Evaluating Visitor Engagement in Mixed Reality Digital Heritage Narratives via Structural Equation Modeling

Area of Science:

• Digital Heritage
• Mixed Reality (MR) Technologies
• Human-Computer Interaction

Background:

• Mixed Reality (MR) offers novel platforms for cultural expression.
• Limited standardized methods exist for quantifying the experiential and educational effectiveness of MR in cultural heritage.
• A need exists for a reliable framework to assess and optimize digital heritage experiences.

Purpose of the Study:

• To present a comprehensive protocol for evaluating the impact of mixed reality (MR) cultural narrative quality on visitor engagement and learning outcomes.
• To establish a quantitative empirical research design for assessing MR effectiveness in digital heritage environments.
• To provide a framework for researchers and designers to optimize educational value.

Main Methods:

• A scenario-based, quantitative empirical research design using a unified MR heritage prototype.
• Data collection from 261 participants via a structured questionnaire measuring narrative quality, immersion, perceived authenticity, emotional connection, visitor engagement, and learning outcomes.
• Analysis using partial least squares structural equation modeling (PLS-SEM) to map structural relationships and mediating effects.

Main Results:

• High-quality MR narratives significantly enhance immersion and perceived authenticity.
• Enhanced immersion and authenticity drive emotional resonance and deeper visitor engagement.
• Heightened visitor engagement translates into improved learning outcomes.

Conclusions:

• The proposed protocol reliably assesses the impact of MR narrative quality on visitor engagement and learning.
• This methodology provides a framework for optimizing the educational value of digital heritage experiences.
• Findings validate the protocol by confirming the positive effects of MR narrative quality on key engagement and learning metrics.