A Systematic Mapping on the Learning Analytics Field and Its Analysis in the Massive Open Online Courses Context

A Systematic Mapping on the Learning Analytics Field and Its Analysis in the Massive Open Online Courses Context

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 |Pages: 24
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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2. Learning Analytics

Learning Analytics is “the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs” (“1st International Conference on Learning Analytics and Knowledge 2011”, 2014). LA is applied at the discipline, course and department levels providing valuable information about what is happening and suggesting ways in which educators can improve the learning process (Siemens & Long, 2011). LA can also tell which students may quit the course or those who need special attention to improve their performance.

A reference model for LA was proposed by Chatti et al. (2012) and has the same dimensions adopted by Atif, Richards, Bilgin and Marrone (2013). We deeper describe these dimensions based on Atif et al. (2013) and Chatti et al. (2012) providing some examples for better understanding:

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