A metaverse literacy assessment framework for immersive library information services in the generative AI era

Abstract

As virtual reality (VR) services expand in libraries and increasingly intersect with generative artificial intelligence (AI), questions of user preparedness and competency gaps have become critical to the sustainability of immersive information services. This study aims to develop and empirically test a metaverse literacy assessment framework to evaluate the competencies required for participation in VR- and AI-enabled library information services. Drawing on information literacy, digital literacy, algorithm literacy and AI literacy, the study constructs a framework comprising four primary dimensions and 13 secondary indicators through literature analysis, the Delphi method and the analytic hierarchy process (AHP). The framework is then validated using survey data from 453 university faculty members and students. Reliability and validity tests, the entropy method and non-parametric tests are employed to examine structural robustness, indicator salience and group differences. The results show that knowledge, skills and norms play a central role in differentiating competency levels for immersive information environments. Tool knowledge, evaluation capability, ethical literacy and risk-related indicators emerge as particularly salient. Significant differences are found across educational and disciplinary groups, suggesting that competency gaps in VR- and AI-enabled information services are unevenly distributed and require targeted educational interventions. This study repositions metaverse literacy as a service-oriented competency framework for libraries rather than a purely technological construct. It offers a quantitative assessment tool for identifying user preparedness and competency gaps in immersive information services and provides practical guidance for libraries designing onboarding, instruction and risk-mitigation strategies for VR services in the generative AI era.