2025 ASEE Annual Conference & Exposition

After conducting an experiment, how do students think, reason, and explain the data? How do they present their understanding in a lab report? Answers to these questions are crucial not only for understanding scientific concepts, but also for shaping the future workforce. [1-3] The integration of Large language models (LLMs) like ChatGPT into education is reshaping technical writing pedagogy, particularly in engineering disciplines. This work-in-progress study investigates the impact of generative AI on scientific writing in a senior-level chemical engineering laboratory course. Students were allowed to use LLMs models during the report-writing process, with self-reported usage analyzed across categories such as grammar enhancement, content clarification, and data visualization. Comparative assessments revealed that independently written reports outperformed LLM-assisted reports, suggesting most students opted to rely on their independent writing skills and did better despite having access to use LLM. The author also emphasizes the importance of effective prompting and reflective evaluation skills. The study also suggests perhaps a comprehensive training for students and educators in integrating generative AI tools effectively in higher education could be beneficial.

[1]. https://www.abet.org
[2]. National Academies of Sciences, Engineering, and Medicine. 2022. New Directions for Chemical Engineering. Washington, DC: The National Academies Press. https://doi.org/10.17226/26342
[3]. Wilson, S. A., & Azarin, S., & Barr, C., & Beckwith, J. K., & Brennan, J., & Carter, T. L., & Karlsson, A. J. (2023, June), Prioritizing learning objectives for chemical engineering laboratory courses Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43961