ChatGPT/生成式人工智能促进以知识点为核心的教学模式变革研究

doi:10.16382/j.cnki.1000-5560.2023.07.016

华东师范大学学报(教育科学版) ›› 2023, Vol. 41 ›› Issue (7): 177-186.doi: 10.16382/j.cnki.1000-5560.2023.07.016

• 学习科学与教学变革 • 上一篇

ChatGPT/生成式人工智能促进以知识点为核心的教学模式变革研究

陈静远^1,², 胡丽雅¹, 吴飞^1,²

1. 浙江大学计算机科学与技术学院，杭州 310027
2. 浙江大学上海高等研究院，上海 201203

出版日期:2023-07-01 发布日期:2023-06-25
基金资助:
国家自然科学基金重点项目（62037001）；上海市“科技创新行动计划”启明星项目（23QA1409000）；浙江大学繁星科学基金（SN-ZJU-SIAS-0010）；浙江大学研究生教育研究课题项目（20210321）

Investigation into the Transformation of Knowledge-Centered Pedagogy with ChatGPT/Generative AI

Jingyuan Chen^1,², Liya Hu¹, Fei Wu^1,²

1. College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
2. Shanghai Institute for Advanced Study of Zhejiang University, Shanghai 201203, China

Online:2023-07-01 Published:2023-06-25

摘要/Abstract

摘要：

本文研究了ChatGPT/生成式人工智能在以知识点为核心的教学模式下的变革作用。作为一种语言生成模型，ChatGPT通过对海量语言数据的学习，能够挖掘单词间的共生关联关系，具备深入的语言理解和组合创新能力。然而在教育领域中，ChatGPT存在过度依赖训练数据、逻辑推理能力弱和新场景处理能力有限等局限性。为了提高ChatGPT在教学场景下生成内容的准确性和针对性，本文提出将ChatGPT与以知识点为核心的教学资源组织方式进行有机结合，通过形成知识点结构图等方式对ChatGPT进行完善，同时提供了几种具体可行的使用ChatGPT辅助教师和学生的方式。最后，本文还探讨了如何将Prompt研究范式与以知识点为核心的教学模式相结合，帮助ChatGPT建立“知识体系”，从而形成一个数据和知识双轮驱动的教育场景的语言生成模型，为教育领域提供更智能化、个性化的服务，推动教育领域的发展和变革。

关键词: ChatGPT, 生成式人工智能；大型语言模型, 知识点, 教学资源组织, 个性化教学

Abstract:

This paper explores the transformative role of ChatGPT in the teaching mode centered on knowledge concepts. As a language generation model, ChatGPT is capable of in-depth language comprehension and innovative combinations by mining the symbiotic relationships between words through massive language data learning. However, in the field of education, ChatGPT faces limitations such as over-reliance on training data, weak logical reasoning ability, and limited ability to handle new scenarios. To overcome these limitations and enhance the accuracy and relevance of ChatGPT’s generated content, this paper proposes an organic combination of ChatGPT with the organization of teaching resources centered on knowledge concepts, and improve ChatGPT by creating structure diagrams of knowledge concepts. Additionally, several specific and feasible ways to assist teachers and students using ChatGPT are also proposed. Finally, this paper discusses how to combine the prompt research paradigm with the teaching mode centered on knowledge concepts to help ChatGPT establish a “knowledge system”. This will enable ChatGPT to become a language generation model driven by both data and knowledge, providing more intelligent and personalized services in the education field, and promoting its development and transformation.

Key words: ChatGPT, AIGC; large language model, knowledge concept, teaching resource organization, personalized learning

陈静远, 胡丽雅, 吴飞. ChatGPT/生成式人工智能促进以知识点为核心的教学模式变革研究[J]. 华东师范大学学报(教育科学版), 2023, 41(7): 177-186.

Jingyuan Chen, Liya Hu, Fei Wu. Investigation into the Transformation of Knowledge-Centered Pedagogy with ChatGPT/Generative AI[J]. Journal of East China Normal University(Educational Sciences), 2023, 41(7): 177-186.

