The Evidence Is Here
Museums and science centers are investing heavily in immersive experiences, but when boards, funders, and granting agencies ask does this actually work?, professionals need more than anecdotal enthusiasm. They need evidence.
This white paper synthesizes three decades of peer-reviewed research on presence (the psychological state of feeling genuinely there inside a mediated environment) and its relationship to measurable learning outcomes. The evidence base includes foundational papers cited thousands of times, more than ten meta-analyses with quantifiable effect sizes, a dominant theoretical model published in a top-tier education journal, six validated measurement instruments, and a growing body of research conducted in museum and informal learning settings.
"Immersive technologies that generate high levels of presence consistently produce positive learning effects, moderated critically by the quality of instructional design surrounding the experience."
Presence is not a silver bullet; it is a catalyst. When paired with intentional design, it activates the same learning mechanisms that constructivism, experiential learning theory, and embodied cognition have long predicted.
The question is not whether immersive technology works. It is whether it is designed well. Funding proposals should emphasize the instructional design framework surrounding the experience, not just the technology itself.
Need to make the evidence-based case for immersive programming to your board or a granting agency? This white paper is free to cite, excerpt, and reference in proposals with attribution.
How to use this in a grant proposal →What Presence Is, and Why It Matters for Museums
Presence is not marketing jargon. It is a well-defined psychological construct with roots in telecommunications research, cognitive science, and educational theory.
At its most fundamental, presence refers to the subjective experience of being situated in an environment, of feeling that the mediated world is the real world, even when the rational mind knows otherwise. The formal study of presence began in 1980 when Marvin Minsky coined the term "telepresence." Through the 1990s, the concept matured rapidly.
In 1997, Lombard and Ditton published the landmark paper that synthesized prior research and proposed the most widely cited working definition: presence is the "perceptual illusion of nonmediation." In the same year, Slater and Wilbur drew a critical distinction that shapes the field to this day:
Slater later refined this framework into two distinct components: Place Illusion (the qualia of being in a real place, supported by sensorimotor contingencies) and Plausibility Illusion (the sense that depicted events are actually occurring, supported by narrative coherence).
Presence Is Not Just a VR Concept
A common misconception is that presence applies only to head-mounted virtual reality. Research demonstrates that presence operates across a spectrum of technologies, from large-format cinema to interactive galleries, planetarium domes to augmented reality overlays. Lee's explication refined presence into three core dimensions: physical presence, social presence, and self-presence.
"Presence is a design variable, not a technology purchase. Every exhibit exists somewhere on the presence continuum, and strategic design choices can move it higher."
How Presence Connects to Established Learning Theory
Presence is not a standalone idea. It is an integrating mechanism that activates learning processes already understood by educational psychologists.
Constructivism
Piaget and Vygotsky hold that learners actively construct knowledge through interaction with their environment. Garrison et al.'s Community of Inquiry framework explicitly builds on this, introducing "cognitive presence" as the extent to which learners construct meaning through reflection.
Experiential Learning
Kolb's experiential learning cycle depends on concrete experience as its entry point. Presence provides that concrete experience (the feeling of "being there") even when the environment is technologically mediated. The critical nuance is that experience must be paired with intentional design: structured reflection, clear narrative, and purposeful content scaffolding.
The SOI Framework
Mayer's Select-Organize-Integrate (SOI) model explains how meaningful learning works: learners must select relevant information, organize it into a coherent mental structure, and integrate it with prior knowledge. Presence amplifies motivation and information processing, but perceptual richness can also distract from the selecting and organizing stages if the experience is not well designed.
Embodied Cognition
Barsalou, Wilson, and Lakoff argue that thinking is grounded in sensorimotor experience. Biocca's progressive embodiment framework shows how increasing sensory coupling deepens presence, while Barsalou's perceptual symbol systems theory explains why simulated sensory experience affects cognitive processing.
Situated Learning
Lave and Wenger's situated learning theory argues that knowledge is inseparable from the context in which it is acquired. An exhibit that transports visitors to the surface of Mars or the deck of a Viking longship creates authentic contextual learning environments through presence.
Flow Theory
Csikszentmihalyi's concept of flow shares significant characteristics with presence: deep absorption, focused attention, altered time perception. They are independent but complementary constructs, and well-designed immersive exhibits can activate both simultaneously.
Immersive exhibits do not represent an untested pedagogical experiment. They operationalize learning theories validated over decades (constructivism, experiential learning, embodied cognition, and situated learning) through the well-studied mechanism of presence.
The Evidence-Based Pathway: The CAMIL Model
The single most important theoretical framework for understanding the presence-learning relationship is the Cognitive Affective Model of Immersive Learning (CAMIL), published by Makransky and Petersen in 2021 in Educational Psychology Review.
CAMIL maps a clear, evidence-based pathway from technology to learning, and resolves a critical question that museum professionals and funders are right to ask: if immersive technology is so engaging, why doesn't it always produce better learning?
The answer, validated by empirical research, is that the pathway from presence to learning is indirect and conditional. Presence creates the conditions for learning (heightened motivation, interest, emotional engagement), but those conditions must be channeled through appropriate instructional design.
The CAMIL model is the right framework, but only if your provider builds around it. Here's how every Hammer & Anvil experience is structured around this exact pathway.
See our approach to instructional design →What the Numbers Show: Meta-Analytic Evidence
Meta-analyses synthesize findings across many individual studies, providing the most reliable estimates of effect sizes. The immersive learning literature now includes more than ten meta-analyses spanning thousands of participants.
The consistent finding: a moderate-to-large positive effect, moderated by instructional design quality. By convention, an effect size of 0.2 is small, 0.5 is medium, and 0.8 is large. The range of 0.38 to 0.72 observed across these meta-analyses indicates moderate-to-substantial improvements, consistent across different research teams, journals, and populations.
| Study | Scope | Effect Size | Journal |
|---|---|---|---|
| Merchant et al. (2014) | 69 studies, N=8,432 | g = 0.41–0.51 | Computers & Education |
| Cummings & Bailenson (2016) | 83 studies, 115 effects | Significant positive | Media Psychology |
| Coban et al. (2022) | 48 studies, N=3,179 | g = 0.38 | Educational Research Review |
| Villena-Taranilla et al. (2022) | 21 studies, K-6 | ES = 0.64 | Educational Research Review |
| Zhou, Chen & Wang (2022) | 51 studies, museum-specific | Significant positive | Educational Research Review |
| Lin et al. (2023) | 70 studies, AR | g = 0.717 | Computer Applications in Eng. Education |
Zhou, Chen, and Wang (2022) is the only meta-analysis conducted specifically on AR/VR in museum learning environments. Reviewing 51 studies, they found significant positive effects on both academic achievement and learner perceptions. This is the essential citation for museum grant proposals.
Beyond the Headset: Evidence Across Immersive Formats
Head-mounted VR is only one tool. Many institutions use or are considering fulldome theaters, projection-mapped environments, immersive rooms, and augmented reality. The research supports these formats.
Yu and colleagues (2016) studied 781 undergraduates and found that students in immersive fulldome planetariums showed the greatest learning retention compared to identical content on flat screens. Jacobson's research at the Carnegie Museum of Natural History found dome displays produced significantly better factual recall than desktop displays, with a follow-up study demonstrating superior conceptual understanding as judged by domain experts.
Oh, Bailenson, and Welch's systematic review of 152 studies found that more immersive displays generally produce higher social presence. For museums, where learning is fundamentally social, shared immersive formats that support co-presence have distinct advantages over isolating head-mounted displays.
The evidence supports multiple immersive formats, not just VR headsets. Shared, group-based immersive experiences align more naturally with how museums function and how visitors learn.
Trying to decide which immersive format is right for your institution? We've designed ALICE to address the specific limitations this research identifies in individual HMD experiences.
Why we built a shared cinema format →Choosing What Belongs in VR: The DICE Framework
The medium works best when the content genuinely earns it. One of the most useful frameworks for evaluating content decisions comes from Jeremy Bailenson, founding director of Stanford University's Virtual Human Interaction Lab.
