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 article focuses on the success of African American students at black colleges and universities and how remedial programs can help students to be more successful in college.
HT2 Labs announces a 3-part Open Learning Experience (OLX) exploring how to use data to create engaging learning experiences that boost retention and help drive ROI.
Students interacting with universities often leave behind a virtual footprint that is used to gauge how well the university has managed to help and prepare these students. Learning analytics is using this data to analyze, measure, collate data, and more about the progress made by both students and educators.
Following the Data Matters conference, Paul Bailey from Jisc looks at the potential for learning analytics to improve teaching practice and the student experience.
This post is some thinking around Col's PhD resulting from some conversations and presentations from this year’s wonderful ALASI2018 conference held recently in Melbourne.
This article discusses the success of African American women in college and provides interventions that can help this demographic of students be more successful in their college journey.
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