Revolutionizing Teaching and Learning of Material Science and Engineering in Chemical Engineering: The Impact of Generative AI

Conventional pedagogical approaches, frequently dependent on lectures, textbooks, and static visual aids, may find it challenging to properly engage students and facilitate a profound comprehension of complex subjects like material science for chemical engineering. The necessity for interactive, customized, and adaptive learning methodologies utilizing generative AI technologies is essential to improve the instruction and comprehension of this intricate topic. Generative AI is increasingly being used as a transformative tool to advance innovations in education. In particular, large language models like ChatGPT offer revolutionary capabilities for enhancing students’ learning experiences. Hence, it is imperative to explore how ChatGPT can facilitate the revolutionization of teaching and learning material science for chemical engineering. By leveraging social constructiveness theory, ChatGPT was employed as an interactive tool that engages learners in dialogue, prompting them to explore concepts, ask questions, and reflect on their understanding. The study examines how students can employ ChatGPT to create hypothetical alloy materials, determine the properties and construct a eutectic phase diagram for the hypothetical alloy materials. To evaluate the impact of the Generative AI pedagogical approach, a questionnaire survey was developed and distributed to the students. The analysis of the survey revealed that ChatGPT facilitated the understanding of complex engineering courses like material science for chemical engineering, enhanced their critical thinking skills, and improved their learning experience. engineering:I tools like ChatGPT have been demonstrated to have the potential to transform learning experience in material science for chemical engineering; nevertheless, effective ethical governance frameworks and ongoing pedagogical enhancement are essential for successful adoption.