(1) Conduct an analysis of the variables that best predict performance and progression in selected modules and/or programmes with large and very large cohorts, using existing data to provide a baseline.
- HEA data: Leaving Cert, socio-economic
- Learning Support usage
- Library usage
- VLE engagement
- Assessment performance
(2) Develop a protocol to improve the academic experience of students through the delivery of timely, personalised and actionable student feedback throughout their participation. This will involve working closely with module leaders and course directors to gather data on student engagement and select learning markers; develop protocols for student participation and opt-out mechanisms; define the conditions under which students would be contacted; establish relevant and potential interactions with established support systems in UL (e.g. Learning Centres; Student Advisor System); follow up individually with students when required; and evaluate the impact of the intervention from the perspective of all stakeholders and from a student’s success standpoint, thus informing the design of the process. Important to involve students in developing the language of communication around the whole process.
For more information, contact Sarah Gibbons and Angelica Risquez