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Learning analytics in higher education : current innovations, future potential, and practical applications / by Jaime Lester, Carrie Klein, Aditya Johri and Huzefa Rangwala.

Contributor(s):

Material type: Text

978-1-138-30217-4 (Paperback)

Subject(s):

DDC classification:

DC 378 2019 L479

LOC classification:

LB2331.72 .L42 2018

Contents:

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 users / David 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.

Summary: 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

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Circulation	UM Digos College - LIC	Circulation	DC 378 L479 2019 (Browse shelf(Opens below))	1	Available		25472

Includes bibliographical references.

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

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