Integrate AI-supported experimental design with professional validation to make authentic inquiry manageable in undergraduate laboratories¶
Design · All designs
Evidence · 2 claims (2 for) · 1 study (1 design),q2· 0 of 1 report an effect size · 2 claims rest on one study
Description¶
The article presents an approach where students use AI to design lab manuals for real-world sample analysis, then implement them experimentally. AI's "rapid response and capacity to produce extensive information from user prompts" helps students narrow broad topics and develop manuals, making Level 3 authentic inquiry more accessible. Independent professional validation ensures safety and feasibility before implementation.
Design Implications¶
Context¶
Requirements¶
- AI tools available to students with institutional guidance on ethical use
- Professional validation team to verify safety and feasibility of student-designed manuals
- Consultation sessions with instructor for safety protocols and practical guidance
- Two draft submissions with instructor feedback before experimental sessions
Constraints¶
- Students need prior hands-on experience with relevant analytical instruments
- Requires staff availability for increased supervision workload
- Students need foundational knowledge to critically evaluate AI-generated content
Target Learners¶
- third-year undergraduate analytical chemistry majors
Learning Goals¶
- experimental design skills
- critical thinking
- problem-solving
- troubleshooting
- scientific communication
Claims¶
- Ai Lab Manual Design Increased Confidence Experimental Design [+M]
- Six Of Eight Groups Completed Experiments [+M]
Related Designs¶
Examples¶
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Key Sources¶
- Yim, K.-H.; Lui, M. Y. (2026). Supporting Undergraduate Students' Learning in Practical Chemistry Courses through AI-Supported Experimental Design. Journal of Chemical Education. https://doi.org/10.1021/acs.jchemed.5c01311
Page metadata
| Field | Value |
|---|---|
type |
design |
id |
ai-supported-authentic-inquiry-professional-validation |
title |
Integrate AI-supported experimental design with professional validation to make authentic inquiry manageable in undergraduate laboratories |
description |
The article presents an approach where students use AI to design lab manuals for real-world sample analysis, then implement them experimentally. |
status |
review |
generated |
by process:settle-candidates on 2026-10-12 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — yim-2026 |
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