Augmented Learning for Joint Creativity in Human-GenAI Co-Creation

Our research introduces a novel theory of augmented learning by reconceptualizing the concept and providing both theoretical insights and empirical evidence to explain its role in human-generative artificial intelligence (GenAI) co-creation for enhancing joint creativity over time. We propose shifting the focus of augmented learning from traditional human cognitive learning to a collective learning process, where humans and GenAI collaboratively rearrange their levels of involvement in co-creation activities to continuously improve joint creativity over time. To examine this reconceptualized augmented learning, we adopted a mixed-methods approach across three studies. Studies 1 and 2 inductively revealed that human-GenAI co-creation does not automatically achieve augmented learning or enhance their joint creativity even after multiple rounds of co-creation experiences. A deeper qualitative analysis of human-GenAI dialogues identified a decline in Idea Co-Development—a co-creation activity characterized by feedback exchanges and iterative idea refinement—as the primary reason for this failure. Based on this finding, Study 3 deductively demonstrated that providing instructions and guidance on Idea Co-Development improved joint creativity over time. Building on these findings, we further refine our theory of augmented learning, offering actionable insights for improving human-GenAI co-creation to achieve greater joint creativity.

History: Min Ding, Ram Gopal, Ulrike Schultz, D. J. Wu, Senior Editors; Mingfeng Lin, Associate Editor.

Funding: This work was supported by the Jesse H. Jones Graduate School and Virani Undergraduate School of Business at Rice University, Cambridge Judge Business School, and the Tony Cowling Foundation [Research Award CFA23-03].

Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2024.0984.