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Learning Analytics in Higher Education
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Author(s): Rushil Raghavjee (University of KwaZulu-Natal, South Africa), Prabhakar Rontala Subramaniam (University of KwaZulu-Natal, South Africa)and Irene Govender (University of KwaZulu-Natal, South Africa)
Copyright: 2021
Pages: 34
Source title:
Perspectives on ICT4D and Socio-Economic Growth Opportunities in Developing Countries
Source Author(s)/Editor(s): Patrick Ndayizigamiye (University of Johannesburg, South Africa), Glenda Barlow-Jones (University of Johannesburg, South Africa), Roelien Brink (University of Johannesburg, South Africa), Stella Bvuma (University of Johannesburg, South Africa), Rehana Minty (University of Johannesburg, South Africa)and Siyabonga Mhlongo (University of Johannesburg, South Africa)
DOI: 10.4018/978-1-7998-2983-6.ch015
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Abstract
It is known that big data has penetrated several if not all spheres of life. In higher education, the ability to take these large amounts of data and process it into something meaningful for academic decision making is commonly referred to as learning analytics. This chapter provides an overview of learning analytics and its importance, as well as identifying academic data sources, techniques used for learning analytics and prediction, and data visualisation techniques used to present analysis for better understanding and eventual decision making. It also includes a discussion of learning analytics frameworks for research and some identified research challenges.
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