Digital Cultural Platforms: Visual Arts Learning and Heritage Engagement
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This study examines digitally mediated visual arts learning and cultural engagement using four open secondary datasets that cover virtual art education, community cultural participation, smart museum interactions, and cultural heritage mobile applications. The study responds to a common limitation in digital arts research: broad claims about transformation are often made without connecting educational, cultural, and platform evidence within one empirical design. A secondary quantitative design was used to analyze 1,483 virtual art-learning records, 8,737 cultural engagement records, 2,834 smart heritage interaction records, and 174 cleaned cultural heritage app records. The analysis combined descriptive statistics, feature coding, correlation analysis, robust ordinary least squares models, and logistic regression for binary outcomes. Results show that improvements in learning in virtual art education were strongly associated with creativity, engagement, and collaboration, whereas session duration, peer count, and uptake of automated suggestions did not show meaningful independent effects. Art-quality scores were mainly explained by composition and creativity. In the cultural engagement dataset, event type, participation frequency, social interaction frequency, duration, and recommendation score explained little variation in high engagement, indicating that generic platform indicators are insufficient for interpreting cultural value. In the smart museum data, content clicking was the strongest predictor of visitor satisfaction, and lower crowd density increased the likelihood of interacting with content. Heritage apps most frequently emphasized tours, maps, and audio functions, while accessibility features were rare. The study contributes an integrated empirical framework showing that digital cultural value depends less on the presence of technology than on learning design, interaction quality, inclusion, and meaningful measurement.
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