This book compiles the proceedings of the 9th International Conference on Smart Learning Environments (ICSLE 2025), hosted by the University of Eastern Finland in Joensuu (October 1617, 2025). The conference brings together researchers, practitioners, and policymakers to examine how rapid technological evolution reshapes learning and teaching, the transformative role of AI in education, and strategies for safe and ethical human-machine collaboration. The topics cover: Next generation learning environments; Collaboration among humans, human-machine collaboration, interactions or dynamics; Pedagogy, learning approaches and instructional design; Digital transformation for catalyzing online, immersive and open learning spaces; and Digital, machine and AI ethics in education.

Integrates Nordic pedagogical innovation with global ethics frameworks Pioneers "algorithmic sovereignty" for learners Validates human-AI synergy through VR field labs

Autorentext

Dr. Sonsoles López-Pernas is an Academy Fellow at the University of Eastern Finland, where she has worked since 2022 as a member of the Learning Analytics unit. She obtained her PhD in Engineering at Universidad Politécnica de Madrid (Spain). Her research interests are in learning analytics, human-AI interactions, game-based learning in engineering and computer science education, among others. She is skilled in quantitative methods that include process and sequence mining, network analysis, complex event processing, and data visualization, which are proven by over 150 publications in the field of learning analytics and education technology as well as workplace achievements.

Dejian Liu is a Senior Engineer graduated from the University of Kansas, the United States of America, and received a Ph.D. degree from Beijing Normal University, China in 2020. He is also the Founder, Chairman, and Executive Director of NetDragon Websoft Holdings Limited, which he has led since its inception in 1999. A pioneer in the convergence of technology and pedagogy, Dr. Liu's research encompasses educational technology, smart learning environments, human-computer interaction, and design methodology.

Dr. Kamila Misiejuk is currently a Postdoctoral Researcher at the Center of Advanced Technology for Assisted Learning and Predictive Analytics (CATALPA), FernUniversität in Hagen, Germany. She obtained a PhD degree in Learning Analytics from the University of Bergen in Norway. She has published on a wide range of topics, including peer assessment, human-AI interaction, learning analytics, and the role of generative artificial intelligence in education.

Dr. Ahmed Tlili is an Associate Professor at Beijing Normal University in China, and holds adjunct and visiting professor positions at other international universities. He is also Co-Director of the Open Educational Resources (OER) Lab at the Smart Learning Institute of Beijing Normal University.

Dr. Mohammed Saqr is a Professor of Computer Science at the School of Computing, University of Eastern Finland, where he leads the university's Learning Analytics Unit. Under his leadership, the unit has become one of Europe's most productive learning analytics laboratories. Prof. Saqr earned his PhD in Learning Analytics from Stockholm University, followed by a postdoctoral appointment at Université Paris Cité. He later received the title of Docent in Learning Analytics from the University of Oulu.

Dr. Sami Heikkinen holds a PhD in Computer Science with a specialization in learning analytics and self-regulated learning. His research focuses on applying computational methods to understand and enhance learning processes, particularly in digital educational environments. He works as a Senior Lecturer at LAB University of Applied Sciences.

Ronghuai Huang is a Professor in the Faculty of Education at Beijing Normal University (BNU), China, and holds multiple prestigious roles in the field. He is currently the Co-Dean of BNU's Smart Learning Institute, the Director of the National Engineering Research Center of Cyberlearning and Intelligent Technology, and the Director of the Educational Informatization Strategy Research Base in Beijing, under the Ministry of Education of the People's Republic of China.

Dr. Kinshuk, who goes by a single name, is a dean at the College of Information and professor in the department of learning technologies at the University of North Texas, the United States of America. His research and activities of interest include learning analytics, learning technologies, mobile, ubiquitous, and location aware learning systems, cognitive profiling, and interactive technologies.

