Institution:
University of Westminster
Location:
London, UK
"“This is a huge difference numerically in the number of comments and a major difference in insight, bringing together various aspects of the student experience. We have created environments where students can feel genuinely heard and valued.''"
Key benefits:
- Advanced qualitative analysis of student feedback from NSS and institutional surveys
- Increased feedback analysis capacity from 7000 to 35000 comments annually
- Insightful reporting with integrated quantitative and qualitative data
- Efficient feedback loop closure
Challenge – Manual Analysis of Student Qualitative Feedback
The University of Westminster has been thematically analyzing open comments from student surveys for several years. Prior to the 2023-24 academic year, it manually conducted a thematic analysis of National Student Survey (NSS) responses from about 3,000 students per year, developing themes and uncovering patterns in the open-comments responses.
“A major challenge that Westminster has faced is the limited in-house capacity to utilize the wealth of student feedback we receive from both external and internal sources: sources from which we can draw insight, cascading the wisdom generated through recommendations at all levels of seniority,” said Institutional Research Analyst Matthew Abley. “For a long time, the Institutional Research team only had scope to focus on the NSS free text comments. Working individually, Kirsty Bryant, Senior Institutional Researcher, recruited student researchers to aid this process. The training, upskilling and deployment of the students took in the region of six months.”
This was a long and laborious task – especially in comparison with quantitative data, which is often received very rapidly by decision-makers – and the University recognized it needed to change its practice via a more innovative approach.
Solution – Implementing AI to Process Open-ended Feedback for Faster Insights
Westminster has become one of the first UK universities to analyze the results of the NSS using Explorance MLY, as part of a wider partnership agreement to support its institutional need for enhanced qualitative analysis of student experience insights emerging in surveys
Matthew highlighted how MLY has provided a platform to “more capably triangulate Westminster’s emergent quantitative and qualitative data with that of the national picture and match the rapidity of both sets of outputs”. The ability to complement the various data types has allowed for a far more streamlined reporting process that empowers Westminster to make sound recommendations in line with the University strategy, transforming insight into action through College Executive Groups, the University Planning Committee, and the University Executive Board, amongst others, he added.
“This is a huge difference numerically in the number of comments and a major difference in insight, bringing together various aspects of the student experience. We have created environments where students can feel genuinely heard and valued. This has meant fostering open communication channels and proactively demonstrating a commitment to acting upon the feedback we receive rather than just receiving it. Students rightly expect their feedback to lead to tangible improvements in teaching, resources and support services. Our commitment to responsiveness fosters a culture of trust and collaboration between students and the institution. It is one thing to open a feedback loop, but it is another greater challenge to close it, and to close it with evidenced impact.”
Outcome – Richer Insights to Enhance the Student Experience and Close the Feedback Loop
Explorance MLY has revolutionized the way the University of Westminster analyses student and staff qualitative feedback, as also reported by Kirsty in Times Higher Education this year.
“With MLY, we have gone from analyzing around 6000-7000 NSS comments per year to being able to analyze in the region of 32,000-35,000 comments across multiple internal and external datasets across the last academic year alone,” Matthew revealed.
“Using AI and machine learning to aid our analysis of open-ended comments has created space for a culture shift within the institution towards good data and robust evaluative practices across the institution,” Matthew reflected. By rapidly analyzing open-ended feedback with Explorance MLY, Westminster enhanced the integration of quantitative and qualitative data in evaluating student-facing interventions. This advancement helped build robust Type 2 and Type 3 evidence bases, supporting alignment with regulatory requirements of their Access and Participation Plan and the Teaching Excellence Framework.
Matthew added: “One of the increased aspects of value of student feedback, certainly through our implementation of MLY, has been students’ awareness of the power and impact of their individual voice.” With Explorance MLY the University of Westminster can now quickly communicate how they are using this feedback, showing students how their input leads to actionable recommendations for academic colleagues, thereby enhancing the feedback experience and building mutual expectations.
