ChatGPT for Education and Research: Opportunities, Threats, and Strategies

被引:367
作者
Rahman, Md. Mostafizer [1 ,2 ]
Watanobe, Yutaka [2 ]
机构
[1] Dhaka Univ Engn & Technol, Gazipur 1707, Bangladesh
[2] Univ Aizu, Dept Comp Sci & Engn, Aizu Wakamatsu 9658580, Japan
来源
APPLIED SCIENCES-BASEL | 2023年 / 13卷 / 09期
基金
日本学术振兴会;
关键词
ChatGPT; educational technology; research; programming education; large language model; GPT-3; ChatGPT survey; GPT-4; artificial intelligence; AI for code;
D O I
10.3390/app13095783
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
In recent years, the rise of advanced artificial intelligence technologies has had a profound impact on many fields, including education and research. One such technology is ChatGPT, a powerful large language model developed by OpenAI. This technology offers exciting opportunities for students and educators, including personalized feedback, increased accessibility, interactive conversations, lesson preparation, evaluation, and new ways to teach complex concepts. However, ChatGPT poses different threats to the traditional education and research system, including the possibility of cheating on online exams, human-like text generation, diminished critical thinking skills, and difficulties in evaluating information generated by ChatGPT. This study explores the potential opportunities and threats that ChatGPT poses to overall education from the perspective of students and educators. Furthermore, for programming learning, we explore how ChatGPT helps students improve their programming skills. To demonstrate this, we conducted different coding-related experiments with ChatGPT, including code generation from problem descriptions, pseudocode generation of algorithms from texts, and code correction. The generated codes are validated with an online judge system to evaluate their accuracy. In addition, we conducted several surveys with students and teachers to find out how ChatGPT supports programming learning and teaching. Finally, we present the survey results and analysis.
引用
收藏
页数:21
相关论文
共 63 条
[11]  
Dai HX, 2023, Arxiv, DOI [arXiv:2302.13007, 10.48550/arXiv.2302.13007]
[12]  
Dehouche N., 2021, Ethics Sci. Environ Polit, V21, P17, DOI [DOI 10.3354/ESEP00195, 10.3354/esep00195]
[13]   ChatGPT for (Finance) research: The Bananarama Conjecture [J].
Dowling, Michael ;
Lucey, Brian .
FINANCE RESEARCH LETTERS, 2023, 53
[14]   Chat With ChatGPT on Intelligent Vehicles: An IEEE TIV Perspective [J].
Du, Haiping ;
Teng, Siyu ;
Chen, Hong ;
Ma, Jiaqi ;
Wang, Xiao ;
Gou, Chao ;
Li, Bai ;
Ma, Siji ;
Miao, Qinghai ;
Na, Xiaoxiang ;
Ye, Peijun ;
Zhang, Hui ;
Luo, Guiyang ;
Wang, Fei-Yue .
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (03) :2020-2026
[15]  
Elkins K., 2020, J CULTURAL ANAL, V5, P2, DOI [DOI 10.22148/001C.17212, 10.22148/001c.17212]
[16]   GPT-3: Its Nature, Scope, Limits, and Consequences [J].
Floridi, Luciano ;
Chiriatti, Massimo .
MINDS AND MACHINES, 2020, 30 (04) :681-694
[17]  
Frieder S, 2023, Arxiv, DOI [arXiv:2301.13867, 10.48550/arXiv.2301.13867, DOI 10.48550/ARXIV.2301.13867]
[18]  
Gao CA, 2022, bioRxiv, DOI [10.1101/2022.12.23.521610, 10.1101/2022.12.23.521610, DOI 10.1101/2022.12.23.521610V1, DOI 10.1101/2022.12.23.521610]
[19]  
Gilson A, 2022, medRxiv
[20]  
Jalil S, 2023, Arxiv, DOI arXiv:2302.03287