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.

part Section I|20 pages

Introduction

chapter 1|18 pages

Data analytics and adaptive learning

Increasing the odds
ByPhilip Ice, Charles Dziuban

part Section II|124 pages

Analytics

chapter 2|15 pages

What we want versus what we have

Transforming teacher performance analytics to personalize professional development
ByRhonda Bondie, Chris Dede

chapter 3|22 pages

System-wide momentum

ByTristan Denley

chapter 4|18 pages

A precise and consistent early warning system for identifying at-risk students

ByJianbin Zhu, Morgan C. Wang, Patsy Moskal

chapter 6|18 pages

Predicting student success with self-regulated behaviors

A seven-year data analytics study on a Hong Kong University English Course
ByDennis Foung, Lucas Kohnke, Julia Chen

chapter 7|18 pages

Back to bloom

Why theory matters in closing the achievement gap
ByAlfred Essa

chapter 8|17 pages

The metaphors we learn by

Toward a philosophy of learning analytics
ByW. Gardner Campbell

part Section III|118 pages

Adaptive Learning

chapter 9|23 pages

A cross-institutional survey of the instructor use of data analytics in adaptive courses

ByJames R. Paradiso, Kari Goin Kono, Jeremy Anderson, Maura Devlin, Baiyun Chen, James Bennett

chapter 10|19 pages

Data analytics in adaptive learning for equitable outcomes

ByJeremy Anderson, Maura Devlin

chapter 11|22 pages

Banking on adaptive questions to nudge student responsibility for learning in general chemistry

ByTara Carpenter, John Fritz, Thomas Penniston

chapter 12|19 pages

Three-year experience with adaptive learning

Faculty and student perspectives
ByYanzhu Wu, Andrea Leonard

chapter 13|12 pages

Analyzing question items with limited data

ByJames Bennett, Kitty Kautzer, Leila Casteel

chapter 14|21 pages

When adaptivity and universal design for learning are not enough

Bayesian network recommendations for tutoring
ByCatherine A. Manly

part Section IV|38 pages

Organizational Transformation

chapter 15|15 pages

Sprint to 2027

Corporate analytics in the digital age
ByMark Jack Smith, Charles Dziuban

chapter 16|21 pages

Academic digital transformation

Focused on data, equity, and learning science
ByKaren Vignare, Megan Tesene, Kristen Fox

part Section V|22 pages

Closing

chapter 17|20 pages

Future technological trends and research

ByAnthony G. Picciano