Signaling feedback mechanisms to promoting self-regulated learning and motivation in virtual reality transferred to real-world hands-on tasks

Abstract

ABSTRACT Virtual reality (VR) provides a unique platform for interactive learning experiences, enhancing learning, particularly in hands-on courses. However, the visual load of VR and the lack of guidance and interaction from physical teachers or peers can pose challenges for learners in self-regulated learning (SRL) and learning motivation. This study designed feedback in the VR learning environment based on the signaling principles of Cognitive Theory of Multimedia Learning (CTML) to investigate learners’ SRL, learning motivation, cognitive levels, and their abilities to handle real-world scenarios. We developed a VR hands-on learning course on the Artificial Intelligence of Things (AIoT) and conducted two real-world AIoT hands-on tasks, implementing a quasi-experimental study with 71 university students. Participants were randomly assigned to either the experimental group or the control group. The experimental group received three types of feedback signals (gaze, progress, and decision) designed based on signaling principles, while the control group received no feedback. The results showed that the experimental group exhibited significantly higher levels of SRL and learning motivation compared to the control group after VR learning. The feedback group also performed better in terms of cognitive levels and real-world hands-on tasks.