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Guidance on the Future of

Computer Science Education 

in an Age of AI

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These initial briefs address critical questions related to the role of AI in primary and secondary computer science (CS) education. Additional briefs will be released through early 2025. View the individual briefs and sign up for updates.

Guidance

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in the "Why is it Still Important to Learn to Program?" brief.

code sense  /kōd sens/ noun

Conceptual understanding of a computer program's underlying design, processes, and system relationships, as well as the mental capacity to analyze, simulate, and predict a program’s behavior.

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 CS Teachers

 85%

of CS teachers think AI should be included in a fundamental CS experience.

88% 

of CS teachers want additional resources and professional learning.

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CSTA and TeachAI surveyed 364 computer science teachers between March and July 2024.

Survey insights are included in the briefs, CSTA/TeachAI Survey, and Infographic.  

CS Education

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Research Collection

A resource for educators, students, and researchers looking to learn more about AI in computer science education.

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Future of CS

About the Guidance on the 

Future of Computer Science Education

in an Age of AI

This guidance was developed by TeachAI and the CSTA in partnership with Karen Brennan (Harvard University), Quinn Burke (Digital Promise), Marie desJardins (AAAI), Bruce Fuda (Grok Academy), Christina Gardner-McCune (AI4K12 and University of Florida), Shuchi Grover (Looking Glass Ventures and Edfinity), Maya Israel (University of Florida), Irene Lee (Everyday AI), Matti Tedre (University of Eastern Finland), and Jan Vahrenhold (German Informatics Society).

We thank the TeachAI Future of CS Workgroup, which includes Adobe, Amazon, Black in AI, College Board, Data Science 4 Everyone, Digital Promise, Education Above All, ETS, Texas Advanced Computing Center, GitHub, Google, Grok Academy, Infosys Foundation USA, Institute for Advancing Computing Education, ISTE, Microsoft, National Council of Teachers of Mathematics, NCWIT, RobinCode, and participating U.S. and global government agencies.

These resources are openly available for reuse under a Creative Commons BY-NC-SA 4.0 license. While permission for use isn't required, citing the source is appreciated.

Suggested Citation: TeachAI & CSTA (2024). Guidance on the Future of Computer Science Education in an Age of AI. Retrieved from teachai.org/cs. [date].

The resources were last updated: July 16, 2024.

TeachAI is an initiative that guides education leaders and policymakers in transforming education through teaching with AI and teaching about AI. It is led by Code.org, ETS, the International Society for Technology in Education, Khan Academy, and the World Economic Forum, and advised by a diverse group of 150+ organizations, governments, and individuals. TeachAI’s goals include providing policy guidance, increasing awareness, and building community and capacity.

We’d also like to recognize Allen Antoine, Owen Astrachan, Elaine Atherton, Carla Brodley, Center for Computational Thinking and Design at Aarhus University, Edie Cheng, CS Access, Leigh Ann DeLyser, Charlotte Dungan, Crystal Furman, Dan Garcia, Kinnis Gosha, Mark Guzdial, William G. Harris, Sallie Holloway, Lori Jacques, Antti Kiviniemi, John Kleeman, Jill Kowalchuk, Michael Littman, Yolanda Lozano, Don Miller, John Mitchell, Rusty Nye, Jamie Payton, Chris Piech, Jennifer Rosato, Mehran Sahami, Vicky Sedgwick, Ben Shapiro, Sepehr Vakil, Sara Vogel,  Hannah Walden, Shira Wein, Benji Xie, and Aman Yadav for their input.

Lead Partners

Guidance on the Future of Computer Science Education in an Age of AI 

Partners

In partnership with Karen Brennan, Shuchi Grover, Maya Israel, and Matti Tedre

TeachAI Steering Committee

In coordination with the World Economic Forum

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