Big Data and Learning Analytics in Higher Education Current Theory and Practice
Titre:
Big Data and Learning Analytics in Higher Education Current Theory and Practice
ISBN (Numéro international normalisé des livres):
9783319065205
Edition:
1st ed. 2017.
PRODUCTION_INFO:
Cham : Springer International Publishing : Imprint: Springer, 2017.
Description physique:
XX, 272 p. 56 illus., 48 illus. in color. online resource.
Table des matières:
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.
Extrait:
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 .
Auteur ajouté:
Auteur collectif ajouté:
Accès électronique:
Full Text Available From Springer Nature Education 2017 Packages
Langue:
Anglais