Pipe after pipe: A longitudinal comparison between AR and VR as means to develop spatial ability in vocational education students, considering novelty and sense of presence
Year: 2026
Type: article
Study designs: Randomized Controlled Trial, Clinical Trial
Abstract: Virtual technologies such as AR and VR have proved to be effective for spatial ability development. However, interventions are often very short, and a direct AR-VR comparison is lacking. This holds especially true for vocational education, where many professions rely on good spatial ability, operationalized via technical drawing tasks that mirror professional practices. This study investigates the differences, if any, between AR and VR used with head-mounted displays for the development of spatial ability in a longitudinal design. It also considers the role played by novelty and looks at the associations of the sense of presence with motivation and extraneous cognitive load. Thirty-two sanitary installer apprentices were randomly assigned to the AR or VR condition; three never produced a valid exercise at any session and were excluded from the analyses, leaving 29 analysed. Participants used an immersive application to learn to transpose 2D representations of pipe schemes into 3D virtual constructions. Training consisted of four sessions spread over a five-week period. Mental rotation and technical drawing skills were assessed one week before and after treatment. Motivation, ease of use, negative effects, extraneous cognitive load and sense of presence were monitored after each session. Spatial ability outcomes improved in both conditions, with no significant differences between the two technologies; Bayesian analyses supported the absence of a difference between the two conditions for mental rotation, but were inconclusive for technical drawing skills. Motivation was significantly associated with exercise performance even though it diminished over time. Sense of presence was significantly associated with higher motivation and lower extraneous cognitive load.
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $1,880
OpenAlex ID: W7222796284
