At Queen’s, the student voice is a pivotal element of Strategy 2030. Listening and responding to student feedback is essential for improving the student experience within the university. The student surveys are instrumental in identifying areas for improvement and recognising good practices. While quantitative data often takes centre stage due to its ease of interpretation, qualitative data offers a more nuanced view of the student experience.
To harness the full potential of qualitative data, Queen’s has partnered with Student Voice to develop a Large Language Model (LLM) specifically for higher education. This AI tool is designed to extract valuable insights from student comments, focusing solely on the content of the feedback without external biases. The LLM has been trained exclusively on student comments from several years of National Student Survey (NSS), Postgraduate Taught Experience Survey (PTES), and Postgraduate Research Experience Survey (PRES) surveys.
Queen’s was one of the first universities to work with Student Voice and continues to lead the way in our implementation of its capabilities. Our relationships with Student Voice and evasys lead to us being included as a case study in a recent WonkHE article.
What AI Offers at Queen's
Student Voice provides coded comment files, categorising each comment by theme and sentiment (positive or negative). These files are available at the School level for NSS and QSS surveys, offering a quantitative overview of the comments. Additionally, the Student Survey Team can compile reports for specific services like the Library or One Elmwood.
The integration of AI analysis into the surveys platform (evasys) is underway, allowing module coordinators to view comments grouped by themes and sentiment scores. This feature aims to streamline the process of identifying key issues and areas for improvement.
Benefits of AI Summaries
AI-generated summaries of survey comments provide a concise overview of student feedback, highlighting positive aspects and areas for improvement. These summaries save time and effort in identifying key issues, enabling staff to focus on actionable insights.
Student Perspective
Amy Smith, Students’ Union President, shared her thoughts on the AI-powered feedback system: “The AI analysis of our comments has made a huge difference to the student services offered at Queen’s. This is a great step forward for our students’ learning as lecturers are able to embed student feedback into their teaching with ease. The improvements in course content has also allowed for a more accessible and enhanced student experience at Queen’s.”
Faculty Perspective
Professor Phil Hanna, who leads the AI initiative, shared his thoughts: “The use of AI in analysing student feedback has been transformative. The insights gained from the AI analysis have enabled us to more easily and quickly identify important trends, and from this to take appropriate action to improve the overall student experience.”
How AI Helps You
The student comments are a crucial tool for understanding the quantitative data from closed questions. Overview tables help pinpoint areas with concentrations of negative comments, indicating potential areas for improvement. Conversely, positive comments reveal aspects that students appreciate. Despite the efficiency of AI summaries, reviewing individual comments remains important for a comprehensive understanding.
Conclusion
The use of AI at Queen’s University Belfast is revolutionising the way student feedback is analysed and utilised. By leveraging AI-powered tools, the university can better understand and respond to the student voice, ultimately enhancing the student experience and driving continuous improvement.
