Arrival & Refreshments

Event Opening - Welcome 

John Atherton, Explorance 

Keynote - Shouting Louder or Listening Harder: What Are Our Students Trying to Tell Us? 

This session will look to discuss the challenges in interpreting quantitative and qualitative student survey results and deploying these into meaningful, informed actions to enhance the student experience. The presentation will seek to explore the range of feedback approaches in ensuring a high-quality student experience and the scale of and impact of qualitative feedback and consider how different mechanisms can harness the impact of this rich resource. The session will be informed by developing expectations on quality and student engagement, reflect on practice and examples from the University of the West of Scotland, and consider partnership across academics and professional services to ensure our student’s voices are being heard.

Gavin Lee, University of the West of Scotland

Keynote - Getting Insights Beyond Positive/Negative: Analysing NSS Qualitative Comments

The NSS (National Student Survey) is the main vehicle for student experience data in England. It is the foundation of regulation and enhancement activity. But the qualitative data coming out of the survey is not analysed or reported on nationally, and similarly within institutions there are mixed pockets of engagement with the data. Analysing the qualitative comments, and linking them with wider institutional datasets, provides opportunity for understanding students’ experiences and engaging with their feedback. This session will explore limitations of dichotomous positive/negative coding, challenges of connecting qualitative and quantitative data, but also how data can unlock insights into how students feel about their experience, and their wider mechanisms for providing feedback on their course.

Camille B. Kandiko Howson, Imperial College London

AI-powered Student Voice: Transforming Unstructured Data into Actionable Feedback Intelligence

In this presentation, we showcase how we used MLY to rapidly process and analyse n. In this session, learn how Explorance MLY can inform student experience and retention strategies by distilling valuable insights into student needs and expectations from qualitative feedback. 

Explorance Solutions Engineer Chris Slack will demonstrate: 

- How MLY categorizes comments into topics specific to the student experience.

- MLY's key features to organize, analyse, and act on qualitative feedback.

- Brand-new redaction capabilities provide users with more control over feedback that contains sensitive information.

Explorance MLY is an award-winning, AI platform purpose-built to understand the student experience and amplify the student voice both inside and outside the classroom. Explorance MLY leverages machine learning to provide in-depth analysis of qualitative feedback by determining topic-specific sentiment analysis, identifying feedback patterns, and highlighting recommendations expressed on what to start, continue, or stop doing.

Chris Slack, Senior Solutions Engineer, Explorance 

Networking Lunch

13:00 – 13:45

Structured Networking

John Atherton, Explorance 

13:45 – 14:15

Listening at Scale: Leveraging AI to Understand Diverse Student Experiences

Qualitative survey data has the potential to provide a deeper-level understanding of the student experiences for those who lead the institutions and those who interact with students. Students’ comments offer a rich, authentic and consistent source of information on the student experience but can often be ‘treated as an aside’ or analysed non-systematically.

Comments can range from short phrases to lengthy reflective accounts. Examining thousands of these is a complex, time-and resource-consuming activity. Computer-aided analysis, such as text-mining and AI powered analytical platforms (e.g. MLY), are increasingly utilised by the universities to speed up the analysis, understand prevalent sentiment in student feedback, and promptly identify areas in need of actions. Crucially, these allow open text analysis to be linked to key student characteristics. As a result, analysis can establish relationships between these characteristics and themes or sentiment.

The session will explore how LJMU has used MLY to better understand experience of students from demographic groups that are included in the institutional Access and Participation Plan. It will emphasise the similarities and differences in the priorities of students from different groups. The presenters will use this to reflect on implications for the institutional APP implementation, as well as the enhancement of the student experience more broadly.

Dr Phil Carey & Dr Elena Zaitseva, Liverpool John Moores University

14:15 – 14:45

Accelerating Insights: The Power of Rapid Feedback

In this presentation, we showcase how we used MLY to rapidly process and analyse free text responses from our latest Staff Health & Wellbeing Pulse Survey. By linking the MLY outputs to our core survey data in Power BI, we produced a timely, data-driven summary of key themes —shared with the wider institution with a rapid turnover. We’ll explore how this approach enabled swift institutional response, strengthened trust, and demonstrated the impact of fast, meaningful feedback in a large organisation. 

Kirsty Scanlan, Heriot-Watt University 

14:45 - 15:00

Closing Remarks

15:00 - 17:00

Networking Drinks