Learning intention formation mechanisms among university students in virtual heritage experiences of Sichuan shadow puppetry
Year: 2026
Type: article
Study design: Observational Study
Abstract: Shadow puppetry, an intangible cultural heritage (ICH), urgently requires digital technology to enrich learning experiences. Although virtual reality (VR) offers immersive interactions for ICH education, user experience mechanisms remain under-researched. Based on a Sichuan shadow puppetry VR platform, this study integrated the Stimulus–Organism–Response (S-O-R) framework, Information Systems Success Model (ISSM), and Technology Acceptance Model (TAM) to build a VR learning intention model for university students. Analyzing 522 empirical datasets via structural equation modeling (SEM) and artificial neural network (ANN), we found that content quality (CQ) and interaction quality (INQ) significantly enhanced perceived ease of use (PEOU) and perceived usefulness (PU), whereas service quality (SEQ) showed negligible effects. PEOU and PU drove learning intention (LI) through learning attitude (LA), with self-efficacy (SE) strengthening the attitude–intention transition. ANN further revealed non-linear predictive complexities. These insights inform digital ICH pedagogy and VCH system design.
Source: npj Heritage Science
Authors: Mengyi Liu, Min Hou, Jiayi Zhang, Jing Pu
Institution: Sichuan Agricultural University
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W7208739765
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