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Complementary Functions and Potential of Generative AI in Algorithm Education
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作者 Guoqiang Li Yuxin Su 《计算机教育》 2023年第12期221-231,共11页
In today’s digital era,algorithms have become an indispensable part of our daily lives and work.Algorithm education plays a crucial role in computer science and software engineering,aiming to cultivate students’prob... In today’s digital era,algorithms have become an indispensable part of our daily lives and work.Algorithm education plays a crucial role in computer science and software engineering,aiming to cultivate students’problem-solving skills and computational thinking.However,traditional algorithm education often requires significant time and efforts from teachers,lacks interactivity,and provides limited examples.The rapid advancement of AI technology,particularly generative models,and large language models(LLMs),has the potential to revolutionize computer education.Models like OpenAI’s GPT-4 and ChatGPT have conversational capabilities and contribute to various aspects of computer education.GPT-3.5,as an assistant in algorithm education,assists teachers in automatically generating explanations and algorithmic examples to enhance students’understanding of algorithms.While existing research has certain limitations,such as focusing on specific scenarios and lacking comprehensive benchmark testing,this paper explores the role of ChatGPT(GPT-3.5)in algorithm education.By refining prompts and evaluating generative capabilities,the study demonstrates that GPT-3.5 holds significant potential as a teaching aid.With an average accuracy of 0.81.GPT-3.5 can generate explanations,code examples,and visualizations of the corresponding algorithms.Other tests including algorithm problem-solving and examples giving also prove the practicability of GPT-3.5 in algorithm education. 展开更多
关键词 ChatGPT Large language models Code generation AI education Computing education Algorithm education
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