The Study on the Mechanism of Peer Feedback Strategies in Facilitating University Students' Deep Learning in Virtual Exhibition Environments

Xinyi Wu^*Miaomiao Zhao^*

• Dalian University, Dalian, China

In recent years, virtual venue technology has gained widespread application in higher education. Existing research has demonstrated that feedback strategies can facilitate college students' deep learning in virtual environments; however, the underlying mechanisms remain insufficiently explored. This study focuses on examining the effects of peer feedback strategies on deep learning processes within virtual learning environments for college students. The ErgoLAB Environment Synchronous Cloud Platform V3.0, combined with questionnaire scales, was employed to collect multimodal learning data, including behavioral patterns, physiological responses (eye movements, EEG, and electrodermal activity), learning experience metrics, and deep learning outcomes. Data analysis revealed significant variations in the effectiveness of different peer feedback strategies on deep learning outcomes. Notably, the peer dialogue feedback group in the basic virtual interaction environment exhibited superior performance compared to the other three experimental groups. These findings suggest that structured peer dialogue combined with fundamental virtual interactions may optimally facilitate students' deep learning processes. The results highlight the importance of carefully designed peer feedback strategies in enhancing deep learning within virtual educational settings. The present study contributes to addressing the need for precise feedback interventions in virtual teaching environments. Furthermore, it provides empirical support for the effective integration of virtual venues with academic curricula while offering valuable insights for improving innovative talent cultivation during the digital transformation of higher education institutions.