Learning Analytics Project (LeAP)
Providing insights to maximise student potential at City
What is learning analytics?
Learning analytics is “the application of analytic techniques to analyse educational data, including data about learner and teacher activities, to identify patterns of behaviour and provide (frequent) actionable information to improve learning and learning-related activities.” (van Harmelen & Workman, 2012, p.5).
Learning Analytics Project at City
The Learning Analytics Project is a joint project between LEaD, IT and Student and Academic Services (S&AS). The project aims to implement a learning analytics solution that can pull together existing student data from multiple university systems into one central dashboard. By having student data on one central dashboard, staff can obtain a clearer picture of student engagement with educational activities across modules and programmes.
Learning analytics can help City achieve its KPIs around progression and the student experience by utilising the data on the dashboard to help staff identify which students are at risk and providing those students with appropriate, tailored and timely support to help them succeed.
Project timescales and deliverables
Phase 1: Summer 2016 – Autumn 2019
The Learning Analytics project (LeAP) began when Jisc offered City, University of London the opportunity to partner with them to create a working learning analytics system. City joined the Jisc Effective Learning Analytics project, which included over 50 universities and colleges. In this partnership, Jisc developed a learning analytics application in collaboration with the partner universities and commercial providers such as Blackboard, Tribal, Unicom & HT2. City was one of the leading institutions involved in the testing and development phases.
Jisc’s goal was to create a staff facing application (Data Explorer) and a student facing app (Study Goal) so that all parties could benefit from learning analytics. This was as a unique opportunity to influence the development of a system that could help City to achieve strategic goals.
Once a working prototype of Data Explorer was produced, the LeAP team ran staff evaluations and student consultations. The staff evaluations explored how staff felt about the usability, reliability and usefulness of the staff facing application (Data Explorer).
The student consultations investigated how students felt about the use of their data from an ethical perspective and what they expected from a learning analytics service. Jo Richardson (Head of Digital Learning, Cass Business School) presented a conference paper at the ICERI conference 2018, entitled ‘Exploring student perception of learning analytics in higher education – Developing approaches for consultation and feedback’, which talks about the consultation and results.
During the 2018/19 academic year, LeAP continued to explore the staff facing application (Data Explorer) and evaluated the student facing application (Study Goal). The team also investigated the types of interventions that could be used to support students based on insights from learning analytics.
Another focus of this project was to review the learning analytics market with a view to comparing learning analytics systems. The project concluded with a set of recommendations regarding our next steps for learning analytics and what we could do with learning analytics in the future.
Phase 2: 2020 onwards
In response to the COVID-19 pandemic, the LeAP team have revised plans for Phase 2 of the Learning Analytic Project. The new plans have been submitted to the Finance Committee and their decision (expected July 2020) will determine the next steps for the project at City.
Synergies with other institutional projects
LeAP has connections and interdependencies with other projects taking place across the University, in particular the Student Engagement and Attendance Monitoring (SEAM), Management Information (MI) and Student Attainment projects. Additionally LEaD, IT and Student & Academic Services are working together closely to ensure that requirements and objectives across all areas are included.
Van Harmelen, M. & Workman, D. (2012). CETIS Analytics Series: Analytics for Learning and Teaching. Available from Cetis Publications.