超越传统教学：大型语言模型与聊天机器人在研究生工程教育中的潜力
Beyond Traditional Teaching: The Potential of Large Language Models and Chatbots in Graduate Engineering Education
AI总结：
本研究探讨将大型语言模型和聊天机器人整合至研究生工程教育，通过流体力学课程评估其回答能力，并展示智能提示和插件扩展的潜力，倡导平衡应用。
摘要：
在教育快速发展的背景下，数字技术已反复颠覆传统的教学方法。本文探讨了这些颠覆中的最新一次：将大型语言模型（LLMs）和聊天机器人整合到研究生工程教育中的潜在可能性。我们首先追溯历史和技术上的颠覆以提供背景，然后介绍机器学习、深度学习等关键术语，以及近期进展的底层机制，即注意力/Transformer模型和图形处理单元。我们调查的核心在于将基于LLM的聊天机器人应用于研究生流体力学课程。我们根据课程材料开发了一个题库，并评估了聊天机器人提供准确、有见地回答的能力。结果令人鼓舞，不仅展示了该机器人有效回答复杂问题的能力，还展示了在课堂中使用聊天机器人的潜在优势，如促进自定步调学习、提供即时反馈以及减轻教师工作负担。研究还考察了智能提示对提升聊天机器人性能的变革性影响。此外，我们展示了诸如Wolfram Alpha用于数学问题求解和代码解释等强大插件如何显著扩展聊天机器人的能力，将其转变为全面的教育工具。在承认在教育中使用此类AI模型所伴随的挑战和伦理影响的同时，我们倡导一种平衡的方法。在研究生教育中使用LLMs和聊天机器人可能非常有益，但需要持续的评估和调整，以确保其伦理和高效的使用。
英文摘要：
In the rapidly evolving landscape of education, digital technologies have repeatedly disrupted traditional pedagogical methods. This paper explores the latest of these disruptions: the potential integration of large language models (LLMs) and chatbots into graduate engineering education. We begin by tracing historical and technological disruptions to provide context and then introduce key terms such as machine learning and deep learning and the underlying mechanisms of recent advancements, namely attention/transformer models and graphics processing units. The heart of our investigation lies in the application of an LLM-based chatbot in a graduate fluid mechanics course. We developed a question bank from the course material and assessed the chatbot's ability to provide accurate, insightful responses. The results are encouraging, demonstrating not only the bot's ability to effectively answer complex questions but also the potential advantages of chatbot usage in the classroom, such as the promotion of self-paced learning, the provision of instantaneous feedback, and the reduction of instructors' workload. The study also examines the transformative effect of intelligent prompting on enhancing the chatbot's performance. Furthermore, we demonstrate how powerful plugins like Wolfram Alpha for mathematical problem-solving and code interpretation can significantly extend the chatbot's capabilities, transforming it into a comprehensive educational tool. While acknowledging the challenges and ethical implications surrounding the use of such AI models in education, we advocate for a balanced approach. The use of LLMs and chatbots in graduate education can be greatly beneficial but requires ongoing evaluation and adaptation to ensure ethical and efficient use.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
