Digital Competencies for Effective GenAI Use in Secondary Schools: A Longitudinal Exploration of Teachers' Perspectives and Classroom Practices

Background: The rapid rise of Generative Artificial Intelligence (GenAI) is transforming education. At this stage, there is not yet a well-established and tested theoretical framework clarifying which competencies learners must possess to use GenAI effectively and safely. This study draws on three theoretical frameworks: Eshet-Alkalai's Digital Literacy Framework (2012), Long and Magerko's AI Literacy (2020) and DigComp 2.2. Objectives: The study aims to explore teachers' perspectives regarding the digital competencies that students need for effective GenAI tool use, as well as the classroom learning activities that facilitate the development and practice of these competencies and how they evolve over time. Methods: We conducted 34 semi-structured interviews at an interval of 6–8 months with 17 teachers who had begun utilising a variety of GenAI tools for teaching purposes. This mixed-methods study combines qualitative top-down and bottom-up thematic analysis with quantitative comparisons between the pre and post measurements. Additionally, for data triangulation, a large qualitative sample of 97 GenAI-enhanced learning activities conducted in classrooms was analysed. Results and Conclusions: Findings revealed seven key competencies categorised into general digital literacies, emerging technology literacies and GenAI-specific competencies. Three categories of classroom activities that practiced these competencies emerged: proper use of tools, fostering personal expression and encouraging critical discussion. As expected in the beginning of new technology integration, declines were observed in most competencies in both interviews and learning activities, except for a significant increase in critical-thinking competencies and stable levels of managing-ongoing dialogue. The findings suggest expanding the digital literacy framework by incorporating ‘Learning New Technology’, which covers general competencies for integrating emerging technologies, and specific GenAI-related competencies. The study offers valuable insights into theory and practice AI-enhanced learning.