Course Evaluation Evidence for Baltic Accreditation: HAKA, AIKA & SKVC
A buyer's guide to turning student course-evaluation feedback into accreditation-ready evidence for the Baltic quality-assurance agencies — HAKA (Estonia), AIKA (Latvia), and SKVC (Lithuania) — all of which operate under the European Standards and Guidelines (ESG).
Koji Education Team
Product
Estonia, Latvia, and Lithuania run three separate, ESG-aligned, EQAR-registered quality-assurance agencies — but they share a common DNA: institutional and study-field accreditation built on the European Standards and Guidelines (ESG), explicit student involvement, and a strong expectation that universities act on student feedback. This guide maps what each agency expects to the concrete course-evaluation evidence a modern platform can produce, and is written for QA directors, vice-rectors for studies, and institutional-research leads preparing for Baltic accreditation.
Short answer
For all three Baltic agencies — HAKA (Estonia), AIKA (Latvia), and SKVC (Lithuania) — course evaluation is not a box-ticking survey. Reviewers want evidence that you collect student feedback systematically, analyse it credibly, act on it (closing the loop), and can demonstrate improvement over time. The ESG Standard 1.9 ("ongoing monitoring and periodic review of programmes") and Standard 1.7 ("information management") sit underneath every Baltic framework. A platform that produces standardized, comparable, longitudinal evidence with documented follow-up actions maps directly onto what these panels score.
The three agencies at a glance
| Country | Agency | Scope | ESG / EQAR status |
|---|---|---|---|
| Estonia | HAKA — Estonian Quality Agency for Education (until June 2022 known as EKKA) | Institutional accreditation; assessment of study programme groups | ENQA full member; EQAR-registered |
| Latvia | AIKA — Quality Agency for Higher Education (a substructure of the Academic Information Centre, AIC) | Accreditation of higher education institutions and study directions (study fields / groups of programmes); programme licensing | Operates under the ESG; ENQA / EQAR |
| Lithuania | SKVC — Centre for Quality Assessment in Higher Education (Studijų kokybės vertinimo centras) | External evaluation and accreditation of institutions and study programmes / fields | ENQA, EQAR and CEENQA member |
All three are aligned with the European Standards and Guidelines for Quality Assurance in the European Higher Education Area (ESG), which is the single most important fact for evidence planning: build for the ESG and you are substantially ready for any of the three.
What each agency expects from student feedback
Estonia — HAKA (formerly EKKA)
HAKA's institutional accreditation is explicitly developmental: its purpose is to support strategic management and quality culture. Student voice is structurally embedded — each HAKA assessment committee includes at least one student member alongside an international expert and a member from outside higher education. For self-evaluation reports, institutions are expected to show a functioning internal quality system in which student feedback is collected, analysed, and demonstrably used to improve teaching and study programme groups.
Latvia — AIKA
AIKA accredits study directions (groups of programmes) and institutions and ensures the external quality-assurance system operates according to the ESG, while promoting improvement of institutions'' internal quality-assurance systems. Decisions are taken by a Study Quality Committee. In practice this means a self-assessment for a study direction must evidence that each programme systematically gathers student feedback and feeds it into review — and that the internal QA system, not just an isolated survey, is mature.
Lithuania — SKVC
SKVC defines quality-assurance aims, evaluation criteria and measurement indicators, and uniquely operates a National Student Survey (NSS), created with the Lithuanian Students'' Union, whose summarised, depersonalised results are submitted to the expert panels that evaluate institutions and study fields. Institution-wide student surveys are used to identify specific strengths and areas for improvement, complemented by meetings and roundtables with students. For a Lithuanian review, your own course-level evaluation evidence should align with, and add depth to, the national-survey picture the panel already sees.
Mapping accreditation requirements to Koji outputs
The table below translates the shared Baltic / ESG expectations into the specific evidence a platform like Koji generates. Koji is an AI-native course-evaluation platform: it runs short, AI-moderated student interviews, performs automatic thematic analysis, applies bias-aware standardized moderation, and tracks closing-the-loop actions.
| Accreditation requirement (ESG / Baltic) | What reviewers want to see | Concrete Koji output |
|---|---|---|
| ESG 1.9 — ongoing monitoring & periodic review | Systematic, recurring collection across all courses | Standardized evaluation cycles with comparable, course-by-course coverage |
| Student-centred quality culture (HAKA, AIKA) | Evidence student voice shapes decisions | AI-moderated interviews that capture the why behind ratings, with thematic summaries for committees |
| ESG 1.7 — information management | Reliable, analysable data on the student experience | Automatic thematic analysis with representative quotes and longitudinal trend data |
| Closing the loop ("you said, we did") | Documented actions taken in response to feedback | Action-tracking records linking feedback to changes, exportable per programme |
| Comparability across programmes / study fields (AIKA study directions; SKVC fields) | Consistent evidence across many courses | Bias-aware standardized moderation so cohorts and instructors are comparable |
| Longitudinal improvement narrative | Cohort-over-cohort trends, not a single snapshot | Multi-cycle reporting showing whether issues were resolved |
| Alignment with national surveys (SKVC NSS) | Course-level depth behind aggregate national data | Qualitative, course-specific evidence that explains the numbers |
A practical evidence checklist for a Baltic self-assessment
- Coverage. Show that evaluation runs every cycle across programmes, not selectively. Patchy coverage is a common panel criticism.
- The "why," not just the score. Aggregate Likert averages rarely persuade an expert panel. Pair every quantitative trend with thematic, quoted evidence of the underlying reasons — exactly what conversational, AI-moderated collection produces.
- Documented action. For each major theme, record what changed. The closing-the-loop record is the highest-value evidence and the most commonly missing.
- Comparability. Use standardized, bias-aware collection so a panel can compare across a study direction or field without worrying that differences are survey-design artefacts.
- Trend over time. Bring at least two or three cycles so you can show improvement, not just a status quo.
- Data protection. All three agencies operate in the EU; ensure your evaluation data handling is GDPR-aligned and, for Lithuania, dovetails with the depersonalised national-survey approach.
Where a traditional survey tool may be enough — and where it is not
Honesty serves this audience. If your institution already runs a mature internal QA system with staff who manually code open-text feedback and maintain action logs, a conventional survey tool (or a national survey like Lithuania''s NSS) may already satisfy a panel. The friction appears at scale: when hundreds of courses generate thousands of comments, manual thematic analysis and closing-the-loop documentation become the bottleneck, and evidence quality drops. That is precisely the gap an AI-native platform closes — and it is why the strongest self-assessments increasingly pair national/aggregate data with richer course-level qualitative evidence.
The same AI interview engine Koji uses for education also powers customer and user research on the main Koji platform (koji.so); in higher education it is applied to teaching and learning, turning short student conversations into accreditation-grade evidence.
The bottom line
HAKA, AIKA, and SKVC differ in structure but converge on the ESG and on a simple expectation: collect student feedback systematically, understand it, act on it, and prove improvement over time. Build your evidence around those four verbs — collection, analysis, action, and longitudinal proof — and a single, well-structured course-evaluation programme will serve an Estonian, Latvian, or Lithuanian review with minimal rework.
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