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A Systematic Mapping on the Learning Analytics Field and Its Analysis in the Massive Open Online Courses Context
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Author(s): Barbara Moissa (Santa Catarina State University (UDESC), Joinville, Brazil), Isabela Gasparini (Department of Computer Science, Santa Catarina State University (UDESC), Joinville, Brazil)and Avanilde Kemczinski (Department of Computer Science, Santa Catarina State University (UDESC), Joinville, Brazil)
Copyright: 2015
Volume: 13
Issue: 3
Pages: 24
Source title:
International Journal of Distance Education Technologies (IJDET)
Editor(s)-in-Chief: Maiga Chang (Athabasca University, Canada)
DOI: 10.4018/IJDET.2015070101
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Abstract
Learning Analytics (LA) is a field that aims to optimize learning through the study of dynamical processes occurring in the students' context. It covers the measurement, collection, analysis and reporting of data about students and their contexts. This study aims at surveying existing research on LA to identify approaches, topics, and needs for future research. A systematic mapping study is launched to find as much literature as possible. The 127 papers found (resulting in 116 works) are classified with respect to goals, data types, techniques, stakeholders and interventions. Despite the increasing interest in field, there are no studies relating it to the Massive Open Online Courses (MOOCs) context. The goal of this paper is twofold, first we present the systematic mapping on LA and after we analyze its findings in the MOOCs context. As results we provide an overview of LA and identify perspectives and challenges in the MOOCs context.
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