Analytics for Tracking Student Engagement
- Submitting institution
-
The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1654339
- Type
- D - Journal article
- DOI
-
10.5334/jime.590
- Title of journal
- JIME- Journal of Interactive Media in Education/EADTU-19 Special Collection
- Article number
- 22
- First page
- -
- Volume
- 2020
- Issue
- 1
- ISSN
- 1365-893X
- Open access status
- Compliant
- Month of publication
- December
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- 23 - Education
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The authors were invited by the JIME journal’s editor to develop an earlier conference paper into this article. Two innovative methodological features singled it out for this invitation: retrospective use of learning analytics to reveal engagement with a particular learning resource by a subset of students; use of a statistical test to show the subset was representative of the cohort. Hence successful assessment performance by members of the subset is reliably attributed to engagement with the resource. The paper thus demonstrates a new, but generalisable, usage of learning analytics to connect particular elements in online courses to beneficial learning outcomes.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -