Virtual Reality Simulations¶

Strategy · All strategies
Evidence · 1 claim (1 against) · 2 studies (1 causal, 1 quant-synthesis), q3–q4 · 1 of 2 report an effect size

Description¶

Virtual reality (VR) simulations place learners inside an interactive, computer-generated environment where they can perform procedures, manipulate objects, and experience scenarios that would be dangerous, expensive, or impractical in the real world. Learning is carried out through embodied action — the learner does the task (or a scaled version of it) rather than reading or watching about it, typically with system feedback on performance.

Design Implications¶

VR's core pedagogical value is safe, repeatable practice of procedural and spatial tasks with immediate feedback, which meta-analytic evidence supports over conventional instruction, particularly in health professions and technical training (Kyaw et al., 2019) [+M]. However, immersion is not instruction: VR's novelty and sensory richness impose extraneous load, and learning gains depend on embedding sound instructional design (clear objectives, guidance, debriefing) inside the simulation [Makransky & Mayer, 2022] [~M]. The medium amplifies whatever design it contains — a well-structured simulation teaches; a poorly structured one merely entertains.

Context¶

Requirements¶

• Clearly defined learning objectives that map to actions the learner can actually perform in the environment
• Embedded guidance: prompts, hints, or an in-scenario coach (Scaffolding) rather than free exploration
• Performance feedback and a structured debrief after the scenario (Assessment, Practice)
• Attention to cognitive load: segment scenarios, minimize decorative detail, and pretrain on controls before content [Makransky & Mayer, 2022] [+M]

Constraints¶

• High extraneous cognitive load from immersive detail and interface manipulation can degrade learning, especially for novices Cognitive overload degrades learning. [-M]
• Novelty effects inflate short-term engagement measures but do not reliably produce retention gains [Makransky & Mayer, 2022] [~W]
• Cybersickness and headset discomfort limit session length and exclude some learners (vestibular disorders, young children) [-M]
• Cost, content-development effort, and device logistics make VR inefficient for verbal/conceptual goals that a text or video would serve as well [-M]
• Unstructured "exploration" in open virtual environments often produces wandering rather than learning [~M]

Implementation Variability¶

• Fully immersive (headset) vs. desktop simulation — desktop versions often achieve comparable learning outcomes at far lower cost (Kyaw et al., 2019) [~M]
• Procedural rehearsal (surgical steps, lab safety) vs. decision rehearsal (triage, crisis management) vs. spatial exploration (anatomy, field sites)
• Single-user vs. multi-user collaborative scenarios with role assignment
• 360° video as a low-cost middle ground for observational (non-manipulative) learning

Target Learners¶

• Novices in high-stakes procedural domains (medicine, aviation, laboratory science, trades) who need safe rehearsal before real performance (Kyaw et al., 2019) [+M]
• Learners who benefit from spatial/embodied understanding of structures and processes that are hard to convey in 2D [~M]
• Less valuable for learners whose goals are purely verbal, conceptual, or argumentative — the added immersion adds cost without adding learning [Makransky & Mayer, 2022] [~M]

Target Learning Goals¶

• Procedural skill acquisition and psychomotor rehearsal
• Spatial knowledge: anatomy, architecture, molecular structure, terrain
• Decision-making under realistic constraints and time pressure
• Affective outcomes: empathy and perspective-taking through embodied role experience [~W]

Instructions¶

1. Define the observable performance the simulation should train and how success will be measured (Assessment).
2. Pretrain learners on the interface and domain vocabulary outside VR to free working memory for the task itself (Cognitive Load Management) [+M].
3. Run a guided scenario with embedded prompts and feedback (Practice, Scaffolding); increase difficulty or variability across repeated runs (Adaptive Difficulty).
4. Debrief immediately after the scenario — compare learner decisions against expert decisions and edge cases (Case Studies) [+M].
5. Follow with transfer tasks in a different format (real equipment, written cases) to check that learning did not stay trapped in the virtual context [~M].

Related Strategies¶

• Simulation-based practice with manikins — the physical-equipment analogue; VR often substitutes for or precedes it
• Case-based discussion — the debrief structure from case methods transfers directly to post-scenario reflection
• Video-based modeling — a lower-cost observational alternative when manipulation is not required
• Use direct-experience formats — simulation games, extracurricular activities, action learning, peer teaching — to pursue relational-domain objectives
• Structured activity design and moderate realism benefit shared VR learning environments
• Use advanced immersive learning technologies as research and learning tools to deliver developmentally-appropriate metacognitive scaffolding

Examples¶

• Osso VR (https://ossovr.com) — surgical rehearsal platform; randomized studies showed orthopedic trainees using it outperformed conventionally trained peers on assessed procedure performance [+M]
• Labster (https://www.labster.com) — virtual science laboratory simulations used in university chemistry and biology courses, with embedded quizzes and guided storylines
• vSim for Nursing (https://www.elsevier.com/vsim) — Wolters Kluwer/Laerdal patient scenarios with branching decisions and post-simulation debriefing worksheets
• Google Expeditions (archived) — 360° field-trip VR for K-12; a large-scale study found learning gains only when paired with structured, teacher-guided tasks rather than free exploration [~M]

Key Sources¶

• Kyaw, B. M., Saxena, N., Posadzki, P., Vseteckova, J., Nikolaou, C. K., George, P. P., Divakar, U., Masiello, I., Kononowicz, A. A., Zary, N., & Tudor Car, L. (2019). Virtual reality for health professions education: Systematic review and meta-analysis. Journal of Medical Internet Research, 21(1), e12959. doi:10.2196/12959
• Makransky, G., & Mayer, R. E. (2022). Benefits and costs of immersive virtual reality learning environments: A learning sciences perspective. Nature Reviews Psychology, 1, 691–707.
• Makransky, G., & Petersen, G. B. (2021). The Cognitive Affective Model of Immersive Learning (CAMIL): A theoretical research-based model of learning in immersive virtual reality. Educational Research Review, 34, 100417. doi:10.1007/s10648-020-09586-2
• Mayer, R. E. (2021). Multimedia Learning (3rd ed.). Cambridge University Press. doi:10.1017/9781316941355