ChatGPT in Research and Education: A SWOT Analysis of Its Academic Impact

Abstract

Advanced artificial intelligence technologies such as ChatGPT and other large language models (LLMs) have significantly impacted fields such as education and research in recent years. ChatGPT benefits students and educators by providing personalized feedback, facilitating interactive learning, and introducing innovative teaching methods. While many researchers have studied ChatGPT across various subject domains, few analyses have focused on the engineering domain, particularly in addressing the risks of academic dishonesty and potential declines in critical thinking skills. To address this gap, this study explores both the opportunities and limitations of ChatGPT in engineering contexts through a two-part analysis. First, we conducted experiments with ChatGPT to assess its effectiveness in tasks such as code generation, error checking, and solution optimization. Second, we surveyed 125 users, predominantly engineering students, to analyze ChatGPTs role in academic support. Our findings reveal that 93.60% of respondents use ChatGPT for quick academic answers, particularly among early-stage university students, and that 84.00% find it helpful for sourcing research materials. The study also highlights ChatGPT’s strengths in programming assistance, with 84.80% of users utilizing it for debugging and 86.40% for solving coding problems. However, limitations persist, with many users reporting inaccuracies in mathematical solutions and occasional false citations. Furthermore, the reliance on the free version by 96% of users underscores its accessibility but also suggests limitations in resource availability. This work provides key insights into ChatGPT’s strengths and limitations, establishing a framework for responsible AI use in education. Highlighting areas for improvement marks a milestone in understanding and optimizing AI’s role in academia for sustainable future use.

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