The mechanisms of peer feedback strategies in facilitating deep learning for university students in virtual exhibition environments - Wu, Xinyi; Zhao, Miaomiao (Frontiers in Education, 2025)
IntroductionIn recent years, virtual venue technology has been increasingly adopted in higher education. While existing studies indicate that feedback strategies can promote deep learning among college students in virtual environments, the specific mechanisms underlying this effect remain poorly understood. This study investigates how peer feedback strategies influence deep learning processes within virtual learning environments.MethodsThe study employed the ErgoLAB Environment Synchronous Cloud Platform V3.0 alongside questionnaire scales to collect multimodal data, including behavioral patterns, physiological responses (eye movements, EEG, and electrodermal activity), learning experience metrics, and deep learning outcomes.ResultsAnalysis revealed significant differences in deep learning outcomes across peer feedback strategies. The peer dialogue feedback group operating in a basic virtual interaction environment outperformed the other three experimental groups, suggesting that structured peer dialogue combined with foundational virtual interactions may most effectively support deep learning.DiscussionThe findings underscore the importance of deliberately designed peer feedback strategies to enhance deep learning in virtual educational contexts. This study addresses the need for targeted feedback interventions in virtual instruction and offers empirical evidence for the integration of virtual venues into academic curricula. It also provides practical insights for fostering innovative talent development in the context of digital transformation in higher education.