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Student Evaluation and Learning Analytics - StELA

StELA Data to Action Flow

The use of, and discussions about learning analytics has become increasingly prevalent in higher education. Learning analytics involves the collection of educational data, such as grades, survey responses, or number of accesses to online resources from various learning environments to better inform how students learn and engage in their course or programme. 

Student Focus Groups

Analysing existing approaches and potential improvements to Student Feedback across a range of disciplines

Staff Focus Groups

Analysing existing approaches and potential improvements to Student Feedback across a range of disciplines and learning contexts. Informed by existing focus group themes used in the SHEILA project and developed by the StELA project team

Composite Report of Focus Groups

Broad thematic analysis comparing and contrasting staff and student responses from focus groups

Final report and recommendations

Initiated to provide a policy basis for the use of data to enhance student success. Findings support the creation of policy, the continued engagement of staff and students in building credibility in data and feedback mechanisms and the need to collect and present data that is accurate, understandable and easy to read. 

Staff Survey

Exploring staff attitudes to the use of educational data and how the use of existing datasets can be used to enhance student learning, enhance services provided by the University and ultimately close the feedback loop

Student Survey & Feedback Mechanisms Policy

Providing an operational framework to enable a coordinated approach for the implementation of surveys and other student feedback or evaluation mechanisms

At UL, the issue of survey fatigue has been raised at a number of fora within the University over the past number of years. The Student Evaluation and Learning Analytics (StELA) project will look at why we ask students for feedback, the most effective methods to use and how we can best use the feedback provided by students. As students interact with the virtual learning environments and other university systems, what insights can we draw from this existing data? Can the insights from multiple feedback mechanisms be triangulated to provide reliable information that can be acted upon? 

The StELA project has 4 main goals

Encourage student engagement

To encourage student engagement

Build credibility

To build credibility with staff in our student evaluation mechanisms

Use existing datasets

explore how existing datasets can be used to provide feedback on the student experience

Co-create policy

Co-create policy on the use of data and on student evaluation

National Forum for the Enhancement of Teaching and Learning

The StELA project is funded by the National Forum for the Enhancement of Teaching and Learning under the Strategic Alignment Teaching and Learning Enhancement (SATLE) fund.