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Supporting Undergraduate Students' Learning in Practical Chemistry Courses through AI-Supported Experimental Design

● high · 2026-08-19 · chemistry-education, higher-ed, laboratory, ai-literacy, critical-thinking

Synthesis: Yim and Lui (2026) report an authentic pedagogical approach integrating AI chatbots into an upper-division undergraduate analytical chemistry laboratory course: students used AI to design lab manuals for analyzing real-world samples, then implemented them through hands-on experimentation, with the manuals reviewed by independent testing and certification professionals. Surveys and focus-group Feedback indicated significantly enhanced student confidence in conducting experiments and soft skills — critical thinking, problem-solving, analytical abilities, and experimental design. A key finding was the shift in staff roles from the traditional "cookbook" demonstration model toward guiding and advising students as they address unexpected issues from student-designed lab manuals.

The pedagogical approach

  • Authentic task: students designed a lab manual for analyzing real-world samples using AI, then implemented it hands-on.
  • Validation: lab manuals were reviewed by independent testing and certification professionals to ensure the accuracy and reliability of AI-generated content.
  • Evaluation: surveys and focus-group interviews with students and staff.

Findings

  • Confidence and soft skills: the approach significantly enhanced students' confidence in conducting experiments and their critical thinking, problem-solving, analytical abilities, and experimental design skills.
  • AI's role: AI was particularly beneficial for ideation, scoping, and managing language-related tasks; with effective prompting it provided useful background information and generic experimental procedures.
  • Student discernment: many students preferred to consult their own literature reviews for critical details, expressing concerns about potential inaccuracies in chemical calculations and the reliability of advanced chemistry content — evidence of evaluative engagement with AI output.
  • Staff role shift: instead of demonstrating established experiments ("cookbook"), staff now encounter a broader range of unexpected issues arising from student-designed lab manuals, focusing on guiding and advising rather than supplying definitive answers.

This complements the wiki's framing of critical AI use and human–AI collaboration: students learned to interrogate and verify AI-generated content rather than accept it uncritically.

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Citation

Yim, K.-H., & Lui, M. Y. (2026). Supporting undergraduate students' learning in practical chemistry courses through AI-supported experimental design. Journal of Chemical Education, 103(6), 3022–3030.