AI-Enhanced Virtual Reality for Human Anatomy Education Learning Efficiency, Cognitive Load, and Future Research Directions

Modern and Contemporary Research in Health Sciences, Fatih HATİPOĞLU, Editör, All Sciences Academy, İstanbul, ss.5-21, 2026

ABSTRACT

Background and Objective Traditional medical anatomy instruction often

delivers limited spatial interactivity, creating gaps in long-term retention and

diagnostic reasoning. While immersive technologies offer a solution, evidence

evaluating the synergistic combination of artificial intelligence (AI) and

virtual reality (VR) remains fragmented. This narrative review aims to

synthesize the current evidence regarding VR-based anatomy learning

outcomes and examine the technical feasibility, early cognitive-load impact,

and instructional efficacy of emerging integrated AI-VR platforms.

Methods A narrative review was conducted of peer-reviewed literature

(2019–2026) retrieved from PubMed/PMC, Scopus-indexed journals,

ResearchGate, arXiv, and publisher databases (Springer, Wiley, Sage, JMIR).

The search was executed using combinations of the terms: artificial

intelligence, virtual reality, anatomy education, learning outcomes, and

cognitive load. Because few studies isolate an AI-VR combination

specifically within anatomy curricula, closely related systematic reviews,

meta-analyses, and randomized controlled trials (RCTs) of VR-only and AIonly

anatomy or procedural training were also included to contextualize

findings.

Results Across the reviewed systematic reviews and trials, VR-based anatomy

instruction is associated with improved short-term knowledge acquisition,

higher learner satisfaction, and favorable usability ratings relative to

traditional teaching, although retention effects and behavior-level outcomes

are less consistently reported. Emerging AI-VR systems—such as generative-

AI conversational tutors embedded in VR and AI-driven automated

segmentation feeding VR visualization—demonstrate technical feasibility and

early promise for adaptive, personalized instruction. However, controlled

comparative trials isolating the AI-VR combination (as opposed to VR alone)

remain scarce. Cognitive-load data from related immersive-technology RCTs

suggest lower NASA Task Load Index scores in technology-assisted arms

compared with traditional training.

Conclusions Available evidence supports VR as an effective adjunct to

anatomy education, and preliminary work suggests AI integration may add

adaptivity and efficiency. However, rigorously designed RCTs that isolate the

incremental contribution of AI within VR anatomy instruction—using pretest/

post-test/retention-test designs and validated workload measures—are

critically needed before strong efficiency claims can be made.

Keywords: artificial intelligence; virtual reality; anatomy education; medical

education; cognitive load; NASA-TLX; immersive learning