Patient-reported outcomes (PROs) and their use in the clinical workflow can improve cancer survivors’ outcomes and quality of life. However, there are several challenges regarding efficient collection of the patient-reported outcomes and their integration into the clinical workflow. Patient adherence and interoperability are recognized as main barriers. This work implements a cancer-related study which interconnects artificial intelligence (spoken language algorithms, conversational intelligence) and natural sciences (embodied conversational agents) to create an omni-comprehensive system enabling symmetric computer-mediated interaction. Its goal is to collect patient information and integrate it into clinical routine as digital patient resources (the Fast Healthcare Interoperability Resources). To further increase convenience and simplicity of the data collection, a multimodal sensing network is delivered. In this paper, we introduce the main components of the system, including the mHealth application, the Open Health Connect platform, and algorithms to deliver speech enabled 3D embodied conversational agent to interact with the cancer survivors in five different languages. The system integrates cancer patients’ reported information as patient gathered health data into their digital clinical record. The value and impact of the integration will be further evaluated in the clinical study.

The integration of Artificial Intelligence into education is transforming how abstract and complex concepts are delivered, especially through embodied tools like social robots. This study examines the impact of AlphaMini, a Slovenian-speaking social robot supported by model ChatGPT 4o and trained on structured book-based content, on student engagement during knowledge management lessons. A case study approach was used, including student questionnaires, classroom observations, and post-session discussions, with 70 university students from diverse academic fields. Engagement was assessed across behavioral, emotional, and cognitive dimensions, with comparisons based on prior robot experience. Results show AlphaMini significantly enhanced emotional and behavioral engagement, with moderate cognitive gains. Students familiar with social robots demonstrated higher engagement, interacting more naturally and actively. Informal feedback highlighted positive attitudes toward AlphaMini, especially among students who regularly use generative AI tools like ChatGPT or Copilot. Participants appreciated its human-like gestures, Slovenian language use, and emotionally supportive presence. Many suggested its potential use in primary and inclusive education, where emotional safety and playful interaction are crucial. This study contributes to the growing evidence on AI in education, showing that combining generative AI with social robotics can foster motivation, participation, and emotionally rich learning experiences.

The rapid emergence of generative artificial intelligence (GenAI) technologies such as ChatGPT, Microsoft Copilot, and Canva AI is driving profound changes in educational leadership and administration. This qualitative study examines how Slovenian school leaders perceive and use GenAI in their work and which opportunities, risks, and support needs they identify. Drawing on four focus groups across primary, secondary, and higher education within the national project ”Generative artificial intelligence”,, we used a qualitative methodology; explicitly a reflexive thematic analysis in ATLAS.ti. We identifed five main themes: (i) pragmatic, low-risk adoption focused on administrative efficiency; (ii) uneven AI literacy and demand for hands-on professional development; (iii) ethical and legal concerns (GDPR/EU AI Act) around privacy, authorship, and transparency; (iv) infrastructural and cost constraints limiting high-stakes use; and (v) emergent opportunities for data-informed decision-making and individualized support. We theorize these patterns using Diffusion of Innovations and Technology Acceptance perspectives to explain why administrative use predominates and pedagogical integration remains tentative. Findings show that GenAI is predominantly used for streamlining administrative work, document preparation, and routine communication. Its application in teaching and learning remains limited and experimental. Participants highlighted both the benefits of GenAI such as increased efficiency, support for creative work, and potential for individualized learning and a range of persistent challenges, including gaps in digital literacy, concerns over data privacy and academic integrity, and unequal access to advanced technologies. The study draws on Diffusion of Innovations, the Technology Acceptance Model, Sensemaking Theory, Educational Change Theory, and Distributed Leadership to explain how school leaders interpret and implement GenAI in practice. We offer actionable implications for leadership development, assessment redesign, and policy aligned with the EU AI Act. The contribution is a leadership-centred, EU-contextualized account that clarifies conditions under which GenAI currently shifts not replaces leadership practice.

Branje v sodobnem digitalnem okolju poteka v kontekstu algoritmično posredovanih informacijskih tokov, v katerih umetna inteligenca vse pogosteje deluje kot nevidni, a strukturni dejavnik bralnega procesa. Algoritmi filtriranja, personalizacije in generiranja besedil ne vplivajo zgolj na dostop do informacij, temveč tudi na pogoje njihove interpretacije, kar postavlja pod vprašaj ustaljene modele bralnega razumevanja. Namen prispevka je konceptualno osvetliti vlogo umetne inteligence v branju ter razviti teoretski okvir kritične bralne pismenosti v algoritmiziranem okolju. Prispevek temelji na analitičnem pregledu raziskav s področja digitalnega branja, novih pismenosti in umetne inteligence v izobraževanju ter na konceptualni sintezi teh izhodišč. Umetna inteligenca je razumljena kot pedagoška motnja, ki v bralni proces vnaša epistemološke, interpretativne in metakognitivne razkorake ter omogoča reflektirano obravnavo besedil. Ključni rezultat je model kritične bralne pismenosti, ki povezuje epistemološko zavest, razumevanje algoritmičnega vpliva, kritično presojo virov, poglobljeno interpretacijo besedil in metakognitivno refleksijo. Model ponuja izhodišče za razmislek o poučevanju branja v osnovnošolskem kontekstu ter za nadaljnje empirične in didaktične raziskave.

The quasi-experimental study examines the role of contemporary technologies, such as artificial intelligence and humanoid robots, in enhancing sustainability education for future teachers, emphasizing their impact on shaping sustainable beliefs in future generations. Involving 112 pre-service teachers, the research compares various contemporary and traditional learning methods. Pre- and post-test evaluations were conducted to assess changes in participants’ understanding of sustainability concepts and the variability of their responses. Results reveal significant improvements in sustainability awareness, with methods involving humanoid robots showing higher response variability. The study also identifies the development of new literacies crucial for effectively utilizing advanced technologies in promoting environmental sustainability. While artificial intelligence and humanoid robots match the efficacy of traditional methods, they notably engage young educators more effectively in sustainability topics. These findings highlight the need to integrate such technologies into educational framework to deepen the understanding of environmental issues and prepare youth for future challenges. However, further research is required to explore long-term effects and broader demographics. The research contributes significantly to educational technology and sustainability in education, showcasing the transformative potential of incorporating contemporary technologies in educational settings.