Overview of content related to 'educational data mining'
This page provides an overview of 2 articles related to 'educational data mining', listing most recently updated content first. Note that filters may be applied to display a sub-set of articles in this category (see FAQs on filtering for usage tips). Select this link to remove all filters.

Educational Data Mining (EDM) describes a research field concerned with the application of data mining to information generated from educational settings (e.g., universities and intelligent tutoring systems). At a high level, the field seeks to develop methods for exploring this data, which often has multiple levels of meaningful hierarchy, in order to discover new insights about how people learn in the context of such settings. A key area of EDM is mining computer logs of student performance. Another key area is mining enrollment data. Key uses of EDM include predicting student performance, and studying learning in order to recommend improvements to current educational practice. EDM can be considered one of the learning sciences, as well as an area of data mining. A related field is learning analytics. (Excerpt from Wikipedia article: Educational Data Mining)
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| Title | Article summary | Date |
|---|---|---|
Editorial Introduction to Issue 71 |
The editor introduces readers to the content of Ariadne Issue 71. |
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The Potential of Learning Analytics and Big Data |
Patricia Charlton, Manolis Mavrikis and Demetra Katsifli discuss how the emerging trend of learning analytics and big data can support and empower learning and teaching. |
July 2013, issue71, feature article |