Paper ID #41739Unfettered ChatGPT Access in First-Year Engineering: Student Usage &PerceptionsDr. Duncan Davis, Northeastern University Duncan Davis is an Associate Teaching Professor in First Year Engineering. His research focuses on using gamification to convey course content in first year classes. He is particularly interested in using the construction of Escape Rooms to teach Engineering Principles.Dr. Nicole Alexandra Batrouny, Northeastern Univeristy Nicole Batrouny is an Assistant Teaching Professor in First Year Engineering at Northeastern University. Her engineering education research interests include the
ondesigning assessments, and communication strategies with students. The study ultimatelyadvocated for the inclusion of GAI in the assessment landscape, calling for the development ofGAI assessment literacy among instructors [10]. A recent systematic literature review also foundthe need for new skills, interdisciplinary teaching methods, and policy implications, highlightingGAI's transformative impact on school education that aligned with their findings in theirliterature review [2]. Following up on the review, Chiu [1] conducted a study to exploreperceptions of AI from the teachers’ point of view and found that tools such as ChatGPT haveinfluenced schools, with the viewpoints of teachers being particularly significant, withconcerning elements such
(NLP) technologies, through the use of artificialintelligence (AI) agents and Large Language Models (LLM), have already provided significantadvantages in the holistic assessment of high-order features such as argumentation, use ofevidence or scientific thinking [4-6]. With the evolution of Automated Feedback Systems (AFS)[7-9] and, more recently, the release of Open AI’s ChatGPT, LLMs have become commonplacein higher education among students and instructors [10, 11]. The emergence of LLMs in higherand secondary education has triggered an influx of publications on the opportunities andchallenges of incorporating these technologies in instruction and evaluation [10, 12, 13].However, the unique nature of engineering design problems, characterized
traditionalNLP methods alone [21]. Additionally, as Large Language Models (LLMs) increase and rapidly develop, manyorganizations and researchers compete to create more powerful and advanced GAI models.These new models aim to outperform older versions [22]. GAI models come as applications ortools like ChatGPT, GitHub Copilot, and Bard to name a few. One key example is the GPTmodel, which has gone through versions 3, 3.5, and now 4, each with different capabilities [22].When new GPT versions are released, they often gain new features, capabilities, and parameterscompared to previous versions [22]. Also, OpenAI and other research groups constantly work toimprove LLMs and other AI models. This could impact the accuracy of the information in
recognition with TensorFlow and Keras, pp. 31-43, 2018.[7] D. Baidoo-Anu and L. O. Ansah, "Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning," Journal of AI, vol. 7, no. 1, pp. 52-62, 2023.[8] E. Brynjolfsson, D. Li, and L. R. Raymond, "Generative AI at work," National Bureau of Economic Research, 2023.