In the original publication by Uta et al [...]

This paper proposes a hybrid Artificial Intelligence-gamification model and algorithm designed to enhance patient education and engagement in smart healthcare applications and systems, with a broader application in general e-Learning and classical educational environments. By seamlessly integrating traditional gamification elements and Artificial Intelligence driven personalization of rewarding systems. The primary contribution is the development of an algorithm that optimizes user engagement in the educational process. The algorithm lays the groundwork for future applications that promote self-directed learning.

In this paper, we present a conceptual design framework for developing immersive learning experiences at scale with generative AI and extended reality (XR) for primary and secondary education. Based on the synthesis of current literature, our framework asserts a practical five-step pipeline: curriculum ingestion, AI-powered blueprinting, asset assembly, educator review, and classroom deployment with formative assessment. The model is designed to be flexible, focusing on narrative and gamification for primary students, moving on to sophisticated simulations and analytical activities for secondary students. We place this framework into the context of recent developments in generative 3D models, bridging fundamental technical and ethical gaps between concept and classroom practice. Finally, we summarize a prioritized research agenda around evaluation, access, and teacher workflows to enable near-term pilot studies. This work is intended to inform educators, researchers, and stakeholders who are interested in implementing effective AI-XR solutions in schools in a pedagogically sound way.

Although emerging technologies are increasingly adopted in teaching and learning, their potential to enhance educational administration remains underexplored. In particular, few studies examine how conversational agents, virtual reality (VR), and robotic process automation (RPA) can jointly streamline administrative workflows in multilingual and multicultural university environments. This study addresses this gap by presenting an integrated solution deployed on the website of an engineering faculty where programs are delivered in foreign languages. The proposed system combines a multilingual chatbot, a VR-based administrative guide and virtual tour, and RPA modules supporting certificate generation, password resets, and exam scheduling. Through an A/B usability test, usage analytics, and qualitative feedback, we evaluate the effectiveness of these technologies in improving access to information, reducing response time, and lowering administrative workload. Results show that this triad significantly enhances efficiency and student experience, particularly for international students requiring continuous support. The paper contributes a replicable model for leveraging emerging technologies in educational administration and offers insights for institutions seeking scalable and student-centered digital transformation.

Contribution: This systematic review identifies important trends, difficulties, and possibilities covered in recent research by looking at the literature on new technologies (VR, AR, and MR) in immersive learning. An organized overview of the current state of the area is provided by the categorization of the findings.Background: The use of immersive technologies such as Mixed Reality (MR), Augmented Reality (AR), and Virtual Reality (VR) holds great promise for revolutionizing teaching approaches. Even with increased interest, a comprehensive picture of the situation is still required, considering adoption barriers and pedagogical factors. From engineering and healthcare education to teacher training, recent assessments demonstrate the growing potential and usage of these technologies in a mixture of educational fields.Problem Addressed: A comprehensive synthesis that highlights the general trends, common issues (such as cost, accessibility, training, technical limitations, and pedagogy), and opportunities across various educational levels—identified in both individual studies and other systematic reviews—is necessary, even though many studies focus on applications or aspects of VR, AR, and MR in education.Research Questions: 1) What are the main patterns in taking advantage of VR, AR, and MR in immersive learning environments? 2) What are the main obstacles to the successful integration and broad use of these technologies in the classroom? 3) What are the main ways in which these technologies can improve learning outcomes and experiences?Methodology: Following the guidelines of a systematic review, this study’s steps included discovering pertinent literature (depending on the original paper’s scope), gathering information about trends, opportunities, and problems, and synthesizing the results considering the research questions. Methodologies employed in comparable systematic reviews within the area are reflected in this procedure.Findings: The review validates robust trends in immersive technology for individualized education, skills training in domains such as engineering and medicine, and experiential learning. Technical obstacles, exorbitant expenses, the requirement for teacher preparation, pedagogical integration difficulties, and equity issues about the digital divide are among the major problems that are frequently mentioned. Significant opportunities exist to improve student motivation and engagement, offer secure practice simulation settings, support the understanding of difficult ideas, and open the door for innovative teaching strategies. To ensure successful implementation, rigorous pedagogical design and sufficient infrastructural support are essential.

