Course Evaluation Evidence for Polish Accreditation (PKA)

In short: For a Polish Accreditation Committee (PKA / Polska Komisja Akredytacyjna) programme evaluation, student course feedback is not a stand-alone exhibit — it is evidence that your internal quality assurance system works. The criteria that matter most are Criterion 10 (the quality assurance policy: designing, approving, monitoring, reviewing and improving the study programme) and Criterion 8 (supporting students''' development and entry into the labour market). Assessors want to see that you collect feedback systematically, analyse it credibly, act on it, and can show the loop closing over time. This guide maps those expectations to concrete outputs and explains where an AI-moderated evaluation tool like Koji produces stronger, more defensible evidence than a stack of Likert averages.

What PKA actually is

The Polish Accreditation Committee (PKA) is Poland'''s independent statutory quality-assurance body, established on 1 January 2002. It conducts mandatory programme evaluations (ocena programowa) of study programmes at Polish higher education institutions, operating under the 2018 Act on Higher Education and Science (the "Constitution for Science"/Ustawa 2.0) and its associated ministerial regulations. PKA is a full member of ENQA and is registered on EQAR, so its criteria are aligned with the European Standards and Guidelines (ESG 2015).

A PKA programme evaluation results in an assessment grade:

• a positive assessment, valid for up to 6 years;
• an outstanding assessment, recognised with an Education Excellence Certificate (Certyfikat Doskonałości Kształcenia) and valid for up to 8 years; or
• a negative assessment.

Because outcomes are high-stakes and tied to a fixed cycle, the evidence you present about student feedback needs to be systematic, longitudinal, and demonstrably acted upon — not a one-off survey snapshot assembled the month before the site visit.

The detailed criteria — and where student feedback lives

PKA evaluates programmes against a set of detailed criteria (Annex 2 to the Statutes of the PKA). Student feedback is directly relevant to several of them, but two are central.

Criterion 10 — quality assurance policy and the improvement cycle

Criterion 10 covers the quality assurance policy and the designing, approving, monitoring, reviewing and improving of the study programme. This is the heart of where course evaluations are assessed. PKA is not asking "do you run surveys?" — it is asking whether your internal quality assurance system systematically gathers evidence (including student opinion), reviews the programme on the basis of that evidence, and feeds improvements back into design. It also looks for the effective influence of students on assuring and improving quality. In practice, assessors want to trace a documented path from student feedback → analysis → decision → change → communicated outcome.

Criterion 8 — supporting students and entry to the labour market

Criterion 8 covers supporting students''' learning, social, academic and professional development and their entry into the labour market, and the development and improvement of that support. Student feedback about teaching, supervision, support services, and employability-relevant skills is evidence here — and longitudinal feedback showing that support has been improved in response to student voice is exactly the "development and improvement" the criterion names.

Where else feedback supports the case

• Criterion 2 (implementation of the programme — content, methods, organisation): student feedback on teaching methods and workload informs review.
• Criterion 9 (public access to information): publishing "you said, we did" responses demonstrates transparency.
• The internal quality assurance system itself, which each HEI designs to reflect its own mission, profile, students, staff and conditions.

Mapping PKA expectations to concrete evidence

PKA expectation	What assessors look for	Concrete output to prepare
Criterion 10 — systematic collection	Feedback gathered routinely, not ad hoc	Standardised evaluation run every cycle across modules, with documented method and dates
Criterion 10 — credible analysis	Evidence that data is genuinely analysed, including open comments	Thematic analysis of qualitative feedback with recurring issues and supporting quotes
Criterion 10 — review & improvement	A documented loop from finding to programme change	Minutes/decisions linking specific feedback to specific actions and revisions
Criterion 10 — student influence	Students demonstrably shaping quality	Records of student involvement and communicated outcomes ("you said, we did")
Criterion 8 — support & employability	Feedback used to improve support and labour-market readiness	Longitudinal feedback on support and skills, with improvements tracked over cohorts
Criterion 9 — transparency	Results and responses accessible	Published summaries of feedback outcomes
ESG/ENQA alignment	Evidence consistent with ESG 1.9 and the European framework	Cross-cohort reporting suitable for both PKA and ESG narratives

Why Likert averages are weak PKA evidence

Most institutions arrive at a PKA review with end-of-semester Likert surveys: a course scored 4.1/5, response rate 28%. This is fragile evidence for three reasons assessors readily probe:

1. It is not analysis. A mean score does not explain why students rated a module the way they did, so it cannot, on its own, justify a programme change under Criterion 10.
2. Open comments are often uncoded. Free-text boxes generate volume that is rarely analysed consistently, leaving the qualitative core of student voice undocumented.
3. The loop is invisible. Without a traceable record from feedback to decision to communicated change, you can show collection but not improvement — and improvement is what the criterion is about.

How Koji produces stronger PKA evidence

Koji is an AI-native course-evaluation platform built for exactly this kind of evidence trail, and EU/GDPR-first by design — important given that PKA evidence concerns Polish students''' personal data.

• Standardised, bias-aware collection (Criterion 10). Students complete a short, AI-moderated conversational interview rather than a static form. The AI probes for specifics ("can you give an example?") and applies that probing consistently across respondents, reducing moderator variability and producing richer, comparable data.
• Automatic thematic analysis (Criterion 10). Koji codes the qualitative feedback automatically, surfacing recurring themes across a cohort with quotes as evidence — turning "we ran a survey" into "here is the analysed student voice and what it told us."
• Closing-the-loop action tracking (Criterion 10, Criterion 8). Findings can be linked to actions and revisions, giving you the documented feedback → decision → change trail PKA expects, and the basis for transparent "you said, we did" communication.
• Longitudinal cohort reporting (Criterion 8). Cross-cohort views show that student support and the programme have been improved over time, which is precisely the "development and improvement" Criterion 8 names.

The same AI interview engine powers the main Koji platform (koji.so) for customer and user research, so the conversational, evidence-linked method is proven well beyond higher education.

An honest note: where Koji is not the whole answer

PKA accreditation is broader than course feedback. Student evaluations are one strand of evidence inside an internal quality assurance system that also covers staff qualifications (Criterion 4), infrastructure (Criterion 5), cooperation with the socio-economic environment (Criterion 6), and more — none of which a feedback tool addresses. A robust submission triangulates student voice with peer review, learning-outcome data, and graduate/labour-market information. Koji strengthens the student-voice and closing-the-loop parts of the case; it does not replace the quality-assurance governance, documentation, and committee processes that PKA evaluates as a whole. Used well, it makes the strongest single weakness in many submissions — thin, unanalysed feedback with no visible loop — into one of the strongest parts.

Practical checklist before a PKA review

1. Run a standardised evaluation across modules every cycle, with documented method and timing.
2. Analyse qualitative feedback thematically — not just report scale averages.
3. Record decisions that link specific feedback to specific programme changes.
4. Communicate outcomes back to students and publish summaries (Criteria 9 and 10).
5. Keep longitudinal, cross-cohort records to evidence improvement (Criterion 8).
6. Triangulate student voice with peer, outcome, and graduate evidence.
7. Confirm GDPR-aligned handling of all feedback data.

Building the PKA evidence narrative

Assessors do not reward raw data; they reward a coherent story. A strong PKA submission presents student feedback as a short narrative for each programme: what we asked, what students told us, what we changed, and what happened next. For example: "Across two cohorts, students consistently described the research-methods module as poorly sequenced relative to the dissertation. Thematic analysis surfaced this in 31 interviews with supporting quotes; the programme board moved the module a semester earlier and added a scaffolding workshop; the following cohort'''s feedback no longer raised sequencing as an issue." That single, evidenced loop demonstrates Criterion 10 (monitoring, review, improvement, and effective student influence) far more convincingly than a page of scale averages — and it is precisely the kind of traceable, quotable trail that AI-moderated interviews and automatic thematic analysis make routine rather than heroic to assemble before a site visit.

Related Resources

• Turning Course Evaluations into NVAO Accreditation Evidence (Netherlands & Flanders)
• Turning Student Feedback into ESG / ENQA Accreditation Evidence
• Course Evaluation Evidence for German Accreditation
• Course Evaluation Evidence for AACSB & EQUIS Business-School Accreditation
• Course Evaluation Evidence for the UK TEF and QAA Quality Review