A Review of International Models of Computer Science Teacher Education

Publication date

2022-12-29

Authors

Yadav, Aman
Connolly, Cornelia
Berges, Marc
Chytas, ChristosORCID 0000-0002-8766-5317ISNI 0000000508286901
Franklin, Crystal
Neira, Raquel Hijón
Macann, Victoria
Margulieux, Lauren
Ottenbreit-Leftwich, Anne
Warner, Jayce R.

Editors

Becker, Brett A.
Quille, Keith
Laakso, Mikko-Jussi
Barendsen, Erik

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

Abstract

Throughout the world, Computer Science Education (CSE) has ex- panded exponentially over the past decade, focused on teaching primary and secondary students computing ideas and tools. To teach all these students computer science (CS), models for teacher preparation range from one and done professional learning work- shops to full certificate and licensure programs. This report provides a landscape of how CS teachers are prepared academically in var- ious countries and makes evidence-based recommendations for how teachers should be educated to develop knowledge and skill to teach computer science. It also discusses how to develop these knowledge systems while promoting instruction that is equitable and centers students in the classroom. We brought together a group of international computer science education scholars who have been engaged in teacher preparation. In addition to what knowl- edge teachers need to teach CS, we also focused on how the field is preparing teachers and the role of computer science in the design of technology tools to achieve goals while mitigating potential societal harms.

Keywords

Taverne

Citation

Yadav, A, Connolly, C, Berges, M, Chytas, C, Franklin, C, Neira, R H, Macann, V, Margulieux, L, Ottenbreit-Leftwich, A & Warner, J R 2022, A Review of International Models of Computer Science Teacher Education. in B A Becker, K Quille, M-J Laakso & E Barendsen (eds), ITiCSE-WGR '22 : Proceedings of the 2022 Working Group Reports on Innovation and Technology in Computer Science Education. Association for Computing Machinery, pp. 65-93. https://doi.org/10.1145/3571785.3574123