Paradigm Shifts in Educational Technology and Administration

Proceedings of the 5th International Conference on Educational Technology and Administration (EduTA2025)
Erscheinungsjahr 2026
ISBN: 978-3-032-29648-1
Verlag: Springer

Buch, Englisch, 486 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Learning and Analytics in Intelligent Systems

Paradigm Shifts in Educational Technology and Administration: Proceedings of the International Conference on Educational Technology and Administration. (EduTA2025) emphasizes the integration of cutting-edge technologies such as Artificial Intelligence, Data Analytics and Immersive Digital Tools to transform Teaching, Learning and Institutional Practices. This volume focuses on creating more personalized, accessible and inclusive education systems that effectively address the needs of diverse learners. Simultaneously, it highlights administrative innovations that promote Data-Driven Decision-Making and efficient academic governance. This scholarly volume contains 39 Research Articles, systematically organized into four major thematic sections offering a comprehensive and structured understanding of the Evolving Educational Landscape:
Artificial Intelligence and Data Analytics in Education
Intelligent Learning Systems and Personalized Education
Smart Educational Platforms, Systems and Administration
Digital Pedagogy, Immersive Learning and Curriculum Innovation

EduTA2025 explores the latest innovations and significant developments in Educational Technology and Administration offering a thorough overview of the current academic and practical landscape. It encompasses key dimensions such as Learning Analytics and Curriculum Design, Online and Distance Learning and Leadership in Modern Education by merging theoretical insights with practical applications, this book empowers educators, researchers, practitioners, policymakers and students to effectively navigate and excel in the rapidly evolving domain of educational technology. With a strong emphasis on responsible technology use EduTA2025 addresses critical challenges such as digital equity, ethical implementation and effective assessment and feedback systems which poises to redefine learning environments and empower future generations.

Zielgruppe

Research

Autoren/Hrsg.

Paas, Fred

Patnaik, Srikanta

Esposito, Anna

Wang, Taosheng

Fachgebiete

• Sozialwissenschaften Pädagogik Berufliche Bildung Wissenschaftliches Arbeiten, Studientechnik
• Sozialwissenschaften Pädagogik Pädagogik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Research on Depression Emotion Recognition in College Students Based on Transformer Algorithm.- Identifying College Students' Psychological States through Image Features Using CNN Algorithm.- University Student Psychological Emotion Monitoring System Design Based on Semantic Analysis.- Incorporating LSTM Networks for Time-series Modeling of Student Mental Health in Big Data Colleges and Universities.- A Study on Dynamic Assessment of College Students' Psychological State Based on Bayesian Networks.- Key Technology Applications of Multimodal Data Analysis in Intelligent Education Tracking Systems.- Deep Learning-Based Analysis of Digital Teaching Behaviors in English Classrooms.- A Study on Predicting Student Career Stress Based on Intelligent Algorithm Models.- Construction of a Personalized Education System Based on CF-LSTM-CNN.- Construction of Knowledge Framework of Teacher PTCCK Based on Deep Learning and Intelligent Teaching Environment Applied Research.- Research on Artificial Intelligence-Driven Personalized Recommendation System for Educational Resources.- Adaptive English Grammar Teaching System Based on Natural Language Processing.- Application of Artificial Intelligence-assisted APP in English Autonomous Learning.- Research on Personalized Learning Path Optimization and Recommendation System of Educational Design Based on Artificial Intelligence.- Design of Adaptive Learning Platform for College English Teaching and Research on Knowledge Tracking Algorithm.- Intelligent Teaching Model for Spoken English Based on IPFD-VC Speech Feature Decoupling.- Application of Multimodal Attention Mechanism in Interdisciplinary Course Recommendation.- etc.

Über Autor(innen)

Prof. (Dr.) Srikanta Patnaik, Chairman and Founder Director of Interscience Institute of Management & Technology, earned his Ph.D. in Computational Intelligence from Jadavpur University in 1999. He has supervised 34 Ph.D. and over 60 M.Tech theses in Machine Intelligence and Soft Computing. With more than 100 research publications, 3 textbooks and more than 100 edited books, he is an academic leader. He serves as Editor-in-Chief of reputed International Journals and Springer Book Series. He has delivered keynote talks in over 20 countries and participated in UNESCO meetings on AI and Human Rights. 
Prof. (Dr.) Fred Paas is professor of Educational Psychology at the Department of Psychology, Education and Child Studies of Erasmus University Rotterdam in the Netherlands. He holds a master's degree (1988) in human movement sciences and a Ph.D. degree (1993) in instructional technology. He is one of the pioneers of cognitive load theory. His research examines the cognitive architecture that underlies learning and instruction, with a focus on self-regulated learning, multimedia learning, embodied cognition, and the effects of physical activity on cognition and learning. He has authored or co-authored nearly 400 scholarly publications. His contributions have been recognized through his election as Fellow of the American Educational Research Association and through consistent top rankings among the most productive and most cited scholars in educational psychology. He currently serves as Visiting Professor at the University of New South Wales and maintains active international collaborations across Europe, Asia, and Australia.
Prof. (Dr.) Anna Esposito received her “Laurea Degree” summa cum laude in Information Technology and Computer Science from University of Salerno in 1989 with a thesis on: The Behavior and Learning of a Deterministic Neural Net. She received her Ph.D. Degree in Applied Mathematics and Computer Science from University of Napoli “Federico II” in 1995. Her Ph.D. thesis on:  Vowel Height and Consonantal Voicing Effects: Data from Italian (published on Phonetica, vol 59(4),197-231, 2002) was developed at Massachusetts Institute of Technology (MIT), Research Laboratory of Electronics (RLE), under the supervision of Professor Kenneth N Stevens. She has been the post-doc at the International Institute for Advanced Scientific Studies (IIASS), an assistant professor at the Department of Physics at the University of Salerno (Italy), and a research professor (2000–2002) at the Department of Computer Science and Engineering at Wright State University (WSU), Dayton, OH, USA. 
Prof. (Dr.) Taosheng Wang is a doctor, professor of Applied Economics (International Trade Direction), specialist of General Office of the State Council, director of Chinese Society of World Economy, vice chairman of the Expert Committee of China Association of Trade in Service, master tutor. He is the dean of School of Business of Hunan International Economics University, chief expert of the provincial-level social science key research base. He is also foregoer of provincial-level key construction course “International Trade,” provincial-level teaching team “International Trade,” provincial-level characteristic specialty “International Economics and Trade.” His main research areas are international economic and trade theory and policy; institutional innovation and international trade; international competitive advantage and competitive strategy.