Examining human–AI collaboration in hybrid intelligence learning environments: insight from the Synergy Degree Model

Xinmei Kong, Haiguang Fang (), Wenli Chen, Jianjun Xiao and Muhua Zhang
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Xinmei Kong: Capital Normal University
Haiguang Fang: Capital Normal University
Wenli Chen: Nanyang Technological University
Jianjun Xiao: Beijing Normal University
Muhua Zhang: Capital Normal University

Palgrave Communications, 2025, vol. 12, issue 1, 1-14

Abstract: Abstract The integrating AI into teaching and learning has the potential to transform traditional classroom environments into hybrid intelligence learning environments, whereby human teachers and AI teachers (educational robots) work together synergistically to enhance students’ learning processes and outcomes. To understand and optimize the synergistic effect of human–AI collaboration in hybrid intelligence learning environments, this study proposes a human–AI synergy degree model (HAI-SDM). A case study was conducted to examine the synergy degree and order degree in human–AI collaboration, involving forty students and one teacher from a class in a junior high school. The results indicate that the order degree between human teacher and AI machines remains at a moderate level while undergoing dynamic changes. The synergy degree fluctuates between low and moderate, reflecting relatively orderly development among the three subsystems (collaboration subject subsystem, collaboration process subsystem and collaboration environment subsystem), but one subsystem may exhibit disordered behaviours in contrast to the others. These findings have implications for developing more effective human-AI classroom collaboration and promoting the effective integration of AI into teaching and learning.

Date: 2025
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DOI: 10.1057/s41599-025-05097-z

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