The areas of learning analytics (LA) and educational data mining (EDM) explore the use of data to increase insight about learning environments and improve the overall quality of experience for students. The focus of both disciplines covers a wide spectrum related to instructional design, tutoring, student engagement, student success, emotional well-being, and so on. This chapter focuses on the potential of combining the knowledge from these disciplines with the existing body of research about the provision of feedback to students. Feedback has been identified as one of the factors that can provide substantial improvement in a learning scenario. Although there is a solid body of work characterizing feedback, the combination with the ubiquitous presence of data about learners offers fertile ground to explore new data-driven student support actions.
|Title of host publication||Handbook of Learning Analytics|
|Editors||Charles Lang, George Siemens, Alyssa Wise, Dragan Gasevic|
|Place of Publication||New York NY USA|
|Publisher||Society for Learning Analytics Research|
|Number of pages||12|
|Publication status||Published - 2017|