At the Utrecht University (UU) the team participating in the USO-project on ‘Differentiation Using Blended Learning and Learning Analytics’ (DUBLLA) has been working on different projects aiming at implementing different forms of Learning Analytics (LA).
As more and more tools are being used in real classrooms to support educational activities, more and more data is generated carrying information about students, classes, learning objects, grades, etc. When this data is processed, aggregated and visualized it can provide insights into the learning experiences of individual students, classes and even entire universities. Teachers can, for instance, see to what degree students master specific concepts, which misconceptions they have and adapt their teaching based on this information. Students might monitor their own progress, see how well they do in relation to their peer.
The main technical product of the DUBLLA project is LearnLytics, a platform for learning analytics. This platform is built around an xAPI-compatable learning record store that can accept events from any educational system and integrates a battery of analytic services computing customizable reports and visualizations for teachers and students. The future of LA at UU Learning Analytics is one of the few educational technologies that promise to become mainstream in the near future. UU has substantial plans to further develop Learning Analytics initiatives (see here for more information). TeacHERs MOnitoring their Students (THERMOS) is another effort to leverage educational data for supporting students in optimizing their learning experience (more information can be found here)
The development of LearnLytics platform will continue. In a follow-up project, the focus will be made on the link between the diagnostic phase and the remedial phase. Based on specific omissions in knowledge or a misconception a student may have, personalised study material can be offered within the LearnLytics platform. The USO-project “Towards personalised education” will focus on shaping the online remediation steps.
Read the full news message on the website of Utrecht Applied Data Science.
Source: Utrecht University.