Thousands of students and teachers across Wales will benefit from cutting-edge data analytics technology to improve student engagement, retention and performance as a result of a funding boost to be announced today by the Higher Education Funding Council for Wales (HEFCW) and Jisc.
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 blog contains text and some of the images used for the invited seminar, UNESCO Chair on Open Distance Learning, University of South Africa (UNISA), Wednesday 12 August 2020
The purpose of this paper is to analyse data on first-year students’ needs regarding academic support services and reasons for their intention to leave the institution prior to degree completion.
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.
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.
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.
Keeping students from dropping out depends on a retention strategy that is based on understanding why they are choosing to leave school in the first place.