Artificial Intelligence (AI) is increasingly used to enhance project management practices, especially in risk analysis, where traditional tools often lack predictive capabilities. This study introduces an AI-based tool that supports project teams in identifying and interpreting risks through machine learning and integrated documentation features. A synthetic dataset of 5000 project instances was generated using deterministic rules across 27 input variables, enabling the training of multi-output Decision Tree and Random Forest models to predict risk type, impact, probability, and response strategy. Due to the rule-based structure of the dataset, both models achieved near-perfect classification performance, with Random Forest showing slightly better regression accuracy. These results validate the modelling pipeline but should not be interpreted as real-world predictive accuracy. The trained models were deployed within a web platform offering prediction visualization, automated PDF reporting, result storage, and access to a structured risk management plan template. Survey feedback highlights strong user interest in AI-assisted mitigation suggestions, dashboards, notifications, and mobile access. The findings demonstrate the potential of AI to improve proactive risk assessment and decision-making in project environments.

Appears in: INTED2024 Proceedings Publication year: 2024Pages: 7208-7217ISBN: 978-84-09-59215-9ISSN: 2340-1079doi: 10.21125/inted.2024.1898Conference name: 18th International Technology, Education and Development ConferenceDates: 4-6 March, 2024Location: Valencia, Spain

Several employment challenges may be overcome with career services, among other actions provided by higher education institutions. The chapter analyzes the diversity of career services that are usually delivered by the career guidance centers organized within higher education institutions. Many examples of career services are provided, based on the professional expertise of the authors, involved in developing career services with their university as well as at the regional level. The analysis is conducted using different service characteristics such as the following: novelty, duration, format, communication, feedback, digitalized degree, and requiring specialists' supervision. Based on this analysis, several conclusions are drawn, including recommendations for efficient organization of the career guidance centers within higher education institutions.

Appears in: INTED2024 Proceedings Publication year: 2024Pages: 2645-2653ISBN: 978-84-09-59215-9ISSN: 2340-1079doi: 10.21125/inted.2024.0735Conference name: 18th International Technology, Education and Development ConferenceDates: 4-6 March, 2024Location: Valencia, Spain

Educational institutions are struggling to keep up with the accelerated technological advancements; hence, sustainable and supportive tools have become essential to reshape traditional models into intelligent learning systems. This paper introduces Lib2Life, a digital library that uses advanced Natural Language Processing techniques to facilitate the digital transformation of historical documents provided by Central University Libraries in Romania. The platform enables Central University Libraries in Romania to preserve the cultural heritage of historically valuable documents, facilitating open-source access to old, printed materials such as books, manuscripts, newspapers, or literary magazines no longer protected by copyright. Lib2Life offers comprehensive functionalities, allowing librarians to benefit from automated text processing and indexing workflows that facilitate digitization, ensuring a consistent representation of original documents. For readers, the platform presents a user-friendly interface with semantic search capabilities and a recommendation engine. The system employs an ontology to organize and manage documents in a unified and structured way, contributing to the evolution of intelligent education technologies. The innovative contributions of Lib2Lifeinclude identifying new solutions for cultural heritage preservation, promoting patrimony through modern methodologies, increasing access to documentary resources, enhancing library services, and fostering the transfer of knowledge and technology to society.

The worldwide increase in the number of disorders requiring rehabilitation is weighing more and more on healthcare systems, seriously affecting the quality of life of patients. Emergent technologies and techniques should be used more and more in both physical and psychological rehabilitation, after a thorough study of their potential and effects. Our paper presents an original virtual reality-based system including gamified immersive physio-psychological exercises, which was tested in a clinical setting with 25 patients suffering from various musculoskeletal, neuromotor, or mental disorders. A thorough testing protocol was followed during a two-week period, including repeated trials, progress tracking, and objective and subjective instruments used for data collection. A statistical analysis helped us identify interesting correlations between complex virtual reality games and people’s performance, and the high level of relaxation and stress relief (4.57 out of 5 across all games) which can be offered by VR-based psychotherapy exercises, as well as the increased ease of use (4.26 out of 5 perceived across all games) of properly designed training exercises regardless of patients’ level of VR experience (84% of patients with no or low experience and no patient with high experience).

The technology innovation, especially in the case of artificial intelligence, has significantly transformed the work processes and how they are organised and performed. Even if the adoption of advanced technologies usually leads to a higher work performance, there are risks of negative disruptions in the working systems, such as non-ethical use and social negative effects. The paper presents the results of an ethnographic research conducted by the authors, with the objective to identify the impact of the artificial intelligence adoption in the workplace on the professional knowledge and skills requirements and on the upskilling and reskilling strategies. Three different domains were considered: information technology, education, and scientific research. One relevant conclusion of the research is that knowledge and skills requirements should be studied from multiple perspectives, such as profession dynamics, not only from the technology innovation perspective. The research originality mainly consists in the way in which the concept of the level of upskilling/reskilling importance is defined and applied, based on professional knowledge and skills development requirements. By using the assessed level of upskilling/reskilling importance, strategies and related actions may be defined and undertaken. By substantiating this manner of setting up the upskilling and reskilling strategies and actions, the research has a theoretical and practical impact in the domain of talent management.

