Buch, Englisch, Format (B × H): 155 mm x 235 mm
Selected Contributions to CSTE 2026 - The 8th International Conference on Computer Science and Technologies in Education
Buch, Englisch, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Educational Technology
ISBN: 978-981-9257-32-4
Verlag: Springer Singapore
This book explores the dynamic intersection between educational and information technology. It covers a wide range of topics, including Artificial Intelligence (AI)-enhanced pedagogy tailored for diverse learners and learning analytics-driven differentiation, accessible immersive learning pedagogies, culturally responsive ed-tech solutions, equity-focused digital assessments, micro-credentialing for varied learners, smart pedagogy training for educators, multilingual learning support, and inclusive gamification frameworks. Through a combination of empirical studies, theoretical insights, and real-world examples, this book demonstrates technology’s potential to transform education. It serves as a valuable resource for educators looking to integrate innovative strategies, researchers exploring educational technology in depth, and practitioners seeking to develop more effective solutions.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
A Study on the Impact of Human Machine Collaboration on College Students' Critical Thinking A Case Study of Students in a Course at a Normal University in G Province.- Enhancing Conceptual Understanding of Human Body Systems Through AI-Powered Interactive Diagrams in Science Learning among Grade 11 Students.- Generative AI Empowering College Curriculum Teaching A Case Study of "Family and Community Education" Course.- Integrating PhET Interactive Simulations as Supplementary Virtual Learning Tool to Enhance Engagement and Learning Outcomes in Projectile Motion for Grade 10 Students.- Breaking the "Abstraction Barrier" in Materials Science Education "Three Integrations Multi Task Drive" for Enhancing Student Engagement and Competence.- TUTOR LA Technology Driven Understanding and Retention in Linear Algebra.- Predicting Mathematics Achievement from Technology Enhanced Instruction, Cognitive Engagement, and Affective Attitudes Using IRT.




