Augmented Reality Exhibition Design for Contemporary Art Consumption

Thesis Abstract

Augmented reality (AR) has emerged as a transformative modality for experiencing contemporary art, yet existing exhibition practices often prioritize physical presence over immersive potential, limiting accessibility, visitor agency, and interpretive depth. This study investigates how AR exhibition design can augment contemporary art consumption by integrating digital overlays, spatial storytelling, and interactive affordances that blend physical artworks with contextually rich digital content. The problem addressed is the mismatch between traditional gallery experiences and diverse audience needs for multimodal engagement, information accessibility, and inclusivity in interpretation. The aim is to develop, implement, and evaluate a design-informed AR exhibition framework that enhances comprehension, emotional engagement, and sustained interest in contemporary artworks. Specific objectives are to (i) identify key design principles for AR-enhanced exhibitions grounded in art theory and user experience design; (ii) implement a prototypical AR exhibition workflow within a mid-sized contemporary art museum, featuring 12 selected works across three gallery spaces; (iii) assess user experience, perceived value, and learning outcomes among diverse visitor cohorts; (iv) analyze how AR design variables influence interpretation accuracy, aesthetic appreciation, and recall; and (v) formulate actionable guidelines for curators, designers, and institutions seeking scalable AR integration. A mixed-methods methodology is employed. The research adopts an interpretive-constructivist stance complemented by design science elements. Data collection comprises a purposive sample of 320 museum visitors recruited over a 12-month pilot period in collaboration with the Metropolitan Contemporary Art Center. Quantitative data are gathered via pre- and post-visit surveys (n?320) to measure perceived usefulness, engagement, and learning gains using validated scales such as the User Engagement Scale and the ART-Learning Index. AR interaction logs (n?15,000 events) capture usage patterns, dwell times, and feature utilization. A quasi-experimental design compares the AR-enhanced condition with a control condition (non-AR interpretation) across matched gallery routes. Qualitative data are collected through 40 semi-structured interviews and 6 focus groups (4–6 participants per group) to elicit nuanced perspectives on interpretive clarity, aesthetic experience, and accessibility. Thematic analysis is applied to interview transcripts, while regression analyses examine relationships between AR design variables (overlay density, narrative sequencing, interactivity level) and outcomes such as interpretation accuracy (measured via post-visit quizzes) and overall satisfaction. Network analysis explores associations among design features and user segments (novice, frequent museum-goer, visually impaired). Validity is ensured through triangulation, member checks, and pilot testing of instruments; reliability is established for scales with Cronbach’s alpha > .80. The study integrates theoretical frameworks from reception aesthetics, affordance theory, and situated cognition, with explicit reference to Arnheim’s gesture theory and Dourish’s embodiment in ubiquitous computing. The anticipated findings indicate that well-curated AR overlays that align with artwork-intention, exhibit flow, and contextual storytelling significantly improve interpretation accuracy by 15–25%, increase aesthetic appreciation by 10–20%, and elevate overall engagement by 20–30% compared to non-AR conditions. However, excessive overlay density or intrusive interactions may impede comprehension and reduce visitor satisfaction, underscoring the need for balanced design. The research contributes to knowledge by operationalizing a scalable AR exhibition framework that blends curatorial intent with interactive technology, offering measurable impact on learning outcomes, accessibility, and visitor retention. It advances design methodology for AR in the arts, providing a replicable workflow, evaluation metrics, and a set of best-practice guidelines for museum practitioners. Recommendations include developing tiered AR content to cater to diverse audiences, co-design approaches with artists and accessibility experts, rigorous ethical considerations regarding data privacy and cultural representation, and iterative refinement through longitudinal studies to assess long-term impact on art literacy and public engagement. The study concludes that AR-enhanced exhibitions can meaningfully expand contemporary art consumption when design is purposefully aligned with interpretive goals, user experience, and institutional values, and it calls for ongoing interdisciplinary collaboration to sustain innovation within museum contexts.