The DICE framework proposes that VR is best reserved for experiences that would otherwise be Dangerous, Impossible, Counterproductive, or Expensive to provide in the real world. A 2025 review of 30 years of VR psychology research in Nature Human Behaviour, co-authored by Bailenson, formalized this guidance: VR should be used selectively, in short doses, and for experiences where "being there" genuinely matters.
For museum and science center programming, this framework is clarifying. Immersive content that transports visitors to the deep ocean floor, the interior of a living cell, the surface of another planet, or a paleontological dig site in the Cretaceous period (experiences that are impossible, dangerous, or prohibitively expensive in the real world) represents an ideal use case. Content that merely replicates the experience of being in a museum, or delivers information that could be conveyed equally well through a flat screen, does not take full advantage of what the medium offers.
When evaluating immersive content for your institution, ask: does this experience genuinely require immersion to achieve its educational goal? VR as a transportation machine (taking visitors somewhere they could not otherwise go) consistently outperforms VR as a presentation format for information that could be conveyed in other ways. The content decision is as important as the technology decision.
This principle also has implications for visitor comfort and safety. VR is a transporting medium that commands full attention, which is precisely its strength. Short, purposeful, high-impact experiences consistently outperform longer sessions in both comfort and learning outcomes, which is why Hammer & Anvil experiences are designed to make every minute count. That finding directly informs how Hammer & Anvil experiences are produced and programmed.
Presence in the Museum Context
The dominant framework for understanding museum learning is Falk and Dierking's Contextual Model of Learning, validated with 217 adult visitors at a major science center.
This model describes learning as the interaction of three overlapping contexts: personal (prior knowledge, motivation, identity), sociocultural (group dynamics, cultural norms), and physical (architecture, design, sensory environment). Presence maps directly onto the physical context dimension. The sensory richness, spatial design, and environmental fidelity that drive presence are the same factors Falk and Dierking identify as shaping museum learning.
The Novelty Effect: A Real Concern with Known Solutions
Research confirms that novelty contributes to heightened initial responses. However, mitigation strategies are well-documented: pre-experience orientation, graduated introduction, and design for repeat engagement. A 2025 longitudinal study demonstrated that learning outcomes in VR environments improve as user familiarity grows.
Preparing Visitors for the Experience
A related and underappreciated factor is visitor preparation prior to entering an immersive environment. Research on VR user experience confirms that visitors arrive with varying levels of prior experience and different expectations, and that proper orientation significantly improves both the user experience and learning outcomes.
Effective preparation includes: explaining what the equipment looks like and how it works before the experience begins; communicating safety measures and what to do if discomfort occurs; ensuring headsets are correctly adjusted for individual users to avoid blurriness or physical discomfort; and where possible, offering a brief orientation or trial period before the substantive content begins. These practices reduce the cognitive overhead of managing unfamiliar technology, allowing visitors to direct their full attention to the content.
Visitor preparation is not merely a safety or logistics consideration. It is a pedagogical one. Visitors who are comfortable with the equipment and confident in what to expect engage more deeply with the content. Staff briefing protocols, clear pre-experience communication, and physical comfort checks are all part of the instructional design.
Institutional Recognition
The American Alliance of Museums convened an "Immersion in Museums" gathering in 2018, published evaluation frameworks for AR/VR in 2021, and hosted a Museum XR Summit in 2025. ICOM's 2022–2028 strategic plan includes digital transformation as a priority.
Measuring Presence: Validated Instruments
Grant proposals that reference measurable outcomes carry greater weight. The presence literature offers several validated psychometric instruments.
| Instrument | Structure | Reliability | Notes |
|---|---|---|---|
| Witmer & Singer PQ | 29–32 items | α = .88 | Most widely used; nearly 6,000 citations |
| iGroup IPQ | 14 items, 3 subscales | α = .87 | Freely available at igroup.org |
| Slater-Usoh-Steed | 6 items | Varies | Short; focused on "being there" |
| ITC-SOPI | 44 items, 4 factors | α = .76–.94 | Cross-media (works beyond VR) |
| Temple Presence Inventory | 8 subscales | Validated | Measures physical and social presence |
| Multimodal Presence Scale | CFA/IRT validated | Validated | Based on Lee's three-type framework |
No validated presence measure has been developed specifically for museum or informal learning contexts. This is both a limitation and an opportunity for institutions seeking research-focused funding. It's a strong angle for NSF AISL proposals.
