Student Voice Analytics for Chemical Process and Energy Engineering — UK student feedback 2018–2025

Scope. UK NSS open-text comments for Chemical Process and Energy Engineering (CAH10-01-09) across academic years 2018–2025.
Volume. ~1,928 comments; 97.4% successfully categorised to a single primary topic.
Overall mood. Roughly 49.0% Positive, 47.6% Negative, 3.4% Neutral (positive:negative ≈ 1.03:1).

What students are saying

The dominant story in this discipline is assessment clarity. Feedback is the single largest category (9.0% share) and trends clearly negative (index −30.0), echoed by Assessment methods (4.6%, −37.3) and Marking criteria (4.3%, −50.8). Students’ concerns are classic and actionable: what “good” looks like, how work is judged, and whether feedback is timely and useful. All three topics are more prominent than in the sector and carry a more negative tone.

Operational delivery also shapes the experience. Workload appears frequently (5.6% share, −46.7; well above sector by share), with Organisation and management of course (3.4%, −32.4), Scheduling/timetabling (2.1%, −27.9), and Communication about course and teaching (1.3%, −38.1) reinforcing the same signal: students want predictability, transparency and a single source of truth. Delivery of teaching (5.9%, −12.8) leans negative, whereas Teaching Staff (6.4%, +10.9) is recognised positively but sits well below the sector on tone.

Set against these frictions are strong people- and community-led positives. Opportunities to work with other students draws an unusually large share (7.1% vs 2.0% sector) and a positive tone (+21.4), suggesting that structured peer collaboration is valued. Career guidance and support (3.6%, +33.8), Student life (2.9%, +41.6), Personal development (2.5%, +56.8), Library (1.7%, +55.9) and Availability of teaching staff (1.7%, +50.2) stand out as strengths. Placements/fieldwork/trips are less central here by volume (1.8% vs 3.4% sector) but are positive when mentioned (+27.7).

Finally, Student support appears less often than sector (3.6% vs 6.2%) and is net negative (−11.6), indicating an opportunity to make support routes clearer and more responsive.

Top categories by share (discipline vs sector)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Feedback	Assessment and feedback	9.0	7.3	1.7	−30.0	−14.9
Type and breadth of course content	Learning opportunities	8.3	6.9	1.4	+19.0	−3.6
Opportunities to work with other students	Learning community	7.1	2.0	5.2	+21.4	+20.3
Teaching Staff	The teaching on my course	6.4	6.7	−0.4	+10.9	−24.6
Delivery of teaching	The teaching on my course	5.9	5.4	0.4	−12.8	−21.6
Workload	Organisation and management	5.6	1.8	3.8	−46.7	−6.7
Assessment methods	Assessment and feedback	4.6	3.0	1.6	−37.3	−13.5
Marking criteria	Assessment and feedback	4.3	3.5	0.7	−50.8	−5.2
Student voice	Student voice	3.7	1.8	2.0	−36.4	−17.2
Student support	Academic support	3.6	6.2	−2.6	−11.6	−24.8

Most negative categories (share ≥ 2%)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Marking criteria	Assessment and feedback	4.3	3.5	0.7	−50.8	−5.2
Workload	Organisation and management	5.6	1.8	3.8	−46.7	−6.7
COVID-19	Others	2.3	3.3	−1.0	−37.9	−5.0
Assessment methods	Assessment and feedback	4.6	3.0	1.6	−37.3	−13.5
Student voice	Student voice	3.7	1.8	2.0	−36.4	−17.2
Organisation, management of course	Organisation and management	3.4	3.3	0.0	−32.4	−18.4
Feedback	Assessment and feedback	9.0	7.3	1.7	−30.0	−14.9

Most positive categories (share ≥ 2%)

Category	Section	Share %	Sector %	Δ pp	Sentiment idx	Δ vs sector
Personal development	Learning community	2.5	2.5	0.0	+56.8	−3.0
Student life	Learning community	2.9	3.2	−0.2	+41.6	+9.5
Career guidance, support	Learning community	3.6	2.4	1.2	+33.8	+3.7
Opportunities to work with other students	Learning community	7.1	2.0	5.2	+21.4	+20.3
Type and breadth of course content	Learning opportunities	8.3	6.9	1.4	+19.0	−3.6
Teaching Staff	The teaching on my course	6.4	6.7	−0.4	+10.9	−24.6
Learning resources	Learning resources	3.2	3.8	−0.6	+9.5	−11.9

What this means in practice

Start with assessment clarity. Use checklist-style rubrics mapped to each learning outcome, publish annotated exemplars that show “why this is merit/distinction,” and set a realistic feedback service level agreement that you can consistently meet. A short feed‑forward note alongside grades (“next time, do more of X, less of Y”) increases perceived usefulness and reduces repeat queries.

Stabilise the operational rhythm. Nominate a single owner for scheduling and course communications; publish a weekly “one source of truth” update that flags what changed and why; and set clear escalation routes when plans shift. Where workload pinch points are unavoidable, show the plan to smooth peaks and protect turnaround times.

Double down on the positives. Protect structured peer collaboration (it is both high‑volume and well‑liked), keep career guidance visible and proactive, and make it easy to access staff at predictable times. Library support is a bright spot—extend its reach by signposting targeted study skills around assessment tasks.

Data at a glance (2018–2025)

Top topics by share: Feedback (≈9.0%), Type and breadth of course content (≈8.3%), Opportunities to work with other students (≈7.1%), Teaching Staff (≈6.4%), Delivery of teaching (≈5.9%), Workload (≈5.6%).
Cluster view by share:
- Assessment & feedback (Feedback, Assessment methods, Marking criteria, Dissertation): ≈18.5%.
- Delivery & ops (Placements/fieldwork, Scheduling/timetabling, Organisation & management, Communication about course and teaching, Remote learning, Workload): ≈15.5%.
- People & growth (Personal Tutor, Student support, Teaching Staff, Availability of teaching staff, Delivery of teaching, Personal development, Student life): ≈23.8%.
How to read the numbers. Each comment is assigned one primary topic; share is that topic’s proportion of all comments. Sentiment is an index from −100 (more negative than positive) to +100 (more positive than negative), averaged at category level. Sector columns show the same measures for a like‑for‑like benchmark.

How Student Voice Analytics helps you

Student Voice Analytics turns open‑text survey comments into clear, prioritised actions. It tracks topics and sentiment over time (by year), so programme, department and school leaders can see which categories are driving experience and how tone is shifting.

It enables like‑for‑like sector comparisons across CAH codes and by demographics (e.g., year of study, domicile, mode of study, campus/site, commuter status), so you can evidence progress against the most relevant peer group. You can segment by site/provider, cohort and year to target interventions precisely, and share concise, anonymised summaries and representative comments with partners and programme teams. Export‑ready outputs (for web, decks and dashboards) make it straightforward to brief the whole institution as well as fine‑grained departmental audiences on priorities and progress.