Buch, Englisch, 489 Seiten, Format (B × H): 155 mm x 235 mm
Third International Conference, ITEA 2026, Hong Kong, China, May 15–17, 2026, Proceedings, Part I
Buch, Englisch, 489 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Communications in Computer and Information Science
ISBN: 978-981-9264-33-9
Verlag: Springer
This book constitutes the refereed proceedings of the Third International Conference on Intelligent Technology for Educational Applications, ITEA 2026, held in Hong Kong, China,during May15–17, 2026.
The 82 full papers included in this book were carefully reviewed and selected from 196 submissions. The papers were organized in topical sections as follows:
Part I- Section 1: AI-Enhanced Curriculum Design and Pedagogical Innovation; Section 2: Personalized Learning, Adaptive Systems and Learning Analytics; Section 3: Educational Data Mining, Evaluation and Decision-Support Systems.
Part II- Section 1: AI in Language Education and Cross-Cultural Learning; Section 5: Learning Experience, Educational Psychology and Human-AI Interaction; Section 6: Emerging AI Technologies, Platforms and Intelligent Systems in Education.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
.- Section 1: AI-Enhanced Curriculum Design and Pedagogical Innovation.
.- Innovative practice of ideological and political education based on intelligent technology: a case study of Shaanxi University of Chinese Medicine.
.- AI Empowerment for Traditional Engineering Drawing: A Study on Curriculum Transformation and Intelligent Teaching.
.- AI-driven Engineering Drawing Course: Three-Stage and Five-Dimension Teaching Innovation Path.
.- Architecture and Implementation Approaches of Intelligent Educational Technology for Machining Processes.
.- Artificial intelligence empowered of materials mechanics courses: an integration framework and new teaching paradigm.
.- Digital Twin–Driven Design Education: Real-Time Interaction Modeling and Intelligent Interventions.
.- Reconstructing Collaborative Teaching and Research in New Engineering: A Virtual Teaching and Research Section for "Mechanical Design".
.- Research on the Construction and Application of Virtual Reality-Based Practical Teaching Environment for Mechanical Manufacturing.
.- Teaching Research on Machine Learning-Based Subjective Evaluation Model for Educational Spaces — Application of Educational Space Design Model Integrated with Architectural Technology Courses.
.- Research on Engineering Thinking and Ethics Cultivation Model for Vehicle Engineering Major Based on Scenario-based Teaching.
.- Innovative teaching of linguistics theory courses in universities based on virtual simulation experiment technology, speech Large Model Practical Training Technology and smart teaching platform.
.- An AI-Assisted Analytics Platform for Engineering Education.
.- Designing an Immersive VR Garden for Educational Use: Development and Application.
.- Research on the Intelligent Reform of MTI Sci-Tech Translation Course Based on "Déjà Vu +AI Technology".
.- Digital Platforms and Internalization in Higher Education: Discursive Construction and Students Interpretation.
.- Section 2: Personalized Learning, Adaptive Systems and Learning Analytics.
.- An Adaptive Generation Algorithm for Personalized Learning Paths Based on Attention Mechanism and Educational Psychology.
.- Reinforcement Learning Agent in Student Learning Path Decision-Making in Sub-Optimal Goals.
.- AI-Based Optimization of Personalized Online Learning Paths for English Learning.
.- A Deep Learning Based Personalized Course Recommendation System for Vocational Education.
.- Learning Outcome Analysis and Prediction for University Accounting Courses Using Data Mining.
.- A Study on Student Performance Prediction and RealTime Improvement Model Based on Fuzzy Comprehensive Evaluation and Neural Networks——A Case Study of Practical Courses in Vehicle Engineering.
.- Adaptive Prompting: Using Large Language Models to Generate Real-Time, Personalized Scaffolding for STEM Students.
.- A Data-Driven Framework for Predicting Student Learning Potential in Technology-enhanced K–12 Mathematics Classrooms.
.- A Human-in-the-Loop AI Framework for Structured Parent-Guided Speech Stimulation.
.- An AI-Teacher Collaborative Early Warning and Intervention System for Cross-Border E-Commerce Courses.
.- A Machine Learning Based Collaborative Evaluation Model for Labor Education and Student Management.
.- AI-Based Optimization and Management of Educational Resource Allocation.
.- Design and Algorithmic Optimization of a Practice-Oriented Education Evaluation Framework under Industry-Education Integration.
.- Research on Algorithm Optimization and Teaching Intervention Strategy of Intelligent Teaching Evaluation System.
.- The Impact of AI-Assisted Feedback on Anxiety of College Students: The Mediating Role of Academic Self-Efficacy.
.- Section 3: Educational Data Mining, Evaluation and Decision-Support Systems.
.- Research on Comprehensive Student Ability Evaluation Based on AHP-TOPSIS Combined Method.
.- Adaptive Clustering of Multi-Source Learning Logs: High-Dimensional Modeling and Drift Handling.
.- Data Mining Based Analysis of Factors Influencing Teachers’ Digital Literacy.
.- From AIED to OR-EDU: A shift from Predictive Learning Analytics to OR-Driven Decision-Support System.
.- The STEM Readiness Index: A Systems Modelling Framework for Educational Policy and Institutional Planning.
.- A Hybrid Statistical–Machine Learning Survey-Weighted Pipeline for Examining the Test-Language-at-Home Paradox in PISA 2022 Mathematics Achievement.
.- Artificial Intelligence-Driven Gender Parity and Equity Analysis Framework Applied in Philippine Basic Education (2016-2020).
.- Policy and Survey Based AI General Course Analysis for Overseas Chinese Students.
.- Big Data Mining and Employment Trend Prediction in University Students' Employment Market Analysis.
.- Data-Driven Mathematical Fairness: An Intelligent Educational Framework Using the 2026 FIFA World Cup to Teach Applied Mathematics.
.- A Student's Approach to Learning Engineering: The Competitive Dynamics of The Learning Process and Cognitive Absorption in Accounting Education.
