The problem, the authors contend, begins with how immersion is conceptualized. VR studies across memory, attention, and executive functions have reported effects ranging from robust improvements to complete null findings. Differences in participant characteristics, intervention intensity, and task design explain part of this inconsistency, but they do not address a deeper issue: the same immersive feature that provides task-relevant support in one intervention can impose unnecessary demands in another. Navigation, spatial orientation, interface management, and even physical discomfort can consume cognitive resources that would otherwise serve the primary task. Cognitive benefit, the authors argue, cannot be inferred from engagement alone; it depends on whether task-relevant support outweighs task-irrelevant processing demands.

At the heart of the argument are two experiential constructs central to immersive VR: presence and agency. Presence is the subjective sense of being there in a mediated environment, while agency is the capacity for meaningful action with contingent feedback. Together, they can strengthen task-relevant processing by embedding cognition within interactive, spatially structured contexts. But the authors emphasize that these constructs must be measured separately, because presence without agency may produce absorption without task-relevant action, whereas agency without presence resembles little more than a conventional interactive display. Neither alone guarantees that the cognitive process being targeted is actually being exercised.

The researchers organize their argument around three propositions. First, immersion is conditional: it supports performance only when its task-relevant contribution exceeds the extraneous load it adds. Second, immersion is directional: a feature’s effect depends on its alignment with the targeted process. Spatial organization, for example, may support spatial encoding but divert resources when incidental to the mechanism being trained. Third, immersion can either scaffold or substitute for cognition, thereby shaping transfer. Cues, prompts, and feedback support learning when they preserve task-relevant challenge, but they can produce nontransferable gains when they perform the learner’s cognitive work rather than strengthen internal control.

To operationalize these ideas, the team proposes a two-dimensional decision matrix defined by immersive engagement and resource cost. Engagement reflects the joint contribution of presence and agency, while resource cost includes extraneous cognitive load and physiological discomfort such as cybersickness. Crucially, the effort required to exercise the target process is not counted as a cost—it is part of the intended training demand. Navigation, interface management, or irrelevant environmental complexity becomes costly only when it competes with that demand. The matrix yields four quadrants with distinct, testable predictions. High engagement with low cost provides the strongest case for benefit, with the best prospects for mechanism-relevant performance, transfer, and maintenance. High engagement with high cost may support immediate gains but is expected to yield weaker or less consistent transfer, along with greater fatigue, discomfort, or attrition. Low engagement with low cost should add little beyond a matched nonimmersive condition, while low engagement with high cost is the least favorable combination, adding burden without task-relevant immersive support.

The framework’s implications become concrete when applied to specific cognitive domains. In memory research, the comparison condition and the outcome measured matter enormously. One study found better recall with an immersive virtual memory palace than with a desktop version, yet a randomized controlled trial in older adults with subjective memory complaints found no added transfer benefit of immersive VR practice after method-of-loci training relative to an active VR control. These findings are not contradictory, the authors note: VR may outperform a less immersive format yet add little beyond an effective mnemonic strategy already in place. What counts as benefit depends on what VR is compared with and whether the outcome reflects trained-task performance, transfer, or long-term maintenance.

Mechanistically, immersive VR is most likely to support memory when its spatial and sensorimotor features strengthen context-dependent encoding. A virtual memory palace may improve recall by linking items to distinct locations, and presence may enhance encoding when those cues are salient and task-relevant. But the same spatial features can become costly when navigation or environmental complexity is incidental to encoding and consumes working memory without supporting retention. Because such encoding is context-dependent, near transfer—improvement on tasks resembling the trained task—is the most plausible outcome. Ecological transfer, meaning improvement in real-world functioning, becomes plausible only when training cues map onto real-world contexts, while far transfer and long-term maintenance require direct evidence.

The attentional and executive control domain illustrates similar tensions. Immersive tasks can embed planning, inhibition, updating, and reorientation within naturalistic, multi-step scenarios—a virtual grocery task, for instance, can require route planning, inhibition of distractions, goal updating, and reorientation as conditions change. Some evidence supports the potential: one study found greater gains in inhibition and task switching among adults aged 50 and older when the same exercise game was delivered in an immersive rather than nonimmersive format, with presence mediating these effects. An exploratory study of young adults reported improvements in selective attention and inhibition after VR exergaming, whereas video exercise produced no such gains. In contrast, another study found that immersive 360-degree presentation increased presence and arousal but actually impaired focused attention and recall relative to screen presentation. Together, these findings suggest that immersion can support selected control processes when task demands engage them, but effects are process-specific and depend heavily on the comparison condition; greater experiential intensity alone does not establish stronger attentional-executive control.

The authors also draw on established theory to sharpen their framework. The Cognitive Affective Model of Immersive Learning, or CAMIL, explains how immersive affordances influence learning, but training performance can improve without durable learning or capacity change. For capacity training, this dissociation is critical: a feature that makes a task easier may raise performance while removing the very cognitive work the intervention is meant to strengthen. The researchers therefore extend CAMIL with three intervention-specific requirements: immersive features should align with the target mechanism, require users to exercise rather than offload that process, and produce benefits beyond VR-supported performance. Embodied cognition helps identify when sensorimotor engagement is mechanism-relevant, while cognitive load theory helps identify when immersive demands are extraneous.

Ultimately, the authors call for a new standard of evidence in immersive cognitive research. Future studies should manipulate specific immersive features using active comparisons matched for task content and expectancy; measure experiential engagement, resource costs, mechanism-specific cognition, and outcomes within the same study; preregister moderator hypotheses concerning age, baseline capacity, task alignment, and cybersickness susceptibility; and distinguish immediate performance from near, ecological, and far transfer as well as delayed maintenance, with transparent attrition reporting. These standards move the field from asking whether VR is broadly beneficial to testing when, for whom, and through which mechanisms immersion produces durable cognitive change. They also make negative or mixed findings more informative, because they help identify whether a weak effect reflects poor mechanism alignment, excessive cost, population-specific vulnerability, or inadequate transfer assessment rather than a generic failure of VR. On these terms, immersion is not a guarantee of benefit but a design parameter whose value must be demonstrated—mechanism by mechanism, population by population.

Subject of Research: Distinguishing cognitive change from VR-supported performance in immersive cognitive training

Article Title: Beyond immersion: distinguishing cognitive change from VR-supported performance

Article References: Yang, H., Kho, H., Tay, C. P. E., & Eun, Z. K. Y. (2026). Beyond immersion: distinguishing cognitive change from VR-supported performance. Frontiers in Virtual Reality, 7, Article 1815501. https://doi.org/10.3389/frvir.2026.1815501

Image Credits: AI Generated

DOI: 10.3389/frvir.2026.1815501

Keywords: virtual reality, cognitive training, presence, agency, cognitive load, transfer of learning, memory, executive function, cybersickness, immersive learning, CAMIL, neuroscience