The data used by StREAM already exists within the university – StREAM collates student activity data from historical and current digital interactions from centralised data points such as campus swipes, tutorial attendance and e-learning portals, and uses it to support staff and students in the student’s learning journey. A key part of the StREAM design is the transparency of the data model (we only measure engagement – we don’t include more contentious areas such as demographics or socio-economic background), which allows us to share the data with both staff and students with no ‘black box’ approach to calculating the engagement scores.
Sharing the data with the student has resulted in them taking control of their own learning journey and the likes of Nottingham Trent University have seen students adjust their behaviour – in the 2017 Student Transition Survey, 74% of students who had logged on to the Dashboard reported having changed their behaviour to raise or maintain their engagement score. Empowering the students enables them to change their levels of engagement without having to rely on university resources to make an intervention. Other universities are using the dashboard and its alerts framework to identify those students that university support services aren’t aware of and get upstream to offer support before they reach the crisis point. We have also seen other customers identify seasonal changes in resource requirements which helps with planning.
Implementing Learning Analytics (LA) can appear a daunting task for some institutions. At Solutionpath, we have developed solutions with a wide range of pre-integrated, out of the box connectors, enabling us to easily digest data and transform it. This reduces the technical burden on IT departments and removes any requirement for internal development resource to be deployed to any LA project involving Solutionpath StREAM technology.
Take a look at our York St John University case study to see how easy it was for them.
The system doesn’t predict grades – it is designed to promote positive behaviours to help achieve positive outcomes. As the data is taken on a daily basis, a student can make adjustments to their daily engagement without the need to wait for the next assessment milestone. Nottingham Trent University research has shown that students wanted to be told that they were at risk of dropping out (94%) or know if the university could improve their chances of progression (97%).
Typically, academics have limited time to spend with students (3-5 times in the first year). The system helps to prioritise their time through identifying those students most at risk, whilst also enabling them to maximise the limited time they do have with students, as the conversations are more focused around their engagement. In the Nottingham Trent University pilot survey, 80% of tutors felt that the data provided by the StREAM Dashboard changed how they worked with students.
Many institutions who have not dipped their toe into Learning Analytics have fears around its use. This installment aims to clear up some commonly held misconceptions around the use of data in this field. “Collecting data about our students for Learning Analytics feels a bit ‘Big Brother” The data used by StREAM already exists within […]
Fill in your details in the form to the right to access the full article.