Engineering education's Odyssey with ChatGPT: Opportunities, challenges, and theoretical foundations

Abstract

This study investigates what Artificial Intelligence (AI) and the generative pre-trained transformer (ChatGPT) software offer to engineering education. First, our literature review shows key challenges and considerations linked to infrastructure and resource requirements, digital inequality, data privacy, copyright and some complex ethical issues that come with this pedagogical transformation. However, the article next contextualizes AI and ChatGPT within foundational learning theories such as Constructivist Learning Theory, Personalized Learning Theory, Cognitive Load Theory, and Vygotsky's Zone of Proximal Development, showing how AI and ChatGPT can shift educational practices towards more individualized, dynamic, and active learning experiences. By bringing together practical considerations demanding attention when introducing AI and ChatGPT to engineering course, and the learning theories the digital tools can promisingly enact, this study significantly contributes to ongoing discourse on AI and ChatGPT in engineering education. Different stakeholders, including educators, students, institutions, and industry partners contemplating AI and ChatGPT introduction are likely to be weighing up options. Readers considering whether pedagogical benefits are worth the considerable care needed to introduce these tools in their own engineering faculty should find this article helpful.

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