The secrets to improving your NSS score finally revealed

Ruth Fernandes is Head of Research and Insight at University of Manchester Students' Union

At the University of Manchester Students’ Union, we were curious how students answered this one NSS question. “How well does the students’ union represent students’ academic interests?” But if you asked me, honestly, I wanted to understand the secret to obtaining a high NSS score.

What are students truly thinking? Do they think about their academic reps? Do they think about the Students’ Union as a whole? What are a few things we can get right to improve our score in the short term? The only way I knew how to do this and be confident in the results was not by only talking to students, conducting focus groups or conducting correlations; but to create predictive models that helped explain the results statistically.

Modelling predictions

Predictive modelling serves as a robust statistical technique that allows us to explain relationships between various variables simultaneously and predict specific outcomes. In our case, we aimed to identify the factors that significantly influence students’ perceptions of how well the students’ union represents their academic interests.

This analysis goes beyond simple correlations and allows us to understand what variables explain our outcome (a good NSS score) simultaneously and to what extent they can influence the outcome. For a better explanation, please read the report on our website.

Secret sauce

We posed this question to students in our annual insight survey (Build your MCR), pre and post-change in the Likert scale. In 2023, using a 4-point Likert scale, we achieved a 79.7 per cent satisfaction rate in our research (across all UG, PGT and PGR programmes), which is not too far away from our NSS score (73.65%) achieved that year. In 2022, we got a 49 per cent in our annual research (and 41.03 per cent in the NSS) when a 5-point Likert scale was used. Regardless of the difference in score across the two years, we uncovered several key predictors that remained consistent in explaining our NSS score.

The predictors below collectively explain 30 per cent of the model and suggest that if we attempt to increase the scores in these variables, this will likely improve how students rate the effectiveness of the students union in representing their academic interests – which is what we’re all pushing for in the end.

Predictors

The question around satisfaction for starters relies on students’ first instincts when they think about the SU. Our analysis suggests often students how welcomed they felt into the physical building or “branches”, like clubs and societies, of the SU, the community they belong to and the range of opportunities to get involved, and how accessible they felt to them.

Secondly, questions around advice and support encourage students to think about how well our advice service, website, social media, help desk or a member of staff roaming around the building they happened to come across gave them answers to a query.

This question asked whether the SU had a positive, negative or no impact on their university experience and well-being. Again, it relies on the student’s first instinct on whether we positively influence their life.

The question on a students’ awareness of how the SU represents their views and opinions could rely on whether students are aware of the SU. For instacing knowing who our representatives are (e.g. officers, course reps, etc) through our communication channels or personal interaction. The fact these representatives talk to the university in some shape or form, and feeling like the exec officers and advice service are effective forms of feedback.

Additionally, participating in a democratic process (such as voting in the exec officer election) can influence this score – especially if they have run in a leadership election themselves, e.g. as a course rep, they are more likely to feel affiliation with the SU.

Age as a predictor

Interestingly, there was an inverse relationship between age and the NSS score, indicating that older/mature students felt the SU represented their academic interests less. Thus, it is likely that if final year students are over the age of 21, we are likely to get lower scores for this question. Understandably, this is one of those variables we cannot influence (as we can’t decrease a student’s age when they answer the survey), but it should get us thinking about how we communicate and offer our services to such students.

Tackling the possibles

Armed with these insights, we can now take proactive steps to enhance student satisfaction and improve the perception of academic representation by the SU

Our first action point was to elevate the advice and support service, by ensuring its services and update sare actively featured in regular communications going out to students – empphasising its availability, impartiality and “ownership” within the SU.

From here, we realised that our overall aim at improving students’ sense of community mattered when it came to students’ response to the NSS too. It was important all parts of the SU, not just the voice team, placed an emphasis on inclusivity interventions that encourages student participation, community-building and a chance to create friendships. Promotion of various activities, particularly free ones, events and student groups to not only demonstrate the diversity of our student union, but encourage students to actively shape the work we do. This included Promote clubs, societies, and volunteering opportunities that align with both academic and personal interests, ensuring inclusivity for all students. This approach aims to increase students’ awareness of the SU and its functions.

A question of comms

It also felt vital that we strengthened our communication strategies to enhance students’ awareness of how the SU represents their perspectives and concerns, with transparency as a priority. It was important that we show students what we think about things and how we support them, rather than just what we actively do.

It’s also important to tailor messages to different student demographics. For instance, our messaging to seventeen – twenty year olds should differ to those ages twenty-one – twenty-five and twenty-six and above. IT was important we worked with the university to access student data splits that enabled us to tailor our comms this way. For instance for older students, we focused less on the large social vents we do, and more on academic representation work or socials more closely related to the subject.

Student leaders themselves play a pivotal role in pushing out this messaging. By fostering meaningful engagement with student leaders – making it clear what those students are working on, and bringing interested students into the fold to help them complete tasks, should create a more positive attitude towards the work we do as an SU.

This could mean continuing to promote the effective changes initiated by the Executive Officers in response to student feedback. As well as utilising various online and in-person platforms for promotionAdditionally, focus on the benefits of being a student leader which includes making connections, developing employability skills, and contributing to the community could help interest students in running for those roles in the future.

Quick wins

If you have read all this and want to influence your upcoming NSS scores, there are few things you could do to get those quick wins. The first of these are targeted comms to existing student leaders, likely your course reps, part-time officers or society leaders – anyone who already holds a key role within the SU. Generally, these students have higher and more positive things to say about the SU compared to their non-leader peers. Make sure they fill out the survey!

Similarly, crafting messages that target different age groups is important. Highlighting the Exec Officer team’s work and how they are using your feedback at the University level, promoting the services of the SU to increase students’ awareness of the SU and its functions, and encouraging students to let us know (or the officers) what they want them to work on are all ways to bring people into influencing the SU’s work.

In our attempt to understand predictors behind the NSS question on academic representation, we have gained valuable insights that can drive positive change within our SU. By leveraging predictive modeling techniques and data-driven approaches, we can enhance student satisfaction, foster a sense of belonging, and ultimately elevate the overall university experience for all students.

Note: We are continuously testing new variables to see if they may influence our outcome. So, the results above are a current reflection of the variables we have tested and are yet to be evaluated with new variables. As the factors collectively explain 30% of the model, it emphasizes that the factors have a substantial impact on the NSS score but requires more variables to explain the rest of the model.

To access the report, please visit our website or contact our insight team at insight@manchester.ac.uk. If you are looking to find out what factors affect your union’s NSS score, let us know!

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