Funding Pathways for Immersive Learning
Frame proposals around the CAMIL pathway, reference the meta-analytic effect sizes, and propose measurable evaluation using validated instruments. This positions the proposal as scientifically grounded, not speculative.
NSF Advancing Informal STEM Learning (AISL) is the primary federal program for museum-based immersive learning research.
IMLS Museums for America is the largest competitive federal grant program for museums, awarding over $23M in FY2024 across 115 projects (individual grants of $5,000–$350,000).
NEH Digital Projects for the Public and Digital Humanities Advancement Grants (up to $325,000) support virtual environments for public humanities engagement.
Knight Foundation has invested in arts and immersive technology since 2019, including five museum experiments totalling $750,000. Current programs include the Knight Arts + Tech Fellowship ($50,000 unrestricted grants to five artists annually) and the Art + Tech Expansion Fund.
The Wellcome Trust, NSF, and ESRC jointly funded the Science Learning+ program (£9 million) studying informal science learning in museums.
Horizon Europe Cluster 2 (Culture, Creativity, and Inclusive Society) funds cultural heritage research with approximately €60–70 million per work program.
Creative Europe MEDIA offers specific calls for immersive content development.
Lead with the CAMIL pathway (Section 3), reference the meta-analytic effect sizes (Section 4), and propose measurable evaluation using validated instruments (Section 7).
Emphasize the instructional design framework surrounding the experience, not the technology itself. Funders have grown sophisticated about hardware-led proposals.
Working on an IMLS, NSF, or NEH proposal? We can help you frame the immersive exhibit component using the research language and effect sizes that granting agencies respond to.
Talk to our team →What the Research Doesn't Claim, and Why That Matters
Credible research acknowledges its boundaries, and doing so is precisely what distinguishes rigorous evidence from vendor claims. None of the limitations below diminish the core finding: well-designed immersive experiences consistently produce positive learning outcomes.
- The methodological quality of the evidence base varies. A 2024 systematic review by colleagues at UCSB examined 38 media comparison studies involving immersive VR in STEM education and found that only 26% were fully controlled with regard to instructional method and content. The remainder differed on at least one control criterion, meaning that in many studies, differences in learning outcomes may reflect instructional design choices rather than the medium itself. This does not invalidate the overall evidence base, but it does mean that effect sizes from meta-analyses should be interpreted as upper-bound estimates, and that the strongest conclusions come from the better-controlled studies. The field is actively improving: "value-added" designs that hold the medium constant while varying one specific instructional feature are becoming more prevalent and provide more precise guidance for practitioners.
- The presence-learning relationship is mediated, not direct. Research does not support a simple "presence causes learning" claim. The pathway runs through motivation, interest, embodiment, and self-regulation, all of which are shaped by instructional design quality. This is a feature of the evidence, not a weakness: it tells us precisely where to invest effort for maximum impact.
- Definitional debates persist. Skarbez, Brooks, and Whitton (2017) noted no widespread agreement on defining presence. The Slater framework and CAMIL model provide increasingly precise definitions, but the field has not fully converged.
- Most studies use formal education settings. University students in labs differ from museum visitors (free-choice learning, diverse demographics, variable dwell times). Zhou et al.'s museum-specific meta-analysis bridges this gap, but further museum evidence is needed.
- Measurement relies primarily on self-report. Approximately 85% of presence studies use subjective questionnaires. The field would benefit from complementary physiological and behavioral measures, an opportunity for institutions seeking research funding.
"The research is here. The funding pathways exist. The theoretical frameworks are established. The question for museums and science centers is not whether immersive learning is supported by evidence. It is how to implement it well."
