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Embedding Emerging AI Literacy Frameworks in a Spiral K-12 CS Curriculum

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Poster
Poster Theme: AI & Emerging Tech in Education
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Session description

The AI literacy standards landscape is shifting fast and new frameworks are redefining what students should know and be able to do with AI. This session examines how those standards directly shaped the design of Level Up, a K-12 CS/AI curriculum co-published with McGraw Hill.

Outline

1. The Shifting AI Literacy Standards Landscape (approx. 10 min)
2. From Standards to Curriculum Design: Key Principles (approx. 12 min)
3. Case Examples from Level Up: Standards in Action (approx. 10 min)
4. Ethical AI as a Standards Requirement, Not an Add-On (approx. 8 min)
5. Assessing Your Own Alignment Readiness (approx. 10 min)
6. Closing and Q&A

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Outcomes

1. Map the current AI literacy standards landscape and understand how each framework distributes AI learning across grade levels.
2. Identify the key design decisions that standards alignment drives in a spiral K-12 CS curriculum, including sequencing, progression, and ethical reasoning benchmarks at each grade band.
3. Examine concrete examples of how AI literacy content in Level Up through Digital Discoveries was developed in response to specific standards requirements, from early AI awareness in Grades K-2 through applied machine learning concepts in Grades 11-12.
4. Evaluate the readiness of schools or districts to align with emerging AI literacy standards, and identify priority areas for curriculum update or professional development.

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Supporting research

CSTA & TeachAI. (2024). Guidance on the future of computer science education in an age of AI. https://teachai.org/cs.
Mills, K , Ruiz, P , Lee, K , Coenraad, M , Fusco, J , Roschelle, J & Weisgrau, J (2024). AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology. https://doi.org/10.51388/20.500.12265/218
Shuchi, G.. (2024). Teaching AI to K-12 Learners: Lessons, Issues, and Guidance. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1 (SIGCSE 2024). Association for Computing Machinery, 422–428. https://doi.org/10.1145/3626252.3630937
TeachAI.org. (2023). AI guidance for schools toolkit. https://teachai.org/toolkit.
Touretzky, D., Gardner-McCune, C., & Seehorn, D. (2023). Machine learning and the five big ideas in AI. International Journal of Artificial Intelligence in Education, 33(2), 233-266.
UNESCO. (2024). AI competency framework for students. https://unesdoc.unesco.org.
UNESCO. (2022). K-12 AI curricula: A mapping of government-endorsed AI curricula. https://unesdoc.unesco.org.

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Presenters

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Andreas Tsouchlaris
VP, Academic & Research
Binary Logic SA

Session specifications

Topic:

Computer Science and Computational Thinking

Grade level:

PK-12

Audience:

District-Level Leadership, School Level Leadership, Teacher

Attendee devices:

Devices not needed

Subject area:

Computer Science, Technology Education

ISTE Standards:

For Educators: Leader, Facilitator
For Students: Computational Thinker

Disclosure:

The submitter of this session has been supported by a company whose product is being included in the session