Student comment coding: when interpretations differ

Updated Oct 06, 2026

Before turning a short student response into a finding, ask what your category adds to the student's words. Harriet Pattison, Sarah Holmes and Helen Davison examine that interpretive work in a study in the Student Engagement in Higher Education Journal. For us, the useful lesson is to make uncertainty visible when using student comments to guide decisions.

What the researchers asked

The study explored early childhood undergraduates' ideas about an ideal student and what distinguished an ideal early childhood student. It involved 69 students across university-campus and outreach-college cohorts. The paper analyses answers to two questions, mostly single words or short phrases, using predefined dimensions and emerging themes.

For UK student experience teams, this raises a practical question: how much meaning can a brief answer carry? When reviewing feedback about confidence, belonging or future plans, preserve the original question alongside the response. That gives colleagues a basis for judging whether an interpretation is warranted.

Key findings

Academic achievement and caring qualities featured differently. The authors interpreted descriptions of the general ideal student as more academically oriented, while the early childhood ideal placed greater emphasis on caring and vocational qualities. This was an interpretation of written answers, not a measurement of students' capabilities.

Category boundaries overlapped. The researchers debated whether “organised” indicated a mindset or study behaviour. The distinction between attitudes and actions became difficult to sustain in some responses.

Some disagreement remained visible. Where very short answers left meaning uncertain, the authors retained disagreement rather than impose a shared reading.

Tutors examined their own assumptions. Reflecting on their dual roles as teachers and researchers, the authors recognised that their initial accounts framed students in terms of perceived deficits.

This was a single institutional case study with an opportunistic sample, uneven across locations and years of study. The authors make no claim of representativeness and acknowledge that fuller responses could have reduced ambiguity. Their interpretation of students' political positioning was indirect, not based on explicit questions about it.

Apply the lesson to institutional comment analysis

Our suggested starting point is a small review of comments that your team finds hard to classify. Ask reviewers to explain which words support their chosen category and what they have inferred. Keep plausible alternative readings alongside the original response. This gives the team a concrete basis for refining its category definitions and coding language.

Check whether your categories combine different questions. A comment about wanting practical experience might concern placement access, confidence or career exploration. These are possible interpretations, not interchangeable findings. Invite students to discuss anonymised examples and suggest what further context would help. The benefit is a more specific question for the relevant service or programme team.

Agree how unresolved cases will appear in reports. Record exclusions, uncertain classifications and changes to definitions, using the student comment analysis governance checklist to structure the discussion. Explain which conclusions depend on a disputed reading. Decision-makers can then see where more evidence is needed before acting.

Review the assumptions behind the proposed response as well as the coding. If a report describes students as lacking confidence or ambition, identify the words supporting that account and consider other explanations. Ask students what support or opportunities they want before choosing an intervention. This keeps the institutional response connected to their stated priorities.

FAQ

Q: How can we apply this without reviewing every comment manually?

A: Define a review process around the intended decision. Inspect ambiguous examples and check a sample across the categories used in reporting, with clear rules for escalating concerns. Document what was checked and what remains uncertain. These are our proposed local quality checks; the paper did not evaluate an automated workflow.

Q: Does disagreement mean the analysis is unreliable?

A: Examine the reason before drawing that conclusion. Distinguish unclear definitions, overlapping categories and missing context. Report how you handled each, and check whether alternative readings change the practical conclusion. Agreement alone cannot supply information that a respondent did not provide.

Q: What does this mean for student voice beyond coding?

A: Invite students to challenge the report's interpretation and help decide what should happen next. Explain which decisions they can influence and how the institution will respond. Our guide to student feedback, representation and partnership can help define that role. Keep a record of how their contribution changed the proposed action.

References

[Paper Source]: Harriet Pattison, Sarah Holmes and Helen Davison. "From Marginalised Student to Marginalised Professional - Identity and the Early Childhood Student"

DOI: 10.66561/sehej.v7i2.1255

Published: 6 November 2025, Student Engagement in Higher Education Journal, volume 7, issue 2, pages 234–254.