(471d) Embracing Generative AI in Chemical Engineering Education: Enhancing Learning through Chatgpt and Perplexity AI

Generative artificial intelligence (Gen AI) tools are rapidly transforming higher education, prompting innovations in Chemical Engineering instruction that enhance accessibility and depth of learning. The work presents our strategic integration of Gen AI into core undergraduate courses to improve student engagement and conceptual mastery. In CHEG 4303 Process control ChatGPT was employed to clarify complex mathematical operations, such as the chain rule and Laplace transforms through intuitive, step by step explanations. This helped students build a
stronger foundation for understanding control system design. However, we also observed that Chat GPT requires precise user input to generate accurate analyses of reaction kinetics and rate laws.
At graduate level, Perplexity AI has emerged as a powerful resource for conducting real time literature reviews, enabling students to efficiently access, compare and synthesize peer reviewed research. Building on this we plan to incorporate Perplexity AI into CHEG 3305 Equilibrium
Separation Processes as a part of an Aspen HYSYS simulation project focused on binary distillation. Students will use the tool to research and interpret assumptions in shortcut and rigorous distillation methods. In addition, they will explore documented examples of design errors linked
to incorrect process assumptions, fostering a deeper understanding of model limitations and engineering judgment. The integration of GenAI tools demonstrates the ethical and effective use in engineering education, promoting independent learning and preparing students for success in a
data driven AI enhanced professional environment.