Leveraging Artificial Intelligence for Cadet Education
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Research
Artificial Intelligence, Education, Language Learning, Large Language Model, e-Learning
Abstract
This paper contributes to the ongoing discourse on integrating artificial intelligence (AI) technologies into educational settings while addressing the challenges within military institutions. Specifically, we investigate how the United States Military Academy (USMA) can integrate emerging technology into classrooms while upholding core military values. We conducted a comprehensive assessment of potential AI applications at USMA, culminating in the development of a use-case feasibility index for educational purposes. We developed an AI-powered platform that would enable cadets and faculty to create customizable chatbots aimed at enhancing learning experiences. We devised Portuguese AI chat and feedback bots aligned with Standard Portuguese (LP204) curriculum objectives, facilitating natural conversations, and delivering personalized feedback to users. Through a systematic test conducted across all LP204 sections, followed by a post-application survey, we examined the efficacy that AI can have on language learning programs. Findings reveal positive feedback, suggesting the potential utility of AI-driven educational tools.
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References
Chen, C. (2023, March 9). AI Will Transform Teaching and Learning. Let’s Get it Right. https://hai.stanford.edu/news/ai-will-transform-teaching-and-learning-lets-get-it-right
Elmessiry, A., Elmessiry, M., & Elessiry, K. (2023, July 5). Unethical use of Artificial Intelligence in Education. EDULEARN23 Proceedings. https://doi.org/10.21125/edulearn.2023.1764
Gilland, S. LTG. (2024, March 11). West Point Mission Statement Update | West Point Public Affairs | United States Military Academy West Point. https://www.usma.edu/news/press-releases/west-point-mission-statement-update-0
Google. (2023, August 8) Introduction to Large Language Models | Machine Learning. Google for Developers. https://developers.google.com/machine-learning/resources/intro-llms
Mollick, E., & Mollick, L. (2023, September 25). Part 4: AI as Learner. Harvard Business Publishing. https://hbsp.harvard.edu/inspiring-minds/ai-as-learner
Monash Lens. (2019, July 22). As machines get smarter, will we all become dumber? Monash University. https://lens.monash.edu/@politics-society/2019/07/22/1375667?slug=social-de-skilling-automation-in-the-era-of-smart-machines
Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence, 2, 100025. https://doi.org/10.1016/j.caeai.2021.100025
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