Evaluating Weekly Predictions of At-risk Students at the Open University: Results and Issues
Evaluating Weekly Predictions of At-risk Students at the Open University: Results and Issues
Author(s): Drahomira Herrmannova, Martin Hlosta, Jakub Kuzilek, Zdenek ZdrahalSubject(s): Social Sciences, Education, Higher Education
Published by: European Distance and E-Learning Network
Keywords: Institutional case study; Institutional innovation and development, case study; Learning analytics; Predictive modelling
Summary/Abstract: Improving student retention rates is a critical task not only for traditional universities but particularly in distance learning courses, which are in recent years rapidly gaining in popularity. Early indications of potential student failure enable the tutor to provide the student with appropriate assistance, which might improve the student’s chances of passing the course. Collated results for a course cohort can also assist course teams to identify problem areas in the educational materials and make improvements for future course presentations.
Journal: European Distance and E-Learning Network (EDEN) Conference Proceedings
- Issue Year: 2015
- Issue No: 1
- Page Range: 200-208
- Page Count: 9
- Language: English
