Innovating engineering education with AI: a case study on ChatGPT 4.0’s role in statics-physics

Abstract

Integrating advanced technologies, like chatbots, offers promising innovations in education. This study addresses the challenges in teaching Statics, a branch of physics foundational in many engineering disciplines, by introducing a methodology that combines AI-driven tools with active learning strategies. Specifically, it proposes the Flipped Chatbot Test, a model that integrates the ChatGPT 4.0 API within a flipped classroom framework to enhance student engagement and understanding. The methodology employs structured prompts that enable the chatbot to provide real-time feedback and grading, fostering a personalized learning environment. A case study with engineering students was conducted to evaluate its effectiveness. Results indicated positive reception, with students highlighting the benefits of instant feedback and improved conceptual clarity. Findings suggest that integrating chatbots into education can enhance learning outcomes, promoting active participation, immediate feedback, and continuous improvement in engineering education. Furthermore, the methodology shows potential for scalability and inclusive education by accommodating diverse learning needs. This work presents a practical model for institutions seeking to integrate AI into their educational practices, thereby creating dynamic and responsive learning experiences. The document also discusses the importance of prompt engineering in chatbot architecture and how the flipped classroom emerges as a solution to the evolving needs of students.

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