Educational data mining and learning analytics

• Main Authors: Baker, Ryan Shaun, Inventado, Paul Salvador B.
• Format: text
• Published: Animo Repository 2014
• Subjects: Data mining; Education—Research; Education—Data processing; Data Science
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/3837; https://animorepository.dlsu.edu.ph/context/faculty_research/article/4839/type/native/viewcontent/978_1_4614_3305_7_4.html
• Institution: De La Salle University

In recent years, two communities have grown around a joint interest on how big data can be exploited to benefit education and the science of learning: Educational Data Mining and Learning Analytics. This article discusses the relationship between these two communities, and the key methods and approaches of educational data mining. The article discusses how these methods emerged in the early days of research in this area, which methods have seen particular interest in the EDM and learning analytics communities, and how this has changed as the field matures and has moved to making significant contributions to both educational research and practice. © Springer Science+Business Media New York 2014.