Evidence map›Paper›PMID 41057539›Full record

ArticleScientific reports2025

Immersive teaching model for traditional Chinese opera costume design based on virtual reality: digital cultural heritage, inheritance, and innovation.

Zhiyan Su

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

1 author.

Zhiyan SuSchool of Fine Arts, Anqing Normal University, Anqing, 246133, Anhui, China. 050064@aqnu.edu.cn.

Funding

Key Scientific Research Project of Anhui Provincial Universities 2024AH052760Quality Engineering Project of the Department of Education of Anhui Province - Anhui Creative Design Industry College 2024cyts007Quality Engineering Project of the Department of Education of Anhui Province - Upgrading and Transformation of the Fashion and Costume Design Program 2024zygzts060
6 · The paper itself

Abstract

Traditional Chinese opera costumes are vital carriers of intangible cultural heritage, embodying intricate craftsmanship, symbolic aesthetics, and cultural narratives. However, conventional pedagogy struggles to convey their complexity and cultural depth due to limitations in static, lecture-based teaching methods. This study proposes an immersive Virtual Reality (VR)-based teaching model that integrates high-fidelity 3D modeling, semantic annotation, and real-time rendering optimization-specifically Level of Detail (LOD) and Occlusion Culling (OC)-to enhance the design education and cultural transmission of traditional Chinese opera costumes. A controlled experiment involving 80 undergraduate students was conducted to compare the VR-based model with traditional teaching methods across five dimensions: learning effectiveness, user experience, cultural understanding, technological adaptability, and instructional interaction. Results demonstrated that the VR-based approach significantly improved educational outcomes, particularly in interactive engagement and practical performance, while maintaining high rendering efficiency and visual fidelity. This work contributes a technically optimized, pedagogically grounded framework for integrating immersive technology into cultural heritage education, offering a scalable solution for revitalizing intangible traditions in the digital era.

Indexed as

Chinese opera costume designDigital cultural heritageEducational technologyImmersive learningLevel of detail (LOD)Occlusion culling (OC)Virtual reality(VR)

Identifiers

PMID41057539
PMCPMC12504592

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.