ABSTRACT
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.
TABLE OF CONTENTS
part Section I|20 pages
Introduction
part Section II|124 pages
Analytics
chapter 2|15 pages
What we want versus what we have
chapter 6|18 pages
Predicting student success with self-regulated behaviors
part Section III|118 pages
Adaptive Learning
chapter 14|21 pages
When adaptivity and universal design for learning are not enough
part Section IV|38 pages
Organizational Transformation
part Section V|22 pages
Closing