In the second episode [link] of the AIDL podcast series, Dr. Michael Hallissy is joined by Dr. Harvey Mellar to explore what current research tells us about data literacy and the use of generative AI in education. Drawing on findings from surveys across seven European countries, the conversation offers a practical look at how teachers and systems are engaging with AI, and what this means for teaching and learning.
The discussion highlights widespread use of generative AI for planning and preparation, but limited use in the classroom. It also explores the often-blurred distinction between data literacy and information literacy, and why both matter when working with AI tools. A key focus is on developing critical thinking, not as a single skill, but as a way of questioning how data is generated, interpreted, and used.
Overall, the episode underlines the need to support teachers with the knowledge, resources, and space to help students engage critically with AI in a data‑rich world.
Notable takeaways
- Personal use of generative AI by teachers is widespread, but classroom use is still limited
- There is significant variation across countries in how data literacy is taught
- Data literacy and information literacy are closely related but not the same
- Critical thinking involves questioning processes, assumptions, and interpretations
- Teachers need more support and resources to teach AI, ethics, and data literacy
- Generative AI outputs should be treated as data to be interpreted, not accepted blindly
Additional resources
