Learning Analytics in Higher Education: Current Innovations, Future Potential, and Practical Applications...

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Jaime Lester Carrie Klein

Learning Analytics in Higher Education

Current Innovations, Future Potential, and Practical Applications

Jaime Lester, Carrie Klein, Aditya Johri , Huzefa Rangwala

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English

Routledge
15 August 2018

Higher & further education, tertiary education; Open learning, home learning, distance education; Computing: general; Computer science

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.

Edited by: Jaime Lester, Carrie Klein, Aditya Johri, Huzefa Rangwala
Imprint: Routledge
Country of Publication: United Kingdom
Dimensions: Height: 229mm, Width: 152mm,
Weight: 235g
ISBN: 9781138302174
ISBN 10: 1138302171
Pages: 200
Publication Date: 15 August 2018
Audience: College/higher education , General/trade , Primary , ELT Advanced
Format: Paperback
Publisher's Status: Active

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

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.