Use a modular lesson structure to keep integrated AI curricula scalable under time constraints¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Because AI is not typically in standard curricula, the article recommends that "it becomes crucial for educators to consider scalability in the design of such curricula". The study adopted a modular approach in which each lesson was a module placed after students learned the relevant biology knowledge. This structure let the curriculum adapt to varying educational contexts and time limitations while core objectives were still met, for example when Lesson 2 reflections were cut short yet its core objectives were met.

Design Implications¶

Context¶

Requirements¶

• Each lesson designed as a self-contained module sequenced after the relevant subject knowledge is learned

Constraints¶

• Educators must balance incorporating AI topics with state-mandated standards, which can challenge coverage of all intended integrated topics

Target Learners¶

• secondary school students

Target Learning Goals¶

• AI literacy integration within existing subject curricula

Related Strategies¶

• Integrate AI literacy across grades and subject-area learning rather than confining it to electives
• Select familiar contextual topics and age-appropriate materials when integrating AI into subject courses

Examples¶

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Key Sources¶

• Shenghua Zha, Marcy Maulucci Bragdon, Na Gong, Jinhui Wang, Silas Leavesley, Rachel Eaton, Erin Bosarge. (2025). A Case Study of Integrating AI Literacy Education in a Biology Class. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-025-00476-8