating tools. Instead of commonsense explanations and folk theories, students relied on scientific explanations and used AI concepts to explain classifier behavior, social media mechanisms, user engagement, and filter bubbles. These concepts and theoretical orientation to everyday data-driven systems extended to ethical reasoning and critical analysis of practices, structures, and problems in everyday life both at personal and societal levels. The study highlights the potential of cumulative AI education to foster transformative learning and agency, extending AI literacy beyond functional understanding toward volition and abilities to question existing practices, envision alternatives, and take informed action.

This article examines pre-service teachers’ data agency, defined as the ability to act according to one’s own values and goals rather than being directed by algorithmic systems. Data agency involves understanding how computational systems, such as algorithms, data-driven profiling, and platform infrastructures, collect, process, and use data, and how these practices shape individuals and society. This article introduces a self-assessment instrument developed to measure data agency and applies it to a sample of 163 Finnish pre-service teachers. The findings show that pre-service teachers evaluated their competencies across different dimensions of data agency rather cautiously. The study highlights the importance of strengthening future teachers’ understanding of the mechanisms behind algorithmic and data-driven decision-making. Such knowledge is increasingly essential for preparing future teachers to address challenges related to datafication, including commercial data collection and algorithmic influencing in contemporary education.

The integration of artificial intelligence (AI) topics into K–12 school curricula is a relatively new but crucial challenge faced by education systems worldwide. Attempts to address this challenge are hindered by a serious lack of curriculum materials and tools to aid teachers in teaching AI. This article introduces the theoretical foundations and design principles for implementing co-design projects in AI education, empirically tested in 12 Finnish classrooms. The article describes a project where 4th- and 7th-graders (N = 213) explored the basics of AI by creating their own AI-driven applications. Additionally, a framework for distributed scaffolding is presented, aiming to foster children's agency, understanding, creativity, and ethical awareness in the age of AI.