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Title: Educational data mining and learning analytics: differences, similarities, and time evolution
Other Titles: Minería de datos educativos y análisis de datos sobre aprendizaje: diferencias, parecidos y evolución en el tiempo
Author: Calvet Liñan, Laura  
Juan Pérez, Ángel Alejandro
Others: Universitat Oberta de Catalunya. Estudis d'Informàtica, Multimèdia i Telecomunicació
Keywords: online learning
educational data mining
learning analytics
big data
Issue Date: Jul-2015
Publisher: RUSC. Universities and Knowledge Society Journal
Citation: Calvet Liñán, L., & Juan Pérez, Á. A. (2015). Educational Data Mining and Learning Analytics: differences, similarities, and time evolution. RUSC. Universities and Knowledge Society Journal, 12(3). 98-112. doi: 10.7238/rusc.v12i3.2515
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Abstract: Technological progress in recent decades has enabled people to learn in different ways. Universities now have more educational models to choose from, i.e., b-learning and e-learning. Despite the increasing opportunities for students and instructors, online learning also brings challenges due to the absence of direct human contact. Online environments allow the generation of large amounts of data related to learning/teaching processes, which offers the possibility of extracting valuable information that may be employed to improve students¿ performance. In this paper, we aim to review the similarities and differences between Educational Data Mining and Learning Analytics, two relatively new and increasingly popular fields of research concerned with the collection, analysis, and interpretation of educational data. Their origins, goals, differences, similarities, time evolution, and challenges are addressed, as are their relationship with Big Data and MOOCs.
Language: English
ISSN: 1698-580XMIAR
Appears in Collections:Articles

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