In the rapidly evolving field of education, emerging technologies are increasingly reshaping how learning takes place. Virtual reality (VR) allows users to fully immerse themselves in simulated worlds, giving them the impression that they are in a completely different environment. This article examines how immersive, interactive virtual reality environments are narrowing the gap between theoretical knowledge and practical application, impacting traditional teaching methods and how using modern technology can improve the quality of education even more. The study also highlights the CareProfSys research project, which demonstrates how VR can transform education and better prepare students for today's jobs by combining VR, AI, and data analysis to develop personalized career counselling.

The increase in the prevalence of mental health issues, especially anxiety and depressive disorders, has encouraged research focused on the benefits brought by emergent technologies as psychotherapy tools. Our current paper showcases the potential brought by virtual reality for digital health, and in particular for psychotherapy. We are focusing on the design process of various immersive virtual reality (VR) exercises for anxiety reduction, describing their medical purpose, functionalities, scene design and gamification principles. We are then presenting a user experience experiment comparing VR interaction practices in an anxiety management exercise in order to understand the following steps needed to implement the proposed exercises.

The current paper describes an innovative career recommendation module embedded into a web platform developed with emergent technologies. The recommendation algorithm bases its strength on semantic data and on HermiT inference capabilities. An ontology aligned with well-known occupational classifications, such as ESCO, O*NET or COR is the core of the recommendation process, which was designed to especially support students who are in high school, college or have recently graduated university, with no work experience so far and no capacity to match the occupational nomenclature from the labor market with their own competencies and profile. To perform the ontological inference-based recommendation, the user profile must be created, using a form-extraction mechanism which provides relevant educational background and psychological traits. Due to the current technological revolution and to the continuous change in the range of professional occupations, our proposed recommender has become a useful career guidance tool, fact supported by preliminary user testing experiments.

This paper presents an innovative use case of virtual reality (VR) for career development and exploration, within the context of the CareProfSys recommendation system for professions. The recommender users receive recommendations not only in textual format but as WebVR gamified scenarios as well, having thus the possibility to try activities specific to the suggested professions and decide whether they are suitable for them or not. This paper describes, from a functional and technical point of view, scenarios for six different jobs: computer network specialists, civil engineers, web and multimedia developers, chemical engineers, project managers, and university professors. Extended experiments were performed, using an internal protocol, with 47 students enrolled in engineering studies. The results of the experiments were measured with the aid of four instruments: two questionnaires, one unstructured interview, and the VR simulation performance recording module. Positive results were obtained: the users admitted that such a tool was useful when choosing one’s career and that it was entertaining. Most of the students considered the VR scenarios as learning or testing experiences, too. Thus, we claim that a VR form of providing job recommendations is more appealing to young people and brings value to career development initiatives.

A primary challenge for digital library systems when digitizing millions of volumes is to automatically analyze and group the huge document collection by categories while identifying patterns and extracting the main themes. A common method to be leveraged on unlabeled texts is topic modeling. Given the wide range of datasets and evaluation criteria used by researchers, comparing the performance and outputs of existing unsupervised algorithms is a complex task. This paper introduces a domain-based topic modeling evaluation applied to Romanian documents. Several variants of Latent Dirichlet Allocation (LDA) combined with dimensionality reduction techniques were compared to Transformer-based models for topic modeling. Experiments were conducted on two datasets of varying text lengths: abstracts of novels and full-text documents. Evaluations were performed against coherence and silhouette scores, while the validation considered classification and clustering tasks. Results highlighted meaningful topics extracted from both datasets.

The current paper proposes a new recommender system for jobs, useful in early career paths for engineering graduates, which matches users' competences developed in higher education institutions to suitable professions from current modern industrial landscape. The strengths of the proposed software lay in the machine learning-based recommendation algorithm, the integration of latest web technologies and the wide collection of data sources used to build users' profiles. The system is presented in the framework of other recommender systems developed for making career choices.

Professionalization of work represents the process of transforming an occupation into a profession with a high degree of integrity and competence, requiring the existence of professional qualification frameworks, standards, and nomenclatures to describe the necessary skills, abilities, and education for an individual to have a fruitful career. The current study provides details on professions from the engineering domain that are modeled using a prototype ontology tailored to the context of Industry 4.0 in the Romanian landscape. Our ontology represents the foundations for providing personalized recommendations to find suitable professions in the Romanian job market while illustrating the importance of AI tools to support career development.