Augmented Reality for Interactive Historical Art Preservation and Study

Thesis Abstract

Augmented reality (AR) offers transformative potential for the preservation and study of historical artworks by enabling immersive, context-rich visualizations that augment physical artifacts without altering their material integrity. This study addresses the persistent challenge of accessible, accurate documentation and interpretive engagement with fragile artworks in museum and archival settings, where traditional conservation records and static displays limit public understanding and scholarly analysis. The aim is to develop and evaluate an AR-based framework that enhances interactive preservation documentation, provenance tracing, and interpretive learning while ensuring conservation ethics and artifact safety. Specific objectives include (1) designing an AR system that overlays high-fidelity digital reconstructions, material properties, and provenance metadata onto real-world artworks; (2) assessing the system’s impact on visitor engagement, comprehension, and perceived information credibility; (3) evaluating the fidelity of digital reconstructions against expert conservation assessments; (4) examining educators’ and curators’ perspectives on workflow integration and interpretive value; and (5) establishing guidelines for ethical AR deployment in heritage contexts. The study employs a mixed-methods research design conducted in three phases over 18 months. Phase I involves a developmental study with a purposive sample of 12 conservators and 6 curators from major regional museums to co-design the AR interface, guided by Activity Theory to ensure alignment with professional practices. Phase II implements a quasi-experimental field trial in two museum galleries with a total of 240 adult visitors, using a randomized controlled design to compare AR-enhanced interactions (n=120) against traditional displays (n=120). Phase III provides an evaluative synthesis through qualitative interviews and focus groups with 20 conservators, 12 educators, and 40 visitors. Data collection instruments include (i) a usability and perceived credibility questionnaire adapted from the System Usability Scale and the Credibility Inventory, (ii) a knowledge gain assessment with pre- and post-tests tailored to artwork provenance, restoration history, and interpretive content, (iii) observational checklists for user engagement, (iv) semi-structured interview guides, and (v) expert review rubrics for digital reconstructions against conservation records. Validity and reliability are ensured through triangulation, pilot testing (n=30), and inter-rater reliability checks (Cohen’s kappa > 0.75) for qualitative coding. Data analysis integrates quantitative and qualitative methods. Descriptive statistics and inferential analyses test hypotheses related to engagement and knowledge gain; ANCOVA controls for prior art knowledge. Regression analysis explores predictors of learning outcomes, while logistic regression models uptake likelihood of AR features among visitors. Thematic analysis is applied to interview transcripts, with code co-occurrence matrices to identify patterns in perceived credibility, ethical concerns, and workflow integration. The conceptual basis combines UNESCO heritage ethics, the Information Foraging Theory to model visitor information-seeking behavior, and Social Constructivism to interpret interpretive learning. A conceptual model maps AR affordances to preservation objectives, visitor outcomes, and institutional workflows. Anticipated findings indicate that AR-enhanced exhibits increase visitor engagement by 28% (p<0.05) and knowledge gains by 22% (p<0.05) relative to traditional displays, with higher perceived credibility among informed audiences. Expert reviews are expected to affirm high fidelity of digital reconstructions and accurate provenance metadata integration, while conservators report improved documentation workflows yet raise concerns about long-term maintenance and data stewardship. The study contributes to knowledge by operationalizing an ethics-informed AR framework for historical art preservation that couples technical feasibility with curatorial practice, and by providing an evidence-based evaluation of AR’s impact on learning outcomes, provenance transparency, and conservation documentation. Based on findings, the study recommends a standards-driven AR deployment protocol emphasizing metadata governance, revision control for digital reconstructions, consent-based artifact augmentation guidelines, and training programs for curatorial and conservation staff. It also suggests scalable integration strategies for other heritage domains, and outlines a roadmap for longitudinal studies to assess durability of interpretive effects and preservation integrity over time.