Adoption of Data Analytics in Higher Education Learning and Teaching



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Éditeur :

Springer


Paru le : 2020-08-10



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Description


The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.


Pages
434 pages
Collection
n.c
Parution
2020-08-10
Marque
Springer
EAN papier
9783030473914
EAN PDF
9783030473921

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
14592 Ko
Prix
137,14 €
EAN EPUB
9783030473921

Informations sur l'ebook
Nombre pages copiables
4
Nombre pages imprimables
43
Taille du fichier
22487 Ko
Prix
137,14 €

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