Integrate computational thinking into existing disciplinary teaching across grade bands rather than adding it on¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The guide recommends that educators embed computational thinking into topics they already teach, such as math and ELA, so it becomes a value-add rather than an add-on to an overscheduled day. It provides tables of example integrations across arts, ELA, math, science, and social studies for PreK-2, grades 3-5, and grades 6-12. The guide states that "it is essential that educators integrate computational thinking with the topics they already teach, like math and ELA. Then, computational thinking can become a value-add to disciplinary learning and not an add-on to an already overscheduled school day."

Design Implications¶

Context¶

Requirements¶

• Educators leverage synergies between disciplinary learning and computational thinking and promote student agency and purpose

Constraints¶

• In younger grades the focus is on building skills and foundational interest; practices such as developing computational artifacts are positioned for older grades (4-12)

Target Learners¶

• K-12 students across PreK-2, grades 3-5, and grades 6-12

Target Learning Goals¶

• Computational thinking embedded in arts, English language arts, math, science, and social studies learning

Related Strategies¶

• Integrate data and analysis into existing K-2 teaching practices through classroom graphs such as birthdays and word walls.
• Integrate AI literacy across grades and subject-area learning rather than confining it to electives
• Design early learning (K-3) CT opportunities both plugged and unplugged, with devices leveraged where appropriate
• Embed AI literacy across disciplines by identifying intersections with existing content and using case studies, interdisciplinary modules, and collaborative projects
• Build computational thinking skills in the younger grades through plugged and unplugged activities
• Embed new solutions into existing operations and procedures to sustain and scale them
• Integrate computational thinking into PreK-8 core subject matter rather than relying on stand-alone clubs and classes
• Integrate AI assistants with existing curricula and teaching practices rather than replacing instruction
• Embed AI training for pre-service science teachers within science pedagogy and inquiry-based teaching rather than general tool operation
• Embed integration elements in the robot's persona and background so multicultural inclusion is addressed within regular activities
• Select familiar contextual topics and age-appropriate materials when integrating AI into subject courses
• Embed subject-specific web credibility modules into existing courses rather than creating standalone courses
• Integrate AI literacy into disciplinary core subjects rather than adding a new AI subject
• Embed computational thinking across existing K-12 subject areas using everyday and data-based activities

Examples¶

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Key Sources¶

• Mills, K., Coenraad, M., Ruiz, P., Burke, Q., & Weisgrau J. (2021, December). Computational thinking for an inclusive world: A resource for educators to learn and lead, Quick start and discussion guide. Digital Promise. https://doi.org/10.51388/20.500.12265/140