When Scores Miss the Feedback Story

Audio briefing based on Student Voice Weekly issue #12.

This Week

This week, the episode discusses feedback literacy, OfS scrutiny, and NSS prep. A longitudinal study shows why feedback-use scores can miss real change. The main topics are grouped below by student voice practice, research, sector developments, archive context, and practical application.

Main Topics Discussed

Student Voice Practice

This week we started the first trials of our comment review pipeline which includes full-text search across all comments, so teams can move from a dashboard theme to the exact student comments behind it and review coding decisions in context.

Research Spotlight

Sector Watch

From the Archive

Practical Application

July NSS results usually create two connected jobs: explaining headline movement quickly, and giving teams enough evidence to act without losing rigour.

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Transcript

Hi, and welcome to Student Voice Weekly. I'm Dr Stuart Grey, founder of Student Voice, and today's theme is feedback evidence: how universities move from headline scores to the student comments, context, and action trail underneath them.

Today I'd like to talk about something that sits underneath a lot of student voice work, and that's the gap between having data and really understanding what students are actually saying.

I still teach part-time at the University of Glasgow, and that matters for this topic, because feedback is not an abstract policy thing. Students experience it directly. Staff experience it directly. And if we're honest, a lot of the problems around feedback do not come from people not caring. They come from things being unclear, too slow, too scattered, or too hard to turn into action.

So the key thing this week is not just whether a feedback score has gone up or down. It is whether we can see what sits underneath that score. Are students talking about feedback arriving too late? Are they saying the comments are vague? Are they confused about marking criteria? Are they getting different messages from different staff? Or are they getting feedback, but still not knowing what to do next?

Those are all different problems. And if we group all of them under one big heading called assessment and feedback, we risk choosing the wrong fix.

That is why this week we started the first trials of our comment review pipeline. One of the things it includes is full-text search across all comments. That means a team can go from a dashboard theme to the exact student comments behind it, and then review the coding decision in context.

That might sound like a small technical feature, but it is actually very important. Because the data is not the finish line. The point of the analysis is to start better conversations. Students talking to staff. Staff talking to students. Quality teams talking to programme teams. People looking at the same evidence and saying, right, what is this really telling us and what do we do next?

This is where comments are so valuable. A score can tell you something has moved. Comments tell you what students think moved, why they think it moved, and what they were expecting instead.

The research item that really connects with this is a paper by Kurt Coppens, Greet Langie, Naomi Winstone and Lynn Van den Broeck on feedback literacy.

Feedback literacy is basically about whether students can understand, evaluate and use feedback, rather than just receive it. And I think that's a really useful distinction, because universities often talk about feedback as if the job is finished once the comments have been returned.

But from a teaching point of view, that is not really the end of the process. If I give a student feedback and they do not understand what it means, or they cannot see how to use it in the next piece of work, then the feedback has not really done its job. It exists, but it has not helped.

The researchers followed engineering students across three undergraduate years. They used a feedback orientation scale, reflective logs and interviews. The scale did not show clear growth, and the final longitudinal sample was small, so we should not overclaim from it. But the qualitative evidence was useful. It suggested that students' relationship with feedback was developing through reflection, behaviour change and more purposeful use.

The reason I think this matters is that a flat score can make it look as if nothing is changing. But actually, students might be changing in ways the score is not picking up. They might be getting better at working out which comments matter. They might be getting more confident about asking questions. They might be learning how to deal with criticism without just feeling knocked by it. They might be starting to use feedback as part of their learning rather than treating it as a judgement at the end.

So for universities, the practical point is to make sure we are not treating one score as the whole story. If we want to know whether feedback is working, we need to ask students about the process. Was it clear? Was it timely? Did it connect to the marking criteria? Did it tell them what to do next? Did they have a chance to use it before the next assessment?

And this is where free-text comments are really useful. Because the difference between "I got feedback" and "I knew what to do with it" often only appears when students explain the experience in their own words.

The sector story this week makes all of this feel less optional.

The Office for Students has imposed ongoing conditions on the University of Northampton after a quality investigation into computing courses. The case covered 2022-23 provision and included issues around student support and the clarity of assessment feedback. Northampton has to report back after 12 months.

Now, the mistake would be to see this only as a Northampton story. It is more useful to see it as part of a bigger shift. Student voice is moving from being an engagement activity to being part of the evidence base for quality.

That does not mean every feedback problem is a regulatory problem. It does mean that institutions need to be able to show what students raised, how those patterns were identified, who owned the response, and whether anything changed.

And again, the key word for me is clarity. Clear assessment briefs. Clear marking criteria. Clear written feedback. Clear support routes. Clear records of what students said and what the university did with it.

If students are saying feedback is unclear, a university needs to know what unclear means in practice. It might mean the language is too general. It might mean the feedback does not match the criteria. It might mean the brief itself was confusing. It might mean the feedback arrives after the next assessment is already underway. These are different issues, and they need different actions.

NSS 2026 makes this even more immediate. The survey has closed, and results are expected on 8 July, subject to final quality review. That gives universities a very short window to make sure they know how the results will be read.

And by that I do not just mean who makes the slide deck. I mean who looks at the comments. Who checks the themes. Who joins the NSS evidence up with module evaluations, rep feedback, complaints, pulse surveys, and all the other routes where students are already telling you what is going on.

Because the problem in universities is rarely that there is no data. Often there is too much data, sitting in too many places, with too little time to make sense of it. What we are looking for is useful, authentic feedback, and a way to turn that into dialogue.

If I were looking at comments on feedback this week, I would separate five things.

First, timing. Did the feedback arrive early enough to help?

Second, clarity. Could students understand what was being said?

Third, alignment. Did the feedback connect to the marking criteria and the assessment brief?

Fourth, consistency. Were students getting the same message across different modules and markers?

And fifth, usability. Did students know what to do next?

That last one is really important. Because sometimes a comment can be perfectly clear to the person who wrote it, but still not useful to the student. "Be more critical", for example, might be true. But if the student does not know what being more critical looks like in that discipline, it does not move them forward.

The risk is that all of these comments get collapsed into one broad category. Assessment and feedback. Maybe the sentiment is negative. Maybe the score is down. But that does not tell the programme team what to do on Monday morning.

A timing problem might need a workflow change. A clarity problem might need better guidance and examples. A consistency problem might need calibration between markers. A usability problem might need feed-forward activities, discussion, or a chance to apply feedback before the next assessment.

So a good analysis should not just say, students are unhappy with feedback. It should help people work out which kind of feedback problem they have.

And this is why being able to search across comments matters. Sometimes you need to find the exact phrase students are using. Sometimes you need to check whether a theme is actually widespread or whether it is just a striking example. Sometimes a department needs to see the comments in context before it trusts the analysis enough to act on it.

Search does not replace good analysis. But it does make the analysis easier to challenge, check and use. And that is where trust comes from.

The one thing I would try this week is very simple.

Take one recent set of assessment or feedback comments and split them into three piles: timing, clarity and usability.

Do not start with a complicated framework. Just ask, is this mainly about when feedback arrived, whether students understood it, or whether they knew how to use it?

Then look at the actions you had planned. Do they actually match the pattern in the comments?

If most of the comments are about usability, a faster turnaround target will not solve the main problem. If most of the comments are about clarity, telling students again that feedback is available will not be enough. If most of the comments are about timing, beautifully written feedback may still arrive too late to help.

So the takeaway is this: separate feedback comments by the kind of action they require.

That is it for this week. The full set of links and summaries is in Student Voice Weekly. If you work with student feedback and want the research, regulation and sector signals in one place each week, you can subscribe at studentvoice.ai.