Big data and learning analytics in higher education : current theory and practice /

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Bibliographic Details
Imprint:Switzerland : Springer, [2017]
©2017
Description:1 online resource
Language:English
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11265713
Hidden Bibliographic Details
Other authors / contributors:Daniel, Ben Kei, 1971- editor.
ISBN:9783319065205
3319065203
9783319065199
331906519X
Notes:Includes bibliographical references index.
Online resource, title from PDF title page (Ebsco, viewed on September 7, 2016).
Summary:This book focuses on the uses of big data in the context of higher education. The book describes a wide range of administrative and operational data gathering processes aimed at assessing institutional performance and progress in order to predict future performance, and identifies potential issues related to academic programming, research, teaching and learning. Big data refers to data which is fundamentally too big and complex and moves too fast for the processing capacity of conventional database systems. The value of big data is the ability to identify useful data and turn it into useable information by identifying patterns and deviations from patterns.
Other form:Print version: Big data and learning analytics in higher education. Switzerland : Springer, [2017] 331906519X
Standard no.:99971908626