Adoption Of Data Analytics In Higher Education Learning And Teaching
Download Adoption Of Data Analytics In Higher Education Learning And Teaching PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Adoption Of Data Analytics In Higher Education Learning And Teaching book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Adoption of Data Analytics in Higher Education Learning and Teaching
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.
Adoption of Data Analytics in Higher Education Learning and Teching
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.
A Research Agenda for Global Higher Education
Author: Huisman, Jeroen
language: en
Publisher: Edward Elgar Publishing
Release Date: 2022-02-11
This innovative Research Agenda critically reflects on the state of the art and offers inspiration for future higher education research across a variety of geographical, disciplinary and theoretical perspectives. It explores the impact of Covid-19, and the need to re-engage with the Global South and reconsider conventional paradigms and assumptions. Leading international contributors address a set of salient issues, ranging from research on macro-level themes to meso and micro-level phenomena.