Every limitation the research identifies has a design response. Here's how ALICE is built to address each one, from cognitive load management to repeat engagement.
See our design principles →Conclusion
"Presence is the psychological mechanism by which immersive technologies activate the learning processes that constructivism, experiential learning, and embodied cognition have long predicted, but only when paired with intentional instructional design."
Presence is not a buzzword. It is a rigorously studied psychological construct with three decades of research, multiple meta-analyses demonstrating measurable learning effects, a dominant theoretical model, and validated instruments for measuring impact. The science is mature enough to ground serious institutional investment and credible grant proposals.
For institutions considering or proposing immersive experiences, the evidence supports a clear set of principles:
- Invest in instructional design as seriously as you invest in technology. The hardware is a delivery mechanism, not the intervention, and this is where experienced partners add the most value.
- Choose immersive formats that match your audience and physical context. Shared, group-based formats align more naturally with how museums function and how visitors learn.
- Measure impact using validated instruments. The presence literature provides six rigorously validated psychometric tools ready for use in evaluation frameworks and grant proposals.
- Design for sustained engagement, not spectacle. Novelty fades; learning that activates constructivist mechanisms does not.
- Leverage the social nature of museum learning by favouring shared immersive experiences where possible. Co-presence amplifies both engagement and learning.
The research is here. The funding pathways exist. The theoretical frameworks are established. The question for museums and science centers is not whether immersive learning is supported by evidence. It is how to implement it well.
Citations
The studies below collectively confirm that well-designed immersive experiences produce measurably better learning outcomes. Individual study titles reflect their specific research questions. The meta-analytic picture is consistently positive.
This white paper may be freely cited and referenced with attribution to Hammer & Anvil.
- Lombard, M. & Ditton, T. (1997). At the heart of it all: The concept of presence. Journal of Computer-Mediated Communication, 3(2). Over 4,000 citations. ↗
- Slater, M. & Wilbur, S. (1997). A framework for immersive virtual environments (FIVE). Presence: Teleoperators and Virtual Environments, 6(6), 603–616. ↗
- Witmer, B.G. & Singer, M.J. (1998). Measuring presence in virtual environments: A presence questionnaire. Presence, 7(3), 225–240. Nearly 6,000 citations. ↗
- Witmer, B.G., Jerome, C.J. & Singer, M.J. (2005). The factor structure of the Presence Questionnaire. Presence: Teleoperators and Virtual Environments, 14(3), 298–312.
- Garrison, D.R., Anderson, T. & Archer, W. (2000). Critical inquiry in a text-based environment. The Internet and Higher Education, 2(2–3), 87–105. ↗
- Slater, M. (2009). Place illusion and plausibility can lead to realistic behaviour in immersive virtual environments. Philosophical Transactions of the Royal Society B, 364(1535), 3549–3557. ↗
- Lee, K.M. (2004). Presence, explicated. Communication Theory, 14(1), 27–50. ↗
- Makransky, G. & Petersen, G.B. (2021). The Cognitive Affective Model of Immersive Learning (CAMIL). Educational Psychology Review, 33, 937–958. ↗
- Makransky, G., Terkildsen, T.S. & Mayer, R.E. (2019). Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and Instruction, 60, 225–236. ↗
- Makransky, G. & Mayer, R.E. (2022). Benefits of taking a virtual field trip in immersive virtual reality. Educational Psychology Review, 34, 1771–1798. ↗
- Merchant, Z. et al. (2014). Effectiveness of VR-based instruction: A meta-analysis. Computers & Education, 70, 29–40. ↗
- Coban, M., Bolat, Y.I. & Goksu, I. (2022). The potential of immersive VR to enhance learning: A meta-analysis. Educational Research Review, 36, 100452. ↗
- Villena-Taranilla, R. et al. (2022). Effects of VR on learning outcomes in K-6 education: A meta-analysis. Educational Research Review, 35, 100434. ↗
- Zhou, B., Chen, J. & Wang, Q. (2022). A meta-analytic review on incorporating VR and AR in museum learning. Educational Research Review, 36, 100454. ↗
- Cummings, J.J. & Bailenson, J.N. (2016). How immersive is enough? A meta-analysis. Media Psychology, 19(2), 272–309. ↗
- Falk, J.H. & Dierking, L.D. (2000). Learning from Museums: Visitor Experiences and the Making of Meaning. AltaMira Press.
