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Big data and learning analytics in h...

Kei Daniel, Ben.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Big data and learning analytics in higher education/ edited by Ben Kei Daniel.
Reminder of title:	current theory and practice /
other author:	Kei Daniel, Ben.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xx, 272 p. :ill., digital ;24 cm.
[NT 15003449]:	Theory and Practice -- Global challenges in higher education -- Technological trends in higher education -- Data Science -- Big data in higher education -- Learning analytics -- Big Data Platforms and Systems -- Analytical platforms -- Systems -- Databases -- Tools -- Visualization -- Dashboards -- Measurement and Methodologies -- Measures, indicators, metrics -- Data mining techniques -- Data capture -- Data tracking -- Metadata -- Methodologies -- Institutional Best Practices -- Case studies/best practices -- Polyicy implication on learning, teaching, and research -- Challenges and opportunities -- Future Trends -- Lessons learned -- Future perspectives in big data -- Conclusions.
Contained By:	Springer eBooks
Subject:	Big data. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-06520-5
ISBN:	9783319065205

Big data and learning analytics in higher education = current theory and practice /
Big data and learning analytics in higher educationcurrent theory and practice /[electronic resource] :edited by Ben Kei Daniel. - Cham :Springer International Publishing :2017. - xx, 272 p. :ill., digital ;24 cm.

Theory and Practice -- Global challenges in higher education -- Technological trends in higher education -- Data Science -- Big data in higher education -- Learning analytics -- Big Data Platforms and Systems -- Analytical platforms -- Systems -- Databases -- Tools -- Visualization -- Dashboards -- Measurement and Methodologies -- Measures, indicators, metrics -- Data mining techniques -- Data capture -- Data tracking -- Metadata -- Methodologies -- Institutional Best Practices -- Case studies/best practices -- Polyicy implication on learning, teaching, and research -- Challenges and opportunities -- Future Trends -- Lessons learned -- Future perspectives in big data -- Conclusions.

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.

ISBN: 9783319065205

Standard No.: 10.1007/978-3-319-06520-5doiSubjects--Topical Terms:

2045508
Big data.

LC Class. No.: LB2326.3

Dewey Class. No.: 378.0072

Big data and learning analytics in higher education = current theory and practice /
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505 0 $a Theory and Practice -- Global challenges in higher education -- Technological trends in higher education -- Data Science -- Big data in higher education -- Learning analytics -- Big Data Platforms and Systems -- Analytical platforms -- Systems -- Databases -- Tools -- Visualization -- Dashboards -- Measurement and Methodologies -- Measures, indicators, metrics -- Data mining techniques -- Data capture -- Data tracking -- Metadata -- Methodologies -- Institutional Best Practices -- Case studies/best practices -- Polyicy implication on learning, teaching, and research -- Challenges and opportunities -- Future Trends -- Lessons learned -- Future perspectives in big data -- Conclusions.
520 $a 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.
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