Foster hands-on student practice of the full responsible AI use cycle across authentic contexts¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The brief recommends integrating practical, hands-on experiences—simulations and project-based learning—where students practice the full cycle of responsible AI use: determining whether AI use is appropriate for a task, critically evaluating AI outputs, and refining or abandoning AI-generated results based on quality, accuracy, or ethical concerns. It stresses that "What works for one subject might not work for another," so students should experience authentic AI practice across the curriculum, with engagements centering human potential, creativity, ethical reasoning, and collaboration.

Design Implications¶

Context¶

Requirements¶

• Authentic learning contexts across disciplines
• Opportunities to practice conceptual questioning and contextual prompting

Constraints¶

• Discipline-specific: practice in physics problem-solving may not transfer to other subjects

Target Learners¶

• Postsecondary students across disciplines

Target Learning Goals¶

• Critically evaluating AI outputs
• Making informed decisions about when and how to use AI

Related Strategies¶

Examples¶

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Key Sources¶

• Zachariah, I., Peters Hinton, V., Ruiz, P., Dallas, D., Liberman, B., & Karim, S. (2025). AI Literacy in Postsecondary Education. Digital Promise. https://doi.org/10.51388/20.500.12265/270