用生成式人工智能工具共同构建知识:基于CSCL视角的思考

IF 4.2 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH International Journal of Computer-Supported Collaborative Learning Pub Date : 2023-10-20 DOI:10.1007/s11412-023-09409-w
Ulrike Cress, Joachim Kimmerle
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引用次数: 0

摘要

生成式人工智能(AI)工具,如ChatGPT,受到了研究者、媒体和公众的极大关注。它们被许多人乐于并经常用于文本生产。这些工具有不可否认的优势,但也有必须解决的弱点。在这篇短文中,我们要问的是,这些工具在多大程度上可以被用户用于个人学习,以及用于知识构建,以激发开发新见解的集体努力。我们以社会的、集体的知识概念为基础,认为用户需要建立一种超越知识讲述(简单地写下自己所知道的)并激发知识转化(将知识转化为复杂的关系论证结构)的对话。生成式人工智能工具没有任何概念知识或有意识的理解,因为它们只使用单词转换并依赖于词类的概率。然而,我们建议,人类和人工智能工具之间的辩论对话可以通过适当的提示来实现,其中可以发生联合知识构建的紧急过程。基于这一假设,我们探讨了人类和人工智能在交流和文本生产中的作用。对于我们的论点,我们借鉴了对个人和合作写作、群体认知以及认知和社会系统共同进化的研究。我们概述了未来CSCL的研究路径,这些路径可能会在术语、理论和方法方面考虑到人类与人工智能共同构建知识。
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Co-constructing knowledge with generative AI tools: Reflections from a CSCL perspective
Abstract Generative Artificial Intelligence (AI) tools, such as ChatGPT, have received great attention from researchers, the media, and the public. They are gladly and frequently used for text production by many people. These tools have undeniable strengths but also weaknesses that must be addressed. In this squib we ask to what extent these tools can be employed by users for individual learning as well as for knowledge construction to spark a collective endeavor of developing new insights. We take a social, collective notion of knowledge as a basis and argue that users need to establish a dialog that goes beyond knowledge telling (simply writing what one knows) and stimulates knowledge transformation (converting knowledge into complex relational argumentation structures). Generative AI tools do not have any conceptual knowledge or conscious understanding, as they only use word transitions and rely on probabilities of word classes. We suggest, however, that argumentative dialogs among humans and AI tools can be achieved with appropriate prompts, where emergent processes of joint knowledge construction can take place. Based on this assumption, we inquire into the human and into the AI parts of communication and text production. For our line of argument, we borrow from research on individual and collaborative writing, group cognition, and the co-evolution of cognitive and social systems. We outline future CSCL research paths that might take the human-AI co-construction of knowledge into account in terms of terminology, theory, and methodology.
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来源期刊
CiteScore
8.00
自引率
18.60%
发文量
20
期刊介绍: An official publication of the International Society of the Learning Sciences, the International Journal of Computer-Supported Collaborative Learning (IJCSCL) fosters a deep understanding of the nature, theory, and practice of computer-supported collaborative learning (CSCL). The journal serves as a forum for experts from such disciplines as education, computer science, information technology, psychology, communications, linguistics, anthropology, sociology, and business. Articles investigate how to design the technological settings for collaboration and how people learn in the context of collaborative activity.
期刊最新文献
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