ScholarWorks@중앙대학교

초록

This study applies the Learning Ecosystem framework to structure the learning environment of virtual museums and empirically analyze how the key environmental characteristics influence learners’ perceived academic outcomes. The research model defines five sub-factors of the external system—flexibility, perceived usability, system functionality, content quality, and interest—as well as perceived interaction as the mediating (intermediate) system, self-directed learning ability as the internal system, and perceived academic achievement as the final outcome variable. A survey was conducted with 313 users of three major virtual museums in Beijing.. The collected data were analyzed using SPSS v.26.0 and SmartPLS v.3.3, performing reliability and validity tests, structural equation modeling (SEM), and mediation effect analyses. The results reveal that the learning environment characteristics of virtual museums significantly and positively influence perceived interaction, self-directed learning ability, and perceived academic achievement. Among these factors, system functionality, content quality, and interest exerted the strongest effects on learners’ perceived learning performance. Furthermore, both perceived interaction and self-directed learning ability showed significant mediating effects between the learning environment characteristics and learning outcomes, with full mediation identified in certain paths. These findings indicate that virtual museums function not merely as spaces for exhibiting art, but as learning ecosystems where the components of the learning environment, interaction, and self-directed learning work organically to enhance learning outcomes. This study provides theoretical and practical implications for the design of digital cultural and artistic education environments that maximize learning effectiveness.

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