Inhalt

Part 1: Introduction.- Chapter 1. The Changing Landscape of Smart Learning Environments at the Intersection of Pedagogy, Collaborative Intelligence, and Ethics (López-Pernas, Liu, Misiejuk, Tlili, Saqr, Heikkinen, Huang, and Kinshuk).- Part 2: Human-AI collaboration in education.- Chapter 2. Capturing the self-regulation process of students' AI interactions while using formative assessment (Prieto, Pernas, Arias, Gonzalez and Huertas, Saqr).- Chapter 3. Reframing AI Agency in Education: Teachers' Perspectives on Epistemic, Functional, and Emotional Dimensions (Zhang, Yang, Da, Tlili, Wang and Li).- Chapter 4. GenAI as a Cognitive Partner in Adult Discovery Learning: Ethical and Technical Considerations (Adarkwah).- Chapter 5. Scaffolding Learning with AI: Pre-service Teachers' Experiences in Teacher Education (Sini, Kukkonen, Pöntinen, Heiskanen and Valtonen).- Chapter 6. Student-AI interactions when Seeking Feedback on Programming Assignments (Arpack, Kayaduman, Kurun, López-Pernas and Saqr).- Chapter 7. A Process-oriented View of Human-AI Interactions: Comparing Argumentative vs. Creative Writing (López-Pernas, Misiejuk, Griskova-Bulanova, Emara, Siddika, and Saqr).- Chapter 8. Working with Generative AI: Longitudinal Evolution of Cognitive Effort and Critical Thinking across Time (Siddika, López-Pernas, Arriaga-Prieto, Zhang, Wang, Ren, Gurung, Gebremichael and Saqr).- Chapter 9. Towards transformative AI education through crossboundary co-design (Vartiainen and Tedre).- Chapter 10. Self-Regulated Learning in AI-Supported Peer Feedback: A Multi-Modal Case Study (Zhang).- Chapter 11. Guiding Inquiry Without Giving Answers: Experiences of Pedagogically Designed Chatbot in Teacher Education (Valtonen, Viik, Erikson, Kärkkäinen, Kontkanen and Hirsto).- Chapter 12. Pre-Service Teachers' Perceptions of Pedagogical AI Chatbots: Perceived Contextual Usefulness, Ease of Use and AI Anxiety (Viik, Valtonen, Hirsto, Kärkkäinen, Eriksson and Jari ukkonen).- Part 3: Learning analytics.- Chapter 13. Uncovering Dynamics of Programming Competency Dimensions: A Multi-channel Modeling in CS1 (Wang , Gao, Yan, Wang, Saqr, and Feng).- Chapter 14. Exploring Idiographic Learning Analytics in Master's Thesis Writing: A Transition Network Approach (Ito).- Chapter 15. High-Order MCQ Generation through Few-Shot and Chain-of-Thought for Formative Assessment (Yan, Al-Shamali and Lin).- Chapter 16. Assessing AI-Driven Learning Analytics Recommendations: Comparative Analysis of RAG and vanilla LLaMA (Elmoazen, López-Pernas, Emara, Belayachi and Mohammed Saqr).- Chapter 17. Behind Schedule - Capturing the Effects and Side Effects of an Intervention on the Learning Process (Heikkinen, Bellhäuser, Stappen and Saqr).- Chapter 18. Correction, Overcorrection or New Reality: AI Portrays Girls as Better Learners, Self-regulated, and on par with Boys in STEM Fields (Saqr, Misiejuk, Oliveira, Saqr, Vogelsmeier and López-Pernas).- Chapter 19. No Gender Differences in Math Performance, Perception, Feeling of Difficulty, or Interplay Between Them in Czech Kids (Saqr, Spitzer, Tlili, Saqr and López-Pernas).- Chapter 20. Writing under pressure: How time-induced stress and cognitive load shape student writing style (Oliveira, Misiejuk, López-Pernas, Rawal and Saqr).- Chapter 21. JTNA: A Desktop Softwa…