As artificial intelligence, spatial computing, and sensor-based environments converge, the role of the library is undergoing a necessary and radical transformation. Libraries are no longer merely repositories of analog knowledge but are emerging as platforms for immersive cognitive engagement and digitally mediated exploration. The next evolutionary step is the Library as a Mixed Reality Learning Lab (MRLL), where virtual, augmented, and extended reality (VR, AR, XR) technologies converge with artificial intelligence and data-rich environments to reconfigure learning, research, and community participation.
Mixed reality is not simply a tool for visual novelty. It is an interface layer that allows users to engage with abstract and complex information systems through spatial immersion and sensory interactivity. As Milgram and Kishino (1994) originally framed it, mixed reality spans a continuum from real environments to fully virtual ones, enabling a blended interface where human cognition and digital systems meet in dynamic interplay. Today’s MR environments use head-mounted displays (HMDs), haptic wearables, LIDAR scanning, and real-time 3D rendering to construct experiential simulations of everything from biological processes to historical archives.
By implementing MRLLs, libraries can provide access to these advanced cognitive tools in a way that is community-driven and equity-centered. Through spatial computing, libraries can offer layered experiences: patrons might step into a digital twin of their neighborhood layered with oral histories and sensor data visualizations, or enter an immersive chemistry simulation where chemical reactions unfold around them in real-time 3D, powered by physics engines and controlled through gesture input. This type of embodied interaction reflects what Wilson (2002) and Barsalou (2008) identified as embodied cognition—the idea that knowledge acquisition is deeply tied to physical experience and multisensory engagement.
An MRLL infrastructure can include spatial experience booths, tactile-feedback haptic stations, eye-tracking-enabled learning pods, and ambient intelligence systems. Databot, for example, offers sensor-based hardware that can be integrated with AR overlays to provide real-time data collection and visualization during STEM investigations (Databot.us, 2024). Combined with AI agents trained in natural language understanding and responsive pedagogy, libraries can deploy dynamic virtual librarians who do more than answer questions—they guide users through simulations, adapt experiences based on biometric feedback, and help scaffold understanding in real time.
A practical application of this integration is the development of AI-guided microlearning quests, or “SkillQuests,” where patrons earn badges by completing simulations designed around key workforce competencies such as circuitry design, climate modeling, or data ethics. These quests would be powered by AI backends capable of adjusting complexity based on learner progress, using real-time analytics and pattern recognition to tailor challenges for optimal cognitive load. Libraries become credentialing spaces—granting micro-certifications backed by blockchain verifiability, in partnership with edtech platforms and educational institutions.
At the infrastructure level, spatial computing technologies allow libraries to create persistent digital environments using tools like Unity, Unreal Engine, and WebXR. These environments can be accessed via headsets, mobile phones, or projected mixed-reality displays in physical spaces. They can also incorporate digital twins of real-world locations, using data from IoT networks, public APIs, or GIS systems to teach civic literacy, environmental science, or urban planning. These experiences are not passive; they are data-rich, customizable, and interactive—pushing patrons to explore, hypothesize, and create.
MRLLs also offer immense potential for inclusive design. Neurodivergent patrons can benefit from MR environments where stimuli are adjustable via user profiles, allowing them to engage on their own terms. Spatial soundscapes can be adapted using real-time sentiment analysis, while haptic feedback gloves and eye-tracking interfaces enable accessibility for patrons with physical impairments. AI-based voice assistants trained on dialectical variation can deliver culturally and linguistically responsive instruction (Black et al., 2022).
However, equitable access must extend beyond flashy installations. Libraries must ensure data privacy, system transparency, and ethical AI governance in MRLL operations. Issues of surveillance, digital redlining, and algorithmic bias cannot be overlooked (Rainie & Anderson, 2023). Community-based design, participatory tech development, and strong partnerships with privacy advocates are essential to ensure MRLLs are inclusive, not extractive.
Funding MRLLs will require a mix of federal innovation grants, philanthropic investment, and municipal budget realignment. Programs such as the Institute of Museum and Library Services’ National Leadership Grants for Libraries provide early funding for such transformational work (IMLS, 2023). Additionally, partnerships with tech-forward universities, open-source XR communities, and AI research consortia can provide sustainability through collaborative development.
In this techno-socio-educational hybrid vision, librarians themselves must evolve. They are no longer just information managers but technologists, AI interpreters, ethical guides, and immersive learning architects. Library science programs must integrate spatial computing, data visualization, human-AI interaction design, and extended reality pedagogy into their core curriculum. The librarian becomes not just a curator of knowledge, but a constructor of digital reality.
Ultimately, the MRLL is a manifestation of what libraries were always meant to be: portals to new worlds. By embracing immersive and intelligent systems, libraries will not just remain relevant—they will become essential infrastructure in the cognitive economy. As society shifts from information consumption to experiential knowledge generation, the mixed reality library stands at the crossroads of equity, embodiment, and exponential innovation.
References
Barsalou, L. W. (2008). Grounded cognition. Annual Review of Psychology, 59(1), 617–645. https://doi.org/10.1146/annurev.psych.59.103006.093639
Black, R., Choudhury, S., & Dennen, V. P. (2022). Learning in immersive environments: A systematic review of design, outcomes, and equity considerations. Educational Technology Research and Development, 70(4), 1–23. https://doi.org/10.1007/s11423-022-10059-2
Databot.us. (2024). Databot – Smart sensors for STEM learning. https://www.databot.us
Institute of Museum and Library Services. (2023). National Leadership Grants for Libraries. https://www.imls.gov/grants/available/national-leadership-grants-libraries
Milgram, P., & Kishino, F. (1994). A taxonomy of mixed reality visual displays. IEICE Transactions on Information and Systems, E77-D(12), 1321–1329.
Rainie, L., & Anderson, J. (2023). Digital equity in the age of AI: A public policy imperative. Pew Research Center. https://www.pewresearch.org
Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4), 625–636. https://doi.org/10.3758/BF03196322