Blanchard / Chen / Chi Artificial Intelligence in Education

27th International Conference, AIED 2026, Seoul, South Korea, June 27–July 3, 2026, Proceedings, Part VI
Erscheinungsjahr 2026
ISBN: 978-3-032-29773-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 491 Seiten

Reihe: Lecture Notes in Artificial Intelligence

This six-volume set LNAI constitutes the refereed proceedings of the 27th International Conference on Artificial Intelligence in Education, AIED 2026, held in Seoul, South Korea, during June 27–July 3, 2026.

The 143 full papers and 165 short papers presented in this book were carefully reviewed and selected from 1241 submissions.

• The conference program comprises seven thematic tracks:
  Track 1: Technical Aspects of AIED
  Track 2: Human Aspects of AIED
  Track 3: Societal Aspects of AIED

This year's theme, "From tools to teammates: human-AI synergy for Augmented Learning" , highlights research on human and AI agency, collaborative intelligence, and human & AI co-evolving. 

Zielgruppe

Research

Autoren/Hrsg.

Blanchard, Emmanuel G.

Chen, Guanliang

Chi, Min

Isotani, Seiji

Inhaltsverzeichnis

.- Scaffolding Critical Engagement with GenAI: Transforming Ethnic Minority Preparatory Students’ Collaborative
Discourse in Prompt Engineering Tasks.
.- From Verdicts to Maps: Reimagining AI Assessment for ADHD through a Strength-Based Lens.
.- BRIDGE the Gap: Mitigating Bias Amplification in Automated  Scoring of English Language Learners via Inter-group Data
Augmentation.
.- Decomposing the Fairness Gap: Disentangling Data Scarcity from Validity Bias in AI-Driven Formative Assessment.
.- From Barriers to Actions: A Thematic Analysis of Teachers’ Perceived Obstacles and Support Needs for AI Integration in
K–12 Education.
.- How Students Interpret Representational Cues in AI-Generated Educational Illustrations.
.- Evaluating the Impact of Workshop Interventions on AI Literacy and STEM Career Aspirations with Australian
Secondary Students.
.- Implementing a Statewide AI Curriculum: One Brazilian Experience.
.- Modernizing Ground Truth: Four Shifts Toward Improving Reliability and Validity in AI in Education.
.- From Tool to Teammate? Negotiating Accountability and Disclosure in Academic Generative AI Use.
.- Mapping AI Literacy: How Do DigComp 3.0 and OECD/EC AILit  Inform K–12 Curriculum Integration Decisions?.
.- A Benchmark for Gender Bias in Large Language Model Feedback on Student Essays.
.- Supporting the Text Entry of nêhiyawêwin for Lifelong Learners.
.- Toward Fair and Scalable Assessment of Socially Shared Regulation of Learning with Large Language Models.
.- From Ethical Discourse to Empirical Evidence: How Ethical Concerns Are Operationalized in Studies on Generative AI in
Higher Education.
.- Territorial Fairness in Large-Scale Academic Risk Prediction: Comparing National and State-Level Machine
Learning Models in Brazil.
.- What Children’s AI Literacy Books Teach: A Content Analysis Using the AI4K12 Framework.
.- Community Futures: Hybrid and Situated Critical AI Literacy.
.- What Constitutes AI Harms and/or Unfairness? An Empirical Analysis of Teacher Deliberation with a Fairness
Elicitation Scaffold.
.- A Survey of AI Misconception and Adoption Among Indonesian K-12 Teachers.
.- Mapping AI Literacy in Medical Education: A Review of Concepts and Teaching Practices.
.- Identifying High-Confidence Social Biases in LLMs for Trustworthy Conversational Tutoring Agents.
.- When LLMs Give Voting Advice: Bias, Coherence, and Educational Risk.
.- Personalization over Privacy? Implications of the Privacy-Personalization Trade-Off on Future Use of
Intelligent Tutoring Systems.
.- Introducing Adolescents to the Social Dimensions of AI through Story-Driven Game-Based Learning.
.- Implicit and Explicit Bias Toward English Language Learners in LLM-based Essay Scoring: A Mechanistic Interpretability
Analysis.
.- Biblometrics Insights on the Trends of Artificial Intelligence and Educational Commercialization in Early Childhood Educational Research.
.- Students, AI, and the Future of Higher Education: A Scoping Review of Perceptions and Concerns.
.- Decoding Student Dialogue: A Multi-Dimensional Benchmark and Bias Analysis of Large Language Models as Annotation
Tools.
.- Measuring AI Leadership in Education: Development and Validation of the AI Educational Leadership Scale (AIELS)
for Chinese Educational Leaders.
.- From Speculation to Evaluation: Exploring Values in Design Fictions about AI-Enhanced Education.
.- Offline-First AIED: An Architectural Blueprint for On-Device LLM Integration in Low-Resource Educational Contexts.
.- Towards Elastic Offline-First Applications for AIED Unplugged.
.- When Features Misrepresent Underrepresented Learners: Auditing Algorithmic Bias with Differentially Expressive
Features.
.- Design Tensions for Generative AI in Education for Early to Mid-Adolescent Youth: An Exploration of Autonomy, Critical
Reflection, and Psychological Safety.
.- AI That Helps—or Widens Gaps? Equity Impacts of a Leaching-by-Tearning Tutor in K–12 Mathematics.
.- Kwame 2.0: Human-in-the-Loop Generative AI Teaching Assistant for Large Scale Online Coding Education in Africa.
.- CLUE-AI: A Collaborative Game-Based Learning Approach to Promote Critical Literacy for Uncovering Errors in AI.
.- Fairness Depends on Assessment: Learning by Teaching with Large Language Models.
.- Sociodemographic Biases in Educational Counselling by Large Language Models.