AI in the Classroom - An Update
Aktueller Überblick zum Einsatz von KI in Schulen: rechtliche Entwicklungen, technische und pädagogische Herausforderungen sowie Schritte zur effektiven Implementierung und Entlastung.
ラーニングアナリティクスがなぜ注目されているか - チャプター③
ラーニングアナリティクスの重要性と注目度の高まりについて、教育・学習データの活用における最新の研究動向と課題を探求する。
教育データで教え方や学び方を変える - ラーニングアナリティクスの導入と活用
Discover how learning analytics and educational data are transforming teaching and learning methods, from digital textbooks to lecture videos, with practical examples from K-12 and university settings.
教育・学習データの利活用における国内外の研究動向と課題 - チャプター④ 教育・学習の支援の例
教育・学習データの活用事例を通じて、最新の教育支援技術と研究動向について深く理解する機会を提供。データ駆動型の教育実践における具体的な応用例を探求。
Learning Behavior and Interactive Pattern Analysis - Coding Scheme, Tools and Applications
Discover how learning analytics and big data can enhance education through interactive pattern analysis, coding schemes, and practical applications in this insightful keynote presentation from Taiwan Tech.
Applying Learning Analytics on Predicting Student's Academic Performance
Discover how learning analytics and educational big data can predict student academic performance through expert insights from Prof. Yang's keynote presentation at Kyoto University's symposium.
Turing Lecture - Is Education AI-Ready?
Exploring AI's role in education post-COVID, discussing current applications, future potential, and recommendations for an AI-ready education system to enable all learners to achieve their full potential.
AI Tools for Instructional Design - Incorporating AI into the ADDIE Model
Explore AI tools for each phase of the ADDIE model in instructional design. Learn to incorporate cutting-edge technology, streamline processes, and enhance efficiency in creating educational content.
eラーニング提供企業からみた教育ビッグデータとラーニングアナリティクス - 2018年3月22日
Discover eラーニング企業の視点からラーニングアナリティクスと教育ビッグデータの活用事例を学び、教育・学習支援の新たな可能性を探る実践的な知見を得る。
LMS Independent Learning Analytics Platform - Research Case Study 2018
Discover how learning analytics platforms can operate independently across different LMS systems to enhance educational support through big data analysis and cloud infrastructure.
機械学習による学習者の生理情報と精神状態の関係性の形式化 - 2018
機械学習を活用した学習者の生理情報と精神状態の関係性について探求し、教育ビッグデータを用いた学習支援の可能性を解明する研究事例を紹介。
ラーニングアナリティクスとサイバーフィジカル社会における教育支援 - 2018年3月
Discover how learning analytics and educational big data can enhance teaching and learning support in cyber-physical society through research cases and practical applications.
Supporting Evidence-based Teaching-Learning Practices with Technology - Learning Analytics Symposium 2019
Discover how learning analytics and technology can support evidence-based teaching practices through research cases presented at Kyoto University's 2019 international symposium on educational innovation.
Data Informed Instruction for New Hampshire Summer Learning - Session 4
Explore data-driven instruction strategies, Khanmigo integration, and administrator tools to enhance student learning and teacher effectiveness in New Hampshire schools.
AI for Improving Math Scores with Khanmigo - Khan Academy
Discover how Khanmigo, an AI-powered assistant, enhances classroom learning and boosts math performance through personalized tutoring and innovative teaching support.
AI-Driven Assessments for Continuous Learning
Discover how AI-driven assessments revolutionize learning through personalized paths, real-time adaptation, and gamification techniques for enhanced educational outcomes and continuous improvement.
AI-assisted Event-driven System for Collaborative Programming Learning Analytics
Discover an AI-powered system for analyzing collaborative programming activities, featuring event-driven visualization tools to enhance learning assessment and group dynamics.
Why Spending Smarter Beats Bigger Budgets in Education
Discover how strategic resource allocation and adaptive learning technologies can revolutionize global education outcomes, challenging the notion that increased spending alone leads to better results.
Quantitative Approach for Measuring Student Engagement in E-learning Platforms
Discover a data-driven approach to measuring student engagement in e-learning platforms, exploring behavioral patterns, trajectory analysis, and intervention strategies for K12 math education.