The Construction and Application of Prompt Framework for Improving College Students’ Human-Machine Synergy Learning Ability with Generative AI

Generative AI-supported human-machine synergy (HMS) learning is emerging as a new form of learning. Prompt, as the supporting scaffold, significantly impacts the synergy effects between learners and generative AI. To investigate the role of prompt framework in improving college students’ human-machine synergy learning ability (HMS learning ability), this study conducted the methods of literature research, theoretical deduction, and quasi-experimental research. Guided by the theories of distributed cognition, information processing and the cooperative principle of conversation, this study clarified the connotation and core dimensions of HMS learning ability, analyzed the HMS learning process with generative AI, explored the impact of prompt framework on college students’ human-machine synergy learning ability and finally, constructed the “GCRET” prompt framework to enhance college students’ human-machine synergy learning ability, and its effectiveness was verified through the Human-Machine Synergy Learning Ability Scale and students’ project practice report. According to the effect analysis, the constructed “GCRET” framework significantly enhanced college students’ HMS learning ability, especially HMS evaluation and judgment ability. The researchers hope that this study could provide theoretical and practical references for further exploring the HMS learning with generative AI.