Learning Analytics in Higher Education
Current Innovations, Future Potential, and Practical Applications
1st Edition
Published on 6. August 2018
216 pages
978-1-351-40053-4 (ISBN)
Description
Learning Analytics in Higher Education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical, theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and consent. Designed to give readers a practical and theoretical foundation in learning analytics and how data can support student success in higher education, this book is a valuable resource for scholars and administrators.
More details
Edition
1. Auflage
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Illustrations
9 Tables, black and white; 16 Illustrations, black and white
File size
3,73 MB
ISBN-13
978-1-351-40053-4 (9781351400534)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Jaime Lester | Carrie Klein | Aditya Johri
Learning Analytics in Higher Education
Current Innovations, Future Potential, and Practical Applications
Book
08/2018
1st Edition
Routledge
€69.20
Shipment within 10-20 days
Jaime Lester | Carrie Klein | Aditya Johri
Learning Analytics in Higher Education
Current Innovations, Future Potential, and Practical Applications
Book
07/2018
1st Edition
Routledge
€231.50
Shipment within 10-20 days
Persons
Jaime Lester is Associate Professor of Higher Education at George Mason University, USA.
Carrie Klein is a PhD Candidate and Research and Teaching Assistant in the Higher Education Program at George Mason University, USA.
Aditya Johri is Associate Professor of Information Sciences and Technology at George Mason University, USA.
Huzefa Rangwala is Associate Professor of Computer Science at George Mason. University, USA.
Carrie Klein is a PhD Candidate and Research and Teaching Assistant in the Higher Education Program at George Mason University, USA.
Aditya Johri is Associate Professor of Information Sciences and Technology at George Mason University, USA.
Huzefa Rangwala is Associate Professor of Computer Science at George Mason. University, USA.
Content
Contents
List of Tables
List of Figures
Preface
Acknowledgments
Chapter 1: Absorptive capacity and routines: Understanding barriers to learning analytics adoption in higher education
Aditya Johri
Chapter 2. Analytics in the field: Why locally grown continuous improvement systems are essential for effective data driven decision-making
Matthew T. Hora
Chapter 3: Big data, small data, and data shepherds
Jennifer DeBoer and Lori Breslow
Chapter 4: Evaluating scholarly teaching: A model and call for an evidence-based approach
Daniel L. Reinholz, Joel C. Corbo, Daniel J. Bernstein, and Noah D. Finkelstein
Chapter 5: Discipline-focused learning analytics approaches with users instead of for usersDavid B. Knight, Cory Brozina, Timothy J. Kinoshita, Brian J. Novoselich, Glenda D. Young, and Jacob R. Grohs
Chapter 6: Student consent in learning analytics: The devil in the details?Paul Prinsloo and Sharon Slade
Chapter 7: Using learning analytics to improve student learning outcomes assessment in higher education: Potential, constraint, & possibility
Carrie Klein, and Richard M. Hess
Chapter 8: Data, data everywhere: Implications and considerations
Matthew D. Pistilli
Contributor Bios
List of Tables
List of Figures
Preface
Acknowledgments
Chapter 1: Absorptive capacity and routines: Understanding barriers to learning analytics adoption in higher education
Aditya Johri
Chapter 2. Analytics in the field: Why locally grown continuous improvement systems are essential for effective data driven decision-making
Matthew T. Hora
Chapter 3: Big data, small data, and data shepherds
Jennifer DeBoer and Lori Breslow
Chapter 4: Evaluating scholarly teaching: A model and call for an evidence-based approach
Daniel L. Reinholz, Joel C. Corbo, Daniel J. Bernstein, and Noah D. Finkelstein
Chapter 5: Discipline-focused learning analytics approaches with users instead of for usersDavid B. Knight, Cory Brozina, Timothy J. Kinoshita, Brian J. Novoselich, Glenda D. Young, and Jacob R. Grohs
Chapter 6: Student consent in learning analytics: The devil in the details?Paul Prinsloo and Sharon Slade
Chapter 7: Using learning analytics to improve student learning outcomes assessment in higher education: Potential, constraint, & possibility
Carrie Klein, and Richard M. Hess
Chapter 8: Data, data everywhere: Implications and considerations
Matthew D. Pistilli
Contributor Bios
