Description
(Text)
This three-volume set CCIS 2590-2592 constitutes poster papers and late breaking results, workshops and tutorials, practitioners, industry and policy track, doctoral consortium, blue sky and wideAIED papers presented at the 26th International Conference on Artificial Intelligence in Education, AIED 2025, held in Palermo, Italy, during July 22 26, 2025. The 72 full papers and 73 short papers (72 of them presented as posters) presented in this book were carefully reviewed and selected from 296 submissions. They are organized in topical sections as follows: Part I: BlueSky; Practitioners, Industry and Policy; WideAIED; Doctoral Consortium. Part II: Late Breaking Results; Part III: Late Breaking Results; Workshops and Tutorials.
(Table of content)
.- BlueSky.
.- CLJ4AI: Citizen Learning Journey for AI.
.- Why the Future of AIED is Causal: Arguments for Creating a Tradition Based on Causal Thinking.
.- Pedagogy-driven Evaluation of Generative AI-powered Intelligent Tutoring Systems.
.- AI in Educational Digital Escape Rooms: State of the Art and Perspectives.
.- On the role of domain experts in creating effective tutoring systems.
.- Practitioners, Industry and Policy.
.- SchrijfBlik: Safeguarding the validity of writing assessment in the age of AI.
.- AMELIA: An AI teaching assistant for equitable STEM Education in Rural Peru.
.- MindMate: An LLM-Powered Mental Health Companion for Adolescents.
.- A Conversational Tool Based on Knowledge Graph, LLMs and BERT Model for Work-Study Programs in France.
.- From Insights to Impact: An Agentic Learning Intelligence Framework for Student-Centred Success.
.- Pilot Study of Self-explanation Based Automate Stuck Point Detection and PersonalizedFeed-back Recommendation by Educational eXplainable AI Tool in Middle School Math Classes.
.- Building Effective Safety Guardrails in AI Education Tools.
.- A Gateway for Egalitarian Access to LLM Based Resources.
.- Systematic Control of Multiple-Choice Item Difficulty through LLM-Based Distractor Generation.
.- Towards Actionable GenAI-Classroom Integration: A Social Role Framework for Teacher s Practice.
.- SCRIPT: Implementing an Intelligent Tutoring System for Programming in a German University Context.
.- WideAIED
.- AI Coding Assistants in Competitive Programming: Empirical Studies from India on Human-AI Interactions in Learning, Problem Solving, and Curiosity Development Perspectives.
.- Gamified Intelligent Communities of Practice: A Path To Support Underprivileged Teachers.
.- Artificial Intelligence and Public Education Policy: Improving Textbook Evaluation in Brazil.
.- Prediction of Online Mathematics Test Efficiency Based on StackedIntegrated Models: A Case Study of NAEP Data.
.- Structural and Semantic Analysis Techniques for Translation Evaluation of Educational Materials.
.- Advancing MOOCs Personalization: The Role of Generative AI in Adaptive Learning Environments.
.- Does the Early Bird Get the Worms? K -12 Teachers Perceptions on the Use of Generative Artificial Intelligence in Chinese Classrooms.
.- MAS-CPS Assessor: A System for Evaluating Collaborative Problem-Solving Skills in Multi-Agent Environments.
.- Doctoral Consortium
.- Evaluating the Impact of LLM-Generated Assignment Report Summaries in Intelligent Tutoring Systems.
.- Fair for whom? Investigating school identity, algorithmic fairness, and educational technologies.
.- Fine-tuning Large Language Models for Knowledge Tracing Harnessing Insights from Explainable AI.
.- Assessing the Effectiveness of GenAI Tutoring for Tertiary Academic Probation Students: A Repeated Measures Study using ChatGPT.
.- AI-Powered Classification of Medical Students Professionalism Profiles.
.- Identifying and Fostering Self-Regulated Learning Among Computer Programmers Using Artificial Intelligence Systems.
.- Personality-Aware Conversational Intelligent Tutoring System with GenAI: Studying the effect on Learners in Introductory Programming.
.- Perceptions of Secondary School Students Solving Math Word Problems in a Foreign Language with GenAI Support.
.- Designing An Ethical Framework for the Integration of Generative AI in Higher Education: Balancing Stake-holder Interests and Enhancing Learning Outcomes.
.- Augmenting LLM Generated Feedback with Data Mining.
.- Towards
