Data Analytics and Adaptive Learning offers new insights into the use of emerging data analysis and adaptive techniques in multiple learning settings. In recent years, both analytics and adaptive learning have helped educators become more responsive to learners in virtual, blended, and personalized environments. This set of rich, illuminating, international studies spans quantitative, qualitative, and mixed-methods research in higher education, K–12, and adult/continuing education contexts. By exploring the issues of definition and pedagogical practice that permeate teaching and learning and concluding with recommendations for the future research and practice necessary to support educators at all levels, this book will prepare researchers, developers, and graduate students of instructional technology to produce evidence for the benefits and challenges of data-driven learning.

About the Author

Patsy D. Moskal is Director of the Digital Learning Impact Evaluation in the Research Initiative for Teaching Effectiveness at the University of Central Florida, USA.

Charles D. Dziuban is Director of the Research Initiative for Teaching Effectiveness at the University of Central Florida, USA.

Anthony G. Picciano is Professor of Education Leadership at Hunter College and Professor in the PhD program in Urban Education at the City University of New York Graduate Center, USA.

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