Abstract
In contemporary higher education, learner behaviour is increasingly traced by digital systems. As such, there is a strong potential for data mining over time to track and represent learner actions in the context of their assessment performance. This chapter explores how learning analytics can assist educators to design impactful feedback processes and help learners identify the impact of feedback information, both across time and at scale. In doing so, it offers current examples of how learning analytics could guide educational designs and be employed to support learners to direct their own learning and study habits. This chapter also highlights how learning analytics can help understand and optimise learning, and the environments in which the learning occurs.
Original language | English |
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Title of host publication | The Impact of Feedback in Higher Education |
Subtitle of host publication | Improving Assessment Outcomes for Learners |
Editors | Michael Henderson, Rola Ajjawi, David Boud, Elizabeth Molloy |
Place of Publication | Cham Switzerland |
Publisher | Palgrave Macmillan |
Chapter | 12 |
Pages | 207-223 |
Number of pages | 17 |
Edition | 1st |
ISBN (Electronic) | 9783030251123 |
ISBN (Print) | 9783030251116 |
DOIs | |
Publication status | Published - 2019 |
Keywords
- assessment feedback
- learning analytics
- massification
- modularisation