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AI and data literacy education

We are embarking on a new series of research projects to investigate how best to learn and teach the fundamentals of artificial intelligence, machine learning, and data science — more details to follow.  

Our partners at the Raspberry Pi Foundation ran a series of online research seminars and a special panel session on this topic between September 2021 and March 2022, hosted in partnership with The Alan Turing Institute.  

We have also conducted a systematic literature review of papers giving empirical evidence from studies of the teaching of AI to young people and a resource mapping exercise categorising over 500 existing resources in the era of AI and machine learning in terms of content, pedagogy, learning goals, and audience (in press). Other research activities include a pilot survey on teachers’ competence and attitudes in AI , a resource categorisation exercise, and the creation of a framework for categorising resources, professional development, and research (currently known as the SEAME model).  


Tshukudu, E., Waite, J., Rizvi, S. & Sentance, S. (2022). Teachers’ Motivations to Learn about ML and AI. In Proceedings of the 27th ACM Conference on Innovation and Technology in Computer Science Education (V. 2) (ITiCSE ’22).

Other reading

Artificial intelligence and data science education — resources and lessons learned
Seminar chapters from our AI and data science education series
Announcing our seminar series in AI and data science education