Abstract
Cultural tourism visitors’ interaction with cultural artifacts is a central aspect of museum experiences and a key method for understanding cultural heritage. Museums are increasingly using Augmented Reality (AR) to enhance visitor engagement and learning. This study explores how AR technology can improve interactions between visitors and artifacts. A mixed-methods approach was adopted, including focus group discussions with participants from two age groups: adults (18–35), and older adults (36- 60). We used thematic analysis to identify user preferences and needs. And the preliminary survey reveals a U-shaped age curve in AR interest: both children and older adults’ express high enthusiasm, whereas the middle-age group remains moderately engaged. During prototype testing, we observed and interviewed visitors as they used AR-enabled devices to scan artworks and interact with AI- powered features. Surveys were later conducted to evaluate the effectiveness of the designs.
Keywords
Artificial intelligence; Museum; Interactive design; Immersive experience; Formatting instruction
DOI
https://doi.org/10.21606/iasdr.2025.396
Citation
Li, J.,and Kong, A.(2025) Augmenting Artistic Engagement: Developing AI-powered AR application for Personalized Museum Experiences, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.396
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 3 - Design, Art & Technology
Augmenting Artistic Engagement: Developing AI-powered AR application for Personalized Museum Experiences
Cultural tourism visitors’ interaction with cultural artifacts is a central aspect of museum experiences and a key method for understanding cultural heritage. Museums are increasingly using Augmented Reality (AR) to enhance visitor engagement and learning. This study explores how AR technology can improve interactions between visitors and artifacts. A mixed-methods approach was adopted, including focus group discussions with participants from two age groups: adults (18–35), and older adults (36- 60). We used thematic analysis to identify user preferences and needs. And the preliminary survey reveals a U-shaped age curve in AR interest: both children and older adults’ express high enthusiasm, whereas the middle-age group remains moderately engaged. During prototype testing, we observed and interviewed visitors as they used AR-enabled devices to scan artworks and interact with AI- powered features. Surveys were later conducted to evaluate the effectiveness of the designs.