Metaverse Classrooms Boost Hospitality Students’ Learning Without Extra Mental Strain

When the pandemic forced classrooms online, one of the most persistent complaints from students and teachers alike was that video-conference learning felt flat, isolating, and cognitively draining. A new quasi-experimental study from Taiwan now offers some of the most concrete evidence yet that a metaverse-style platform can do better. Writing in the journal Current Psychology, Chung-Jen Wang of National Pingtung University of Science and Technology reports that hospitality students who attended online lessons in a spatial, game-like virtual campus learned significantly more than peers taught the same material over Google Meet, and, crucially, they did so without any increase in cognitive load, the mental effort demanded by the learning environment itself.

The research focused on a course that would seem an unlikely candidate for virtual worlds: Hospitality Cost Control, a subject rooted in numbers, recipes, and profit margins rather than flashy simulations. Yet Wang argued that the way students encounter that content matters as much as the content itself. Conventional video platforms present a grid of faces and a shared screen, a format that can flatten the social cues and spontaneous interactions that make classroom learning feel alive. Metaverse platforms such as Gather.Town take a different approach, rendering a two-dimensional pixel-art campus through which students move avatars, walk into virtual rooms, and trigger video and audio connections only when their avatars stand near classmates or instructors. The result is a hybrid of video conferencing and a video game that mimics the spatial logic of a real building.

To test whether that spatial logic translates into better learning, Wang recruited two intact classes of Hospitality Cost Control students at a university in southern Taiwan, a total of 96 participants. Forty-six students formed the control group, receiving their online instruction through Google Meet, while fifty students formed the treatment group, learning in Gather.Town. The design was deliberately conservative. Both groups began with the same face-to-face instruction phase and sat the same midterm examination, which served as a pretest to establish a baseline. Only then, during weeks eleven through seventeen of the semester, did the groups diverge into their respective online formats. At the end of the term, all students took a final exam and completed a cognitive load assessment, while the metaverse group additionally answered a survey based on the Unified Theory of Acceptance and Use of Technology, a widely used framework known as UTAUT.

The outcome on achievement was clear. Students taught in the metaverse environment scored significantly higher on the final examination than their counterparts in the video-conference group, even after accounting for their midterm baseline. In practical terms, the virtual campus did not merely make online lessons more entertaining; it measurably improved how much cost-control knowledge students retained and applied. Just as important was what the study did not find. The cognitive load assessment showed that the richer, more interactive environment did not impose a heavier mental burden. That distinction matters, because educational technologists have long worried that immersive platforms, for all their appeal, can overwhelm learners with novelty, navigation, and interface management, leaving less working memory available for the actual subject matter. The Taiwanese results suggest that a well-designed metaverse classroom can add engagement without adding strain.

The second half of the study tackled a different question: why do students embrace or reject such platforms? Here Wang turned to UTAUT, the model developed by Venkatesh and colleagues in 2003 that has become a workhorse of technology-adoption research. UTAUT proposes that four constructs shape a person’s intention to use a new technology: performance expectancy, the belief that the tool will improve one’s performance; effort expectancy, the belief that it will be easy to use; social influence, the sense that important others expect one to use it; and facilitating conditions, the perception that infrastructure and support are available. Behavioral intention, in turn, is expected to drive actual use behavior, moderated by the resources and support at hand.

Using structural equation modeling, a statistical technique that tests networks of hypothesized relationships among latent variables simultaneously, Wang found that all four UTAUT antecedents exerted significant positive influences on the hospitality students’ behavioral intention to keep using the metaverse platform. Students who believed Gather.Town would help them learn, who found it easy to navigate, who felt encouraged by peers and instructors, and who perceived adequate technical support were all more likely to intend to use it. The model then showed that facilitating conditions and behavioral intention together significantly predicted actual use behavior. In other words, wanting to use the platform was not enough on its own; students also needed the practical scaffolding of reliable equipment, connectivity, and institutional backing to convert intention into genuine engagement.

These findings arrive at a moment when the hospitality and tourism industries are themselves experimenting with virtual worlds, from virtual hotel tours to metaverse-based destination marketing, and when hospitality educators face pressure to prepare students for technology-rich workplaces. Prior research has documented growing interest in metaverse applications across hospitality and tourism, but rigorous classroom experiments comparing metaverse instruction against standard video conferencing have remained scarce. By anchoring the comparison in a real course, with intact classes, a pretest, a posttest, and a validated adoption model, the study offers a template that other institutions can adapt. It also speaks to the broader debate about post-pandemic online learning, where the question is no longer whether to teach online but how to do so without sacrificing the social and spatial richness of campus life.

The cognitive load result deserves particular attention from instructional designers. Cognitive load theory holds that working memory is a limited resource and that learning suffers when extraneous load, the mental effort imposed by the interface rather than the content, grows too large. Many immersive technologies flunk this test, dazzling students while burying the lesson. Gather.Town’s design, which layers video conferencing onto a simple, navigable map, appears to hit a sweet spot: it supplies spatial presence and serendipitous interaction, the ingredients missing from grid-based calls, while keeping the controls intuitive enough that students do not burn mental bandwidth figuring out where to click. The UTAUT results echo this interpretation, since effort expectancy emerged as a significant driver of intention, suggesting that ease of use was not a barrier for this cohort.

The study is not without boundaries. It involved two classes at a single university in southern Taiwan, all studying one hospitality subject, so generalizing to other disciplines, cultures, or platform designs requires caution. The treatment group alone completed the UTAUT survey, meaning the adoption analysis rests on fifty respondents and describes users of one specific metaverse platform rather than metaverse instruction in general. The quasi-experimental design, while strengthened by the midterm pretest and intact-class structure, cannot match the causal purity of randomized assignment. Wang also notes that the datasets generated during the study are available from the corresponding author upon reasonable request, and the research received ethical approval from the National Cheng Kung University Human Research Ethics Committee, with written informed consent obtained from all participants.

Even with those caveats, the implications are hard to ignore. Higher education invested heavily in video-conference teaching during the pandemic and has largely reverted to it as the default online format, yet student dissatisfaction with that format is well documented. This study suggests that the next generation of online instruction may look less like a conference call and more like a campus, a persistent virtual space where students wander, bump into classmates, and learn by moving through an environment rather than staring at a grid. For hospitality educators, whose field depends on spatial service, atmosphere, and human interaction, the metaverse may be an especially natural fit. For everyone else, the Taiwanese experiment offers a measured but provocative data point: the technology that students accept, and that genuinely lightens rather than loads their minds, may be the one that finally makes online learning feel less like a workaround and more like a place.

Subject of Research: Metaverse-based online instruction and technology acceptance in higher education hospitality training

Article Title: Metaverse adoption in hospitality education: using the UTAUT framework for online instruction environments

Article References: Metaverse adoption in hospitality education: using the UTAUT framework for online instruction environments. (n.d.). https://doi.org/10.1007/s12144-026-10142-4

Image Credits: AI Generated

DOI: 10.1007/s12144-026-10142-4

Keywords: metaverse, UTAUT, hospitality education, online instruction, Gather.Town, cognitive load, learning achievement, technology acceptance, structural equation modeling, higher education, virtual learning environments, Current Psychology