A large-scale implementation of Predictive Learning Analytics in Higher Education: the teachers' role and perspective
- Submitting institution
-
The Open University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1689382
- Type
- D - Journal article
- DOI
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10.1007/s11423-019-09685-0
- Title of journal
- Educational Technology Research and Development
- Article number
- -
- First page
- 1273
- Volume
- 67
- Issue
- 5
- ISSN
- 1556-6501
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2019
- 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
-
4
- Research group(s)
-
-
- Citation count
- 15
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper demonstrates the impact of our Predictive Learning Analytics methods deployed to teachers. Greater usage was found to predict better completion and pass rates. The paper was used as a core evidence to the OU policy to recommend using Predictive Learning Analytics in all undergraduate with >150,000 students. The results also led to winning DataIQ award for Best use of data by a non-profit organisation and two OU awards recognising teaching excellence. Other researchers usually cite this work when referring to successful adoption of Predictive Learning Analytics (De Laet et al., 2020; Tsai et al., 2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -