Learning Analytics service

We provide support for teaching innovation processes, promoting the use of evidence obtained from data analysis in the decision-making processes of the UOC's academic staff. To achieve this, the Learning analytics team focuses on two areas: 

  • Providing academic data
    • We are responsible for the data mart, the UOC repository for data concerning the activity of students and teaching staff, and as such we support research and innovation projects carried out by the University's teaching staff and researchers. We provide data on students' use of the University, enrolment, keeping up with assessment activities, academic results, and access to different areas and services on the campus including classrooms, teaching materials and areas for interaction. We also have information compiled by other groups, such as the student and teacher satisfaction surveys administered by the Planning and Quality department, and the information on new students compiled by the Professional Guidance and Career Services.

To request this service, users must complete the Support for the use of data in research and teaching form, which can be found here.

  • Advanced analysis of academic data
    • We work with institutional registries to provide evidence that can help in decision-making processes, trying to respond to questions raised by different bodies and management committees at the University. With an agile incorporation of research processes, we design and implement ways of assessing institutional innovation projects, we develop analytical perspectives on issues of strategic importance to the University, and we help the different groups involved make decisions with the generation of new evidence-based knowledge. Among other projects, we have analysed the impact of the pandemic on students' academic achievement and assessed some institutional innovation projects, such as ESPRIA (designed to support and improve the experience of new undergraduate students) and Niu challenge, and we are particularly interested in analysing factors associated with student success.