2026 ASEE Annual Conference & Exposition

Designing AI-enabled MEB Learning Activities

Presented at Leveraging AI for Enhanced Learning

Material and Energy Balances (MEB) is often one of the first technical courses that undergraduates take in the chemical engineering major. Along with providing an introduction to the profession, the course serves an important role in orienting students to how chemical engineers think and solve problems. While MEB content has been roughly similar since at least 1990, some changes, such as greater inclusion of computer usage in calculations and analysis, have been seen in a survey of MEB courses conducted by the AIChE Education Division Survey Committee in Fall 2021.

With the release of ChatGPT in Fall 2022, and as the use of generative AI tools have become more pervasive amongst students, greater consideration is needed by engineering instructors in how to use and integrate these approaches into their own courses. Targeting MEB for the creation of AI-enabled teaching offers an opportunity to integrate AI early into the chemical engineering curriculum. Helping students build critical thinking skills and AI competencies (e.g., the limitations of AI)—or, generally, how to think about AI—at the beginning of their chemical engineering course requirements could help students better understand how they may leverage AI tools throughout their studies, and how AI is being used in the profession. Early disciplinary exposure to AI use may also help shape student perspective on AI and engineering, especially if a student’s previous use of chatbots for studying were not productive. Additionally, the previous MEB survey was conducted before the release of ChatGPT, and would not have been able to capture how instructors for that course may have been leveraging generative AI.

To help address this gap, and as an example of how to intentionally integrate AI into a particular core course in chemical engineering, we are creating MEB activities that leverage commercially available chatbots, which could be used across course contexts, and reflecting on how AI has affected MEB. These learning activities—and other pedagogical materials—are designed to target a range of MEB concepts, learning objectives, and use cases (e.g., in-class or outside of class, one-off or continued use). This work-in-progress paper describes the types of AI-enabled activities we have created, and our reflections on implementing these activities in our classrooms. Our analysis will present strategies for designing homework problems, in-class activities, syllabus language, and other pedagogical materials that may be helpful to instructors who are considering using AI tools for teaching. By sharing a case of multiple instructors designing AI-embedded learning activities for a particular course, along with our observations as to how AI has impacted student learning and our own teaching, we hope our example can inspire other instructors to consider how they may try similar approaches to enhance learning in their own courses by integrating AI intentionally.

Authors
  1. Dr. Sakul Ratanalert Orcid 16x16http://orcid.org/0000-0002-1766-807X Columbia University in the City of New York [biography]
  2. Dr. Taryn Melkus Bayles University of Pittsburgh [biography]
  3. Dr. Janie Brennan Washington University in St. Louis [biography]
  4. Dr. Milo Koretsky Tufts University [biography]
  5. Prof. Adam T Melvin Clemson University [biography]
  6. Dr. Courtney Pfluger Northeastern University [biography]
  7. Dr. Donald P. Visco Jr. The University of Akron [biography]
Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026