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This comprehensive volume investigates the untapped potential of machine learning in educational settings. It examines the profound impact machine learning can have on reshaping educational research. Each chapter delves into specific applications and advancements, sheds light on theory-building, and multidisciplinary research, and identifies areas for further development. It encompasses various topics, such as machine-based learning in psychological assessment. It also highlights the power of machine learning in analyzing large-scale international assessment data and utilizing natural language processing for science education. With contributions from leading scholars in the field, this book provides a comprehensive, evidence-based framework for leveraging machine-learning approaches to enhance educational outcomes. The book offers valuable insights and recommendations that could help shape the future of educational sciences.
This edited volume documents attempts to conduct systematic and prodigious research using multilevel analysis in educational settings, and present their findings and identify future research directions. It showcases the versatility of multilevel analysis, and elucidates the unique advantages in examining complex and wide-ranging educational issues. This book brings together leading experts around the world to share their works in the field, highlighting recent advances, creative and unique approaches, and innovative methods using multilevel modeling and theoretical and practical aspects of multilevel analysis in culturally and linguistically-diverse educational contexts.
This comprehensive volume highlights the paradigm shift, creative approaches, and theoretical and practical aspects of rhizomatic learning. The great French theorists Deleuze and Guattari introduced the concept of the rhizome to allow educators to explore the educative process with the rhizomatic lens. The chapters cover digital pedagogies, the conceptual framework of rhizome and nomadic pedagogy in 21st-century education. It creates rhizomatic learning environments and rhizome metaphors to illuminate learning and teacher professional development. It covers an extensive range of issues and challenges related to teaching and learning in the techno centric education systems. It presents an up-to-date and comprehensive analysis of rhizomatic learning approaches in various disciplines. It examines the following key questions: What is the conception of rhizomatic learning and nomadic pedagogy? In which ways can rhizomatic learning transform teaching methods in the digital era? How can educators implement a rhizomatic learning approach in practice? What is the connection between the rhizomatic process and divergent thinking in socially mediated and technology-driven learning environments?Combining theory and practice, this book is essential reading for educational policymakers, teacher educators, university faculty, researchers, instructional designers, learning technologists, teachers, and undergraduate and graduate students worldwide.
Examines the challenges involved in the development of modern curriculum models, teaching strategies, and assessments in science education in order to prepare future students in the 21st century economies. This comprehensive collection of research brings together science educators, researchers and administrators interested in enhancing the teaching and learning of next generation science.
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