This study examined how task complexity and self-regulated learning (SRL) support strategies relate to learners’ cognitive load and emotional engagement in a Metaverse Learning Environment (MLE) using multimodal indicators. College students ( N = 42) completed three game-embedded tasks of low, mid, and high complexity while receiving cognitive-regulated support (CS), motivational-regulated support (MS), or no additional support (control group, CG). Learners’ cognitive and emotional engagement were assessed using self-reported mental effort and multimodal measures for process approaches, an EEG-derived mental workload index (beta/[alpha + theta]), frontal alpha asymmetry (FAA), and facial expression analysis (FEA) metrics of task-facing orientation and engagement. Task complexity showed robust but non-monotonic effects across modalities. The mid-complexity task elicited higher EEG workload and emotional engagement than the low- and high-complexity tasks, whereas task-facing orientation was lower in the high-complexity task than in the low- and mid-complexity tasks. FAA was also higher in the mid-complexity task than in the high-complexity task. SRL support strategies were modality-specific: the control group reported higher mental effort than the CS group, and the CS group showed higher expressive engagement than both the MS and CG groups during the mid-complexity task. These findings suggest that cognitive support may reduce subjective strain while sustaining emotional involvement under moderate challenge. More broadly, the results highlight the value of multimodal measurement for distinguishing perceived effort from physiological and behavioral indicators of learner experience in immersive learning environments.

The split-attention principle suggests that separating onscreen information sources can overburden working memory and impede learning. While research has traditionally focused on the separation of images and text, relatively little is known about the impact of multiple simultaneous visual inputs. This study examined the split-attention principle in a multimedia environment featuring a pedagogical agent performing gestures, with hologram-like images either integrated centrally with the agent or spatially separated. A within-subjects design (N = 80) investigated the impact on satisfaction, cognitive load, and cued recall. The quantitative findings revealed no significant differences between the two spatial conditions. Preliminary qualitative insights from a limited sample of six individual interviews suggested that some participants may employ strategies to simplify complex designs and manage perceived cognitive load. Based on these limited qualitative observations, this research tentatively proposes the “pruning principle”, a metacognitive strategy where learners actively “prune” extraneous information to optimize cognitive resources. These findings underscore the importance of considering individual differences and metacognitive strategies in multimedia design.