Enhancing dance learning by optimising instructional perspective: A preregistered study on the effect of dancers’ viewing perspective, cognitive load and expertise

Elisabetta Versace, Manuela Angioi, Kristin Hadfield, Vincent Gallo, Lars Juhl Jensen, Juncal Roman, Karen Sheriff, Emma Redding, Frances Clarke, Julian Deering, Dylan Morrissey and Stephen Buckingham

PLOS ONE, 2026, vol. 21, issue 9, 1-15

Abstract: While movement sequences in choreography are often taught through instructor demonstrations, the influence of visual perspective on learning outcomes has received limited attention. Drawing on cognitive load theory, we investigated how the requests imposed by different instructional perspectives affect learning and performance. We compared the effects of Back view (first-person), Front mirror view (third-person mirrored), and Front opposite view (third-person) between dancers. We hypothesized lower cognitive load and better performance in the Back view, particularly for less experienced dancers. After preregistering the study, 32 dancers with varying levels of experience learned a moderately complex choreography from pre-recorded videos, in the three perspectives. Five dance experts assessed movement accuracy, spatial skills, and rhythm/dynamics using a validated scoring system and a new open-source digital tool. The Back view consistently yielded superior outcomes, especially among less trained dancers. No significant differences emerged between the two third-person views, possibly due to sample size or dancer background. These findings suggest that first-person perspectives may support motor learning, with performance patterns consistent with reduced cognitive load. Practically, camera perspective should be considered in online instruction, while first-person views may benefit early in-person training. Our results highlight the role of visual perspective in learning choreography and complex motor routines, offering both theoretical and applied contributions, including validation of a novel digital assessment tool.

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0355860 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 55860&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0355860

DOI: 10.1371/journal.pone.0355860

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().