Context-prompt reflection assignments in which students elaborate on a concept, apply it to a novel problem, and receive AI feedback¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article proposes reflection assignments as an extension of the same context-prompt framework: students elaborate on their understanding of a specific physics concept, apply it to a novel problem, and receive AI feedback on the completeness, coherence, and correctness of the elaboration. The authors present this as partially automating the resource-intensive process of reflection, while noting that in the present paper reflection is best understood as the next pedagogical extension rather than an equally implemented classroom component.

Design Implications¶

Context¶

Requirements¶

• The reflection context prompt must contain key elements of prompt engineering so that outputs remain constrained and on-target

Constraints¶

• Reflection was not implemented in the classroom as the exploration activities were

Target Learners¶

• undergraduate physics learners

Target Learning Goals¶

• validation and consolidation of acquired physics knowledge

Affordances¶

• Context Prompts Gen Ai Physics

Related Strategies¶

• Grade AI-dialogue assignments on evidence of sustained dialogue, and explicitly teach students to answer the AI's questions
• Maximize Transfer and Generalization
• Elaborative Interrogation
• A proposed but not yet classroom-evaluated extension: have students write and refine the measurement-application prompt themselves

Examples¶

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Key Sources¶

• Miguel Rodriguez and Peter Wulff. (2026). Artificial Intelligence Driven Physics Assignments using Context Prompts. https://arxiv.org/abs/2609.22578