- Falk, J.H. & Storksdieck, M. (2005). Using the contextual model of learning. Science Education, 89(5), 744–778.
- Yu, K.C., Sahami, K., Denn, G., Sahami, V. & Sessions, L.C. (2016). Immersive planetarium visualizations for teaching solar system moon concepts to undergraduates. J. Astronomy & Earth Sciences Education, 3(2), 93–110.
- Jacobson, J. (2011). Digital dome versus desktop display in an educational game. Int. J. Gaming and Computer-Mediated Simulations, 3(1), 13–32.
- Jacobson, J. (2013). Digital dome versus desktop display: Learning outcome assessments by domain experts. Int. J. Virtual and Personal Learning Environments, 4(3), 51–65.
- Oh, C.S., Bailenson, J.N. & Welch, G.F. (2018). A systematic review of social presence. Frontiers in Robotics and AI, 5, Article 114. ↗
- Schubert, T., Friedmann, F. & Regenbrecht, H. (2001). The experience of presence: Factor analytic insights. Presence, 10(3), 266–281.
- Lombard, M., Weinstein, L. & Ditton, T. (2011). Measuring telepresence: The validity of the TPI. Proceedings of ISPR 2011.
- Biocca, F. (1997). The cyborg's dilemma: Progressive embodiment in virtual environments. JCMC, 3(2).
- Makransky, G., Lilleholt, L. & Aaby, A. (2017). Development and validation of the Multimodal Presence Scale. Computers in Human Behavior, 72, 276–285. ↗
- Kolb, D.A. (1984). Experiential Learning. Prentice-Hall.
- Lave, J. & Wenger, E. (1991). Situated Learning. Cambridge University Press.
- Csikszentmihalyi, M. (1990). Flow: The Psychology of Optimal Experience. Harper & Row.
- Barsalou, L.W. (1999). Perceptual symbol systems. Behavioral and Brain Sciences, 22(4), 577–660.
- Skarbez, R., Brooks, F.P. & Whitton, M.C. (2017). A survey of presence and related concepts. ACM Computing Surveys, 50(6), Article 96. ↗
- Heath, C., Vom Lehn, D. & Osborne, J. (2005). Interaction and interactives. Public Understanding of Science, 14(1), 91–101.
- Miguel-Alonso, I., Rodriguez-Garcia, B. & Checa, D. (2024). Novelty effect on user experience with immersive VR. Virtual Reality, 28, Article 43.
- Makransky, G. et al. (2021). Immersive VR increases liking but not learning... and generative learning strategies promote learning in IVR. J. Educational Psychology, 113(4), 719–735.
- Sylaiou, S. et al. (2010). Exploring the relationship between presence and enjoyment in a virtual museum. Int. J. Human-Computer Studies, 68(5), 243–253. ↗
- ICOM Strategic Plan 2022–2028. icom.museum
- American Alliance of Museums (2018). Unpacking our understanding of immersion. Museum Magazine.
- Mayer, R.E. (1996). Learning strategies for making sense out of expository text: The SOI model for guiding three cognitive processes in knowledge construction. Educational Psychology Review, 8, 357–371. ↗
- Bailenson, J.N. et al. (2025). Five canonical findings from 30 years of psychological experimentation in virtual reality. Nature Human Behaviour. DOI: 10.1038/s41562-025-02216-3. Source of the DICE framework (Dangerous, Impossible, Counterproductive, Expensive). ↗
- Cromley, J.G. et al. (2024). Confounded or controlled? A systematic review of media comparison studies involving immersive virtual reality for STEM education. Educational Psychology Review, 36. DOI: 10.1007/s10648-024-09908-8. ↗
- American Alliance of Museums (2021). Evaluating the impact of augmented and virtual reality. aam-us.org