What do IT students say about their teaching staff?
Updated Apr 05, 2026
teaching staffinformation technologyFor IT students, teaching quality is felt most clearly when difficult material is explained well and assessment expectations are easy to follow. In the National Student Survey (NSS), comments on Teaching Staff are strongly positive overall (78.3% positive), though sentiment is more measured in technical fields such as Computing (+44.6). Within Information Technology, students rate staff warmly (+30.4) while still pointing to recurring gaps in delivery, feedback, and assessment guidance. The Teaching Staff category in the NSS captures sector-wide views on staff professionalism and support, while CAH11-01-02 groups IT programmes across the UK.
This post draws on 76 anonymous comments from information technology students to show where teaching staff are building trust, where frustration persists, and what institutions can improve first. The aim is practical: help teaching teams understand what students value, where confidence starts to slip, and how survey text can guide better action using a repeatable NSS open-text analysis methodology.
How did we collect and analyse the comments?
We used student surveys to capture direct feedback from those experiencing the teaching first-hand. The dataset comprises 76 anonymous comments from information technology students, and that anonymity encouraged frank views about teaching staff. Surveys gave us enough breadth to capture both praise and criticism across student-staff interactions, which are central to student success and satisfaction in IT. Simple, targeted questions made the feedback easier to analyse and more useful for improvement.
Where do IT students rate teaching staff highly?
Students most often praise staff who are approachable, engaged, and good at making difficult material feel manageable. Terms like "brilliant", "helpful", and "understanding" recur, reflecting satisfaction with both expertise and day-to-day support. Many students value lecturers who simplify complex topics, keep content current, and create interactive, inclusive sessions. Staff who refine their teaching and provide reliable support earn the strongest praise, which helps explain the positive tone around Teaching Staff in IT.
What challenges do students report about teaching and feedback?
Students become more critical when explanations feel rushed, feedback arrives too late, or assessment expectations remain vague. Some comments also raise doubts about staff confidence with specialist material, which can weaken trust and make progression harder. Students describe feedback as insufficient or poorly timed, echoing wider evidence on what makes feedback useful to students, and limiting their ability to improve during a module. This aligns with IT comments where delivery of teaching sits slightly negative (-1.9), so students ask for clearer explanations, more worked examples, and stronger links between teaching points, assessment briefs, and marking criteria.
Which issues recur across comments?
The same friction points come up repeatedly, which gives institutions a clear shortlist for action. Feedback timeliness and clarity recur, especially in relation to complex topics. Students also describe the disruption created by COVID-19, which affected delivery and reduced interaction. Consistent communication, defined office hours, and prompt guidance are repeatedly requested. In IT, uncertainty about marking criteria is a pronounced pain point, with sentiment strongly negative (-43.3) where expectations are not explicit and exemplified.
How did COVID-19 affect teaching and learning?
The rapid shift online tested staff adaptability and exposed how much IT students depend on clear structure and regular contact. Some students noted helpful flexibility and accessible online classes. Others reported inconsistent virtual teaching, bandwidth barriers, and reduced interactivity that made difficult material harder to grasp, a pattern that also appears in student feedback on remote learning in computer science. Student comments underline the value of staff seeking input proactively, adapting online delivery, and maintaining regular touchpoints that help students sustain momentum.
What do students suggest would improve teaching practice?
Their suggestions are practical rather than abstract. Students ask for more face-to-face contact where possible, plus structured opportunities to clarify difficult material. They want assessment briefs that map explicitly to marking criteria computer science students can trust, with annotated exemplars and quick "what to do next" feedback. They also call for predictable communication, visible office hours, and support that recognises diverse needs, including mature students and those with mental health considerations. In IT, these changes would reinforce already positive views of staff while reducing frustration around teaching, assessment, and workload.
What are the implications for higher education?
For higher education teams, the message is clear: in technically demanding subjects, teaching quality is judged as much by clarity and follow-through as by expertise. Strengthening explanations, making feedback more actionable, and making assessment expectations unmistakable can improve confidence and learning. Institutions should support teaching teams to review delivery methods, standardise communication rhythms, and check whether students can act on feedback within the module rather than after it ends. Prioritising these behaviours helps sustain trust and improve outcomes in IT education.
How Student Voice Analytics helps you
If you want to spot these patterns before they affect satisfaction scores, Student Voice Analytics helps you focus effort where it matters most in IT:
- Track Teaching Staff feedback over time, with drill-downs from provider to department and cohort.
- Compare IT results with similar CAH subject families, demographics, mode of study, site or campus, and year of study.
- Produce concise, anonymised summaries for programme reviews, departmental briefings, and quality boards.
- Monitor sentiment by module area and close the loop with students on what changed.
Explore Student Voice Analytics if you need a faster way to turn open-text feedback into teaching improvements.
Request a walkthrough
Book a free Student Voice Analytics demo
See all-comment coverage, sector benchmarks, and reporting designed for OfS quality and NSS requirements.
- All-comment coverage with HE-tuned taxonomy and sentiment.
- Versioned outputs with TEF-ready reporting.
- Benchmarks and BI-ready exports for boards and Senate.
UK-hosted · No public LLM APIs · Same-day turnaround
Related Entries
- Does the IT curriculum match what students need and expect?
- Do computer science students trust marking criteria?
- What does student feedback say about remote learning in computer science?
- Can fixing course communications lift computer science learning?