ValiAssist: Scaling LLM-generated Programming Feedback Validation by Demonstration
Generative AI can create programming feedback at scale, but validating its alignment with instructors' pedagogical goals and strategies remains challenging. Instructors may struggle to fully specify validation criteria upfront, as these often emerge through inspecting concrete examples and revising misaligned feedback. We present ValiAssist, a validation-by-demonstration system that infers reusable validation logic from instructors' revisions of AI-generated feedback and allows instructors to inspect and refine that logic as it is applied across other student submissions. In a comparative study with 16 instructors, ValiAssist helped instructors create and refine validation criteria, produ...
| Authors | Xiaohang Tang, Rehema Abulikemu, Peng Gao et al. |
|---|---|
| Primary category | cs.HC |
| Published | 19 October 2026 |
| Last updated at source | 19 October 2026 |
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