Evidence map›Paper›PMID 42100582›Full record

ArticleProceedings of the SIGCHI conference on human factors in computing systems. CHI Conference2026

Designing for Wayfinding in VR: Linking Navigation Interfaces to Spatial Learning and Cognitive Mapping.

Armin Mostafavi, Zhiwen Qiu, Tong Bill Xu, Wenqian Niu, Saleh Kalantari

Abstract read
In one paragraph

Article in Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Armin MostafaviDepartment of Human Centered Design, Cornell University, Ithaca, New York, USA.
Zhiwen QiuInformation Science, Cornell University, Ithaca, New York, USA.
Tong Bill XuDepartment of Human Centered Design, Cornell University, Ithaca, New York, USA.
Wenqian NiuDepartment of Human Centered Design, Cornell University, Ithaca, New York, USA.
Saleh KalantariDepartment of Human Centered Design, Cornell University, Ithaca, New York, USA.

Funding

A Social Engaging Restorative Virtual Environment (SERVE) Volunteer Intervention to Support Social Engagement and Well-Being in Older Adults with Cognitive ImpairmentR01AG082831 · NIA · CORNELL UNIVERSITY · PI Walter Richard Boot, SARA J CZAJA · 2023 to 2026
$3.0M
NIA NIH HHS R01 AG082831
6 · The paper itself

Abstract

Various virtual locomotion techniques and visual transition methods are used in VR-based navigation research, yet few studies have systematically examined their effects on spatial learning, cognitive map formation, and navigational performance in complex indoor environments. We conducted a between-subjects study (N=142) in two high-fidelity VR hospital contexts, including free exploration and task-based wayfinding, while treating locomotion and viewpoint transitions as experimental factors. Spatial learning was measured through pointing, distance estimation, and sketch-map accuracy; performance was measured through completion time and distance traveled; and experience was measured through cybersickness, perceived presence, and usability. Locomotion techniques affected task completion time, with teleportation associated with faster performance in the task-based context. Spatial learning effects were mixed, with patterns indicating that techniques without viewpoint transitions may better support cognitive mapping. Empirical insights and guidelines are provided to improve the reliability and real-world applicability of VR-based wayfinding research.

Indexed as

locomotionnavigational performancespatial learningteleportationviewpoint transitionVR Wayfinding

Identifiers

PMID42100582
PMCPMC13148787

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.