1. Exploring student perspectives on e-learning in nursing educationMirko Prosen, Sabina Ličen, 2025, independent scientific component part or a chapter in a monograph Abstract: E-learning has rapidly gained prominence in nursing education, offering flexible alternatives to traditional learning. This study aimed to explore nursing students’ experiences with e-learning, focusing on perceived benefits, challenges, and its impact on skill acquisition. Using a qualitative design, data were collected from four face-to-face focus groups comprising 20 nursing students. Thematic analysis was employed to examine the data, yielding six key themes: Flexibility and accessibility benefits, Impact on student engagement and interaction, Technological and infrastructure challenges, Effect on practical skills and learning outcomes, Diverse preferences in learning approaches, and Self-management and motivation in e-learning. The findings indicate that, while e-learning provides accessibility and flexibility, it poses challenges in practical skill development and engagement. This study emphasises the need for adaptive e-learning models to meet diverse learning requirements effectively.
Keywords: online learning, blended learning, thematic analysis, skill development, student engagement
Published in RUP: 22.12.2025; Views: 162; Downloads: 0
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2. Integrating AI-driven wearable metaverse technologies into ubiquitous blended learning : a framework based on embodied interaction and multi-agent collaborationJiaqi Xu, Xuesong Zhai, Nian-Shing Chen, Usman Ghani, Andreja Istenič, Junyi Xin, 2025, original scientific article Abstract: Ubiquitous blended learning, leveraging mobile devices, has democratized education by enabling autonomous and readily accessible knowledge acquisition. However, its reliance on traditional interfaces often limits learner immersion and meaningful interaction. The emergence of the wearable metaverse offers a compelling solution, promising enhanced multisensory experiences and adaptable learning environments that transcend the constraints of conventional ubiquitous learning. This research proposes a novel framework for ubiquitous blended learning in the wearable metaverse, aiming to address critical challenges, such as multi-source data fusion, effective human–computer collaboration, and efficient rendering on resource-constrained wearable devices, through the integration of embodied interaction and multi-agent collaboration. This framework leverages a real-time multi-modal data analysis architecture, powered by the MobileNetV4 and xLSTM neural networks, to facilitate the dynamic understanding of the learner’s context and environment. Furthermore, we introduced a multi-agent interaction model, utilizing CrewAI and spatio-temporal graph neural networks, to orchestrate collaborative learning experiences and provide personalized guidance. Finally, we incorporated lightweight SLAM algorithms, augmented using visual perception techniques, to enable accurate spatial awareness and seamless navigation within the metaverse environment. This innovative framework aims to create immersive, scalable, and cost-effective learning spaces within the wearable metaverse.
Keywords: metaverse, embodied interaction, wearable, multi-agent, artificial intelligence, ubiquitous blended learning
Published in RUP: 17.07.2025; Views: 735; Downloads: 8
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3. From virtual worlds to real connections : investigating the effects of virtual reality on positive interdependence in language learning and teachingIlaria Compagnoni, 2024, doctoral dissertation Keywords: Italian as a foreign language, task-based language learning, virtual reality, teacher training, positive interdependence, digital storytelling, blended learning, instructional design, dissertations
Published in RUP: 31.01.2025; Views: 1268; Downloads: 28
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