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OU Analyse is a system powered by machine learning methods for early identification of students at risk of failing. All students with their risk of failure in their next assignment are updated weekly and made available to the course tutors and the Student Support Teams to consider appropriate support. The overall objective is to significantly improve the retention of OU students.
This Moodle plugin adds a new predictive model to identify students that are likely to miss assignment due dates. The model automatically generates insights for teachers about these students.
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It is my personal opinion that Canonical's Contributor Agreement program is, in its current form (as of Sept 2010), flawed such that I can not participate in it due to the risks it brings me and my Free software contributions.
D. Porta, Z. Tuncer, M. Wirth, and M. Hellenschmidt. Proceedings of the Eighth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM 2014), Rome, Italy, page 227-232. International Academy, Research and Industry Association (IARIA), (August 2014)
D. Porta, Z. Tuncer, M. Wirth, and M. Hellenschmidt. Proceedings of the Eighth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies (UBICOMM 2014), Rome, Italy, page 227-232. International Academy, Research and Industry Association (IARIA), (August 2014)