图/表 3

参考文献 0

	机器之心. (2023). 史上增速最快消费级应用, ChatGPT月活用户突破1亿. 取自: https://mp.weixin.qq.com/s/ahUJrwTgXJhc0Gc7CYG_7w.
	吴飞, 陈为, 孙凌云, 肖俊以知识点为中心建设AI+X微专业科教发展研究 2023 3 1 吴飞, 陈为, 孙凌云, 肖俊. (2023). 以知识点为中心建设AI+X微专业. 科教发展研究,3(1).
	Keskar, N. S., McCann, B., Varshney, L. R., Xiong, C., & Socher, R. (2019). Ctrl: A conditional transformer language model for controllable generation. arXiv preprint arXiv: 1909.05858.
	Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing ACM Computing Surveys 2023 55 9 1 35 Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2023). Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing. ACM Computing Surveys, 55(9), 1—35.
	Liu, X., Zhang, F., Hou, Z., Mian, L., Wang, Z., Zhang, J., & Tang, J Self-supervised learning: Generative or contrastive IEEE Transactions on Knowledge and Data Engineering 2021 35 1 857 876 Liu, X., Zhang, F., Hou, Z., Mian, L., Wang, Z., Zhang, J., & Tang, J. (2021). Self-supervised learning: Generative or contrastive. IEEE Transactions on Knowledge and Data Engineering, 35(1), 857—876.
	Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., ... & Sutskever, I. (2021, July). Learning transferable visual models from natural language supervision. In International conference on machine learning (pp. 8748−8763). PMLR.
	Schulman, J., B. Zoph, C. Kim, J. Hilton, J. Menick, J. Weng, J. F. C. Uribe et al. (2022) “ChatGPT: Optimizing language models for dialogue.”
	Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017). Attention is all you need. Advances in neural information processing systems, 30.
	Wu, L. L., & Barsalou, L. W Perceptual simulation in conceptual combination: Evidence from property generation Acta psychologica 2009 132 2 173 189 Wu, L. L., & Barsalou, L. W. (2009). Perceptual simulation in conceptual combination: Evidence from property generation. Acta psychologica, 132(2), 173—189. doi: 10.1016/j.actpsy.2009.02.002
	Wei, J., Wang, X., Schuurmans, D., Bosma, M., Chi, E., Le, Q., & Zhou, D. (2022). Chain of thought prompting elicits reasoning in large language models. arXiv preprint arXiv: 2201.11903.

[1]	朱永新, 杨帆. ChatGPT/生成式人工智能与教育创新：机遇、挑战以及未来[J]. 华东师范大学学报(教育科学版), 2023, 41(7): 1-14.
[2]	陈玉琨. ChatGPT/生成式人工智能时代的教育变革[J]. 华东师范大学学报(教育科学版), 2023, 41(7): 103-116.
[3]	顾小清, 胡艺龄, 郝祥军. AGI临近了吗：ChatGPT热潮之下再看人工智能与未来教育发展[J]. 华东师范大学学报(教育科学版), 2023, 41(7): 117-130.
[4]	张治. ChatGPT/生成式人工智能重塑教育的底层逻辑和可能路径[J]. 华东师范大学学报(教育科学版), 2023, 41(7): 131-142.
[5]	蒋里. AI驱动教育改革：ChatGPT/GPT 的影响及展望[J]. 华东师范大学学报(教育科学版), 2023, 41(7): 143-150.
[6]	余南平, 张翌然. ChatGPT/生成式人工智能对教育的影响：大国博弈新边疆[J]. 华东师范大学学报(教育科学版), 2023, 41(7): 15-25.
[7]	倪闽景. 从学习进化的视角看ChatGPT/生成式人工智能对学习的影响[J]. 华东师范大学学报(教育科学版), 2023, 41(7): 151-161.
[8]	贺樑, 应振宇, 王英英, 孙文琪. 教育中的ChatGPT：教学能力诊断研究[J]. 华东师范大学学报(教育科学版), 2023, 41(7): 162-176.
[9]	郑金洲. 重构课堂[J]. 华东师范大学学报(教育科学版), 2001, 19(3): 53-63.

ChatGPT/生成式人工智能促进以知识点为核心的教学模式变革研究

Investigation into the Transformation of Knowledge-Centered Pedagogy with ChatGPT/Generative AI

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

图/表 3

参考文献 0

相关文章 9

编辑推荐

Metrics

本文评价