Editorial: Applications of artificial intelligence and immersive interaction in cultural heritage, digital design, and educational innovation

1 Introduction

Artificial intelligence (AI), virtual and augmented reality, human–computer interaction (HCI), and data-driven design are rapidly reshaping how cultural knowledge is preserved, interpreted, experienced, and taught. Yet technological novelty alone does not guarantee meaningful engagement, accessibility, or educational value. Effective innovation requires systems that are culturally grounded, cognitively informed, inclusive, and evaluated in relation to real users and real contexts. The five contributions to this Research Topic address this challenge across museums, digital heritage, tactile art accessibility, neuroarchitecture, and immersive engineering education. Together, they show that the future of intelligent and immersive technologies depends less on isolated technical performance than on the quality of the relationships they create among people, content, environments, and learning goals.

2 Contributions to the Research Topic

Pan et al., in “Interaction design methods for data-intelligent museum exhibitions: an embodied cognition perspective,” respond to the persistent problem of exhibitions that privilege technological spectacle over cultural meaning. Drawing on embodied cognition and dynamical systems theory, they propose the PCAE model, which connects Body Perception, Body Action, Environmental Construction, and Meaning Construction in a cyclical interaction process. Its application to the “Dialogue with the Master” exhibit at the Confucius Museum demonstrates how interaction can connect bodily experience, environmental feedback, and cultural interpretation. Importantly, the study also reveals practical limitations: visitors rated the exhibit as interesting, but immersion was comparatively weaker, emphasizing that conceptual coherence must be matched by appropriate interaction modalities, task difficulty, and duration.

Shang et al., in “Sensory immersion vs. cultural reflection: a multi-factor analysis of dual-process mechanisms in digital heritage engagement,” examine how users form psychological bonds with digital heritage environments. Their combination of text mining and PLS-SEM distinguishes a fast, hedonic pathway driven by vividness and interactive affordances from a slower, reflective pathway driven by narrative and meaning-making. Narrative quality predicted cultural identity but not hedonic engagement, suggesting that sensory stimulation and cultural reflection should not be treated as interchangeable outcomes. This finding supports dual-mode interface strategies that allow interactive agency while also protecting attention for narrative absorption and identity formation.

Furferi et al., in “From pictorial space to tactile form: a comparative evaluation of AI-based 2.5D reconstruction from modern artwork paintings,” extend the discussion from visual immersion to multisensory accessibility. Comparing monocular depth estimation, large language models, and large reconstruction models, they show that no single approach simultaneously achieves perceptual plausibility, geometric integrity, stylistic fidelity, and manufacturability. Their evaluation framework combines art-historical judgment, geometric verification, and additive-manufacturing expertise. The study therefore positions AI-generated tactile reconstruction not as automatic replication, but as an interpretive and application-dependent process requiring hybrid methods and human-guided post-processing.

Núñez Ávila et al., in “Neuroscience-informed approaches in architectural design: a systematic review of cognitive measures and interactive technologies from an HCI perspective,” synthesize 32 studies at the intersection of neuroarchitecture, HCI, and spatial experience. The review identifies growing use of sensors, spatial computing, and VR, but also finds an uneven evidence base: research concentrates on urban and educational settings, while residential, healthcare, and cultural environments remain underexplored. Attention, comfort, and cognitive load are studied more frequently than memory, welfare, and spatial orientation, and many contributions remain conceptual rather than validated in real-world settings. The review calls for multimodal measurement, transparent reporting, and stronger ecological validity.

Ponce et al., in “Large language models and AI-driven virtual laboratory for FrED and FrED factory: materials, products, and sustainable digital manufacturing,” present an immersive laboratory that integrates VR, LLM-driven expert avatars, personality-tailored interaction, predictive analytics, and optimization algorithms. Deployed on Oculus Quest 3 and Android platforms, the system broadens access through bilingual voice and text interaction and connects technical manufacturing knowledge with critical thinking, collaboration, leadership, and sustainability. Rather than claiming completed learning-effect evidence, the article establishes a structured platform and a multi-method evaluation plan that can compare VR-LLM, VR-only, LLM-only, and conventional conditions.

3 Cross-cutting insights and future directions

Across these studies, four priorities emerge. First, intelligent and immersive systems should be designed around meaning, not technological display. Second, evaluation must extend beyond usability to cultural identity, cognition, learning transfer, accessibility, and long-term engagement. Third, inclusion should be treated as a design principle, as demonstrated by tactile heritage translation, multilingual access, and attention to diverse user capacities. Fourth, AI outputs require contextual validation and human oversight, particularly when semantic plausibility may conceal geometric, cultural, or pedagogical weaknesses.

Future research should therefore prioritize longitudinal and real-world studies, culturally diverse samples, interoperable platforms, reproducible AI workflows, and combined behavioral, physiological, qualitative, and performance-based evidence. Ethical issues—including authorship, bias, privacy, cultural authority, and the risk of decontextualization—must also become integral to system design and evaluation.

4 Conclusion

This Research Topic demonstrates that AI and immersive interaction technologies can support cultural preservation, digital design, and education when they are integrated with embodied experience, reflective meaning-making, accessibility, and rigorous evaluation. The contributions collectively move the field from technology-centered experimentation toward human-centered, culturally resonant, and evidence-based innovation. We hope they encourage further collaboration among computer scientists, designers, heritage professionals, educators, psychologists, and policymakers in developing digital experiences that are not only intelligent and immersive, but also inclusive, sustainable, and socially meaningful.

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Footnotes

Edited and reviewed by: Kostas Karpouzis, Panteion University, Greece