Co-constructing knowledge with generative AI tools: Reflections from a CSCL perspective

Abstract

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.