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 at City
The Learning Analytics Project (LeAP) at City is exploring how Learning Analytics can be used to improve students’ educational experience and support the institution’s education performance indicators relating to progression and attainment.
The University already holds a large amount of data about students, which is essential in evidencing learning, reporting and providing support when needed. Learning Enhancement and Development (LEaD), Information Technology (IT) and Student and Academic Services (S&AS) are exploring the potential value of implementing a Learning Analytics system. This system will have the capability of pulling together existing data from multiple university systems into one central location. The goal is to utilise this data to provide staff with a clearer picture of student engagement with educational activities across modules and programmes. Thereafter, this information could enable staff to assist students in areas where they need the most help so that they can feel supported and be successful at City.
How might learning analytics benefit City as an institution?
Learning Analytics could support City’s strategic priorities and Key Performance Indicators (KPIs) relating to student progression by enabling a more informed approach to support. There is also potential to contribute to City’s KPIs relating to the student experience and student employability as learning analytics can improve students’ well-being and ability to succeed. The system could also provide insights into student engagement through better provision of reporting information.
Project timescales and deliverables
Funding for this project has been granted for 3 years (Summer 2016-Summer 2019).
Summer 2016 – Summer 2018
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 now includes over 50 universities and colleges. In this partnership, Jisc developed a Learning Analytics application in collaboration with the partner Universities and commercial providers. City has been 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 consultation investigated how students felt about the use of their data from an ethical perspective and what they expected from a Learning Analytics service.
Autumn 2018-Summer 2019
For this academic year, LeAP will continue to explore the staff facing application (Data Explorer) and evaluate the student facing application (Study Goal). The team will also investigate the types of interventions used to support students based on insights from Learning Analytics. Another focus of this project will be to review the Learning Analytics market with a view to comparing Learning Analytics systems to ensure that we choose the right one for City. The project will conclude with a set of recommendations on how City should proceed with Learning Analytics.
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) and Management Information (MI) projects under the Modernising Administration for Students (MAfS) banner. 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: http://publications.cetis.org.uk/2012/516