Provision of data-driven student feedback in LA and EDM

Abelardo Pardo, Oleksandra Poquet, Roberto Martinez-Maldonado, Shane Dawson

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Other


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.
Original languageEnglish
Title of host publicationHandbook of Learning Analytics
EditorsCharles Lang, George Siemens, Alyssa Wise, Dragan Gasevic
Place of PublicationNew York NY USA
PublisherSociety for Learning Analytics Research
Number of pages12
ISBN (Electronic)9780995240803
Publication statusPublished - 2017
Externally publishedYes

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