Abstract
| Original language | English |
|---|---|
| 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 |
| Edition | 1st |
| ISBN (Electronic) | 9783030251123 |
| ISBN (Print) | 9783030251116 |
| DOIs | |
| Publication status | Published - 2019 |
Keywords
- assessment feedback
- learning analytics
- massification
- modularisation
Cite this
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Identifying the impact of feedback over time and at scale : opportunities for learning analytics. / Ryan, Tracii; Gašević, Dragan; Henderson, Michael.
The Impact of Feedback in Higher Education: Improving Assessment Outcomes for Learners. ed. / Michael Henderson; Rola Ajjawi; David Boud; Elizabeth Molloy. 1st. ed. Cham Switzerland : Palgrave Macmillan, 2019. p. 207-223.Research output: Chapter in Book/Report/Conference proceeding › Chapter (Book) › Research › peer-review
TY - CHAP
T1 - Identifying the impact of feedback over time and at scale
T2 - opportunities for learning analytics
AU - Ryan, Tracii
AU - Gašević, Dragan
AU - Henderson, Michael
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - assessment feedback
KW - learning analytics
KW - massification
KW - modularisation
U2 - 10.1007/978-3-030-25112-3_12
DO - 10.1007/978-3-030-25112-3_12
M3 - Chapter (Book)
SN - 9783030251116
SP - 207
EP - 223
BT - The Impact of Feedback in Higher Education
A2 - Henderson, Michael
A2 - Ajjawi, Rola
A2 - Boud, David
A2 - Molloy, Elizabeth
PB - Palgrave Macmillan
CY - Cham Switzerland
ER -