Koji vs Unipark (Tivian / EFS Survey): The Honest Comparison for Course Evaluation (2026)
Unipark (Tivian/EFS, formerly QuestBack) is a mature, German-hosted academic survey platform. But for course evaluation specifically, its questionnaire-first model leaves the hard work — reading and coding open text, closing the loop — to humans. Here is a fair, evidence-based comparison with Koji's AI-moderated approach.
Koji Education Team
Product ·
Unipark — the academic edition of Tivian's EFS Survey platform (formerly QuestBack) — is one of the most established online survey tools in European higher education, especially in German-speaking countries. If you are a quality-assurance director, dean, or institutional-research lead deciding between Unipark and Koji for course evaluation, this guide gives you the honest version: where each tool genuinely wins, and where the questionnaire paradigm runs out of road.
The short answer
Unipark/EFS is an excellent research-grade survey instrument. Koji is purpose-built for course evaluation. Unipark gives you complete control over questionnaire design, 35+ question types, respondent and panel management, German data hosting, and SPSS-ready exports — ideal for academic research projects and bespoke studies. But course evaluation has a different job to do: it needs comparable, qualitative-rich, action-ready feedback every semester, at scale, without an army of people coding free-text boxes. That is where Koji's AI-moderated interview model pulls ahead. Koji replaces the static questionnaire with a short adaptive conversation that probes "why," then returns standardized, themed, accreditation-ready evidence automatically.
If your goal is fast, fair, qualitatively deep course feedback that closes the loop with faculty, Koji fits better. If your goal is building custom research questionnaires and managing respondent panels, Unipark remains a strong, credible choice.
What Unipark (Tivian / EFS) actually is
Unipark is the academic programme of Tivian, positioned as an online survey tool "exclusively for students and academic staff." Tivian markets that over 55,000 students, doctoral candidates, and researchers across 25 countries and 400+ universities use the software. Its core strengths, verified from Tivian's own documentation:
- Powerful questionnaire design — more than 35 question types, from single/multiple choice and sliders to complex matrix questions, with full layout control for users who know HTML/CSS.
- Dynamic logic — filters, lists, loops, and triggers for conditional routing based on answers and participant data.
- Statistical reporting and export — multi-faceted online statistics plus export to SPSS, Excel, and other formats for downstream analysis.
- Respondent and panel management — recruitment, fieldwork administration, and automated reminders via an integrated mail server.
- German data residency — all software and survey data are hosted in Germany in a data centre certified to ISO 27001.
These are real advantages, particularly for researchers who need a flexible, statistically rigorous survey environment with EU data hosting. For survey research, Unipark is hard to fault.
Where the questionnaire model limits course evaluation
The constraint is structural, not a knock on Unipark's engineering. Every questionnaire tool — Unipark, EvaSys, Qualtrics, LimeSurvey — collects two things: closed Likert ratings and open-text boxes. The Likert numbers are easy to aggregate but shallow ("4.1 out of 5" tells you little about why). The open text is where the insight lives — but it arrives as an undifferentiated pile of comments that someone has to read, code into themes, and summarise by hand, every department, every semester. In practice this is where most evaluation programmes break down: response rates are low, the qualitative analysis is slow or never happens, and faculty rarely see what changed as a result.
A questionnaire also cannot ask a follow-up. If a student writes "the assessment was unfair," a paper or web form simply records it. There is no probe for which assessment, why it felt unfair, or what would have helped. The single most valuable moment in qualitative feedback — the follow-up question — is exactly what a static instrument cannot do.
How Koji approaches the same problem differently
Koji is an AI-native course-evaluation platform built on a conversational interview engine — the same engine that powers customer and user research on the main Koji platform (koji.so). Instead of a form, each student has a short, text-based, AI-moderated conversation that adapts to what they say:
- Conversational probing — when a student raises something vague, the AI asks a neutral, standardized follow-up, surfacing the why a Likert grid never reaches.
- Automatic thematic analysis — responses are clustered into themes with representative quotes and sentiment, so a department head reads a synthesis in minutes rather than coding hundreds of comments.
- Bias-aware standardized moderation — every student gets a consistent, neutral interviewer, which standardizes wording and probing across cohorts and reduces the interviewer-variance and question-wording effects that plague ad-hoc qualitative work.
- Closing the loop — findings convert into trackable actions, producing a documented "you said / we did" trail for students and for accreditation.
Side-by-side comparison
| Dimension | Unipark (Tivian / EFS) | Koji |
|---|---|---|
| Core paradigm | Online questionnaire (Likert + open-text) | AI-moderated conversational interview |
| Qualitative depth | Open-text boxes; no follow-up probing | Adaptive follow-ups that probe "why" |
| Analysis of free text | Manual coding, or export to SPSS for the team to analyse | Automatic thematic analysis with quotes and sentiment |
| Standardization / bias control | Consistent question wording; no probing standardization | Standardized AI moderation reduces wording and interviewer variance |
| Closing the loop | Not built in; handled outside the tool | Built-in action tracking ("you said / we did") |
| Survey design flexibility | Excellent — 35+ question types, full logic, panels | Focused on evaluation interviews, not bespoke survey design |
| Research panels / longitudinal studies | Strong panel and respondent management | Cohort and longitudinal evaluation reporting |
| Data residency & security | Hosted in Germany, ISO 27001 certified | EU hosting, GDPR-aligned data handling |
| Best fit | Academic research surveys, custom studies, panels | Semester course evaluation with qualitative depth and accreditation evidence |
| Public pricing | Academic licensing; as of publication, public pricing was not available | See edu.koji.so |
When Unipark is the better choice
Honesty matters with an evidence-driven audience, so to be clear: Unipark may be the right tool for you in several situations.
- Bespoke research surveys. If your primary need is designing complex research questionnaires — branching logic, experimental designs, matrix batteries — and exporting clean datasets to SPSS, Unipark's flexibility is a genuine strength that a focused evaluation tool does not try to match.
- Panel management. If you run longitudinal research panels with recruitment, incentives, and fieldwork management, Unipark is built for exactly that.
- A strict German-hosting mandate. If your institution's policy specifically requires data hosted in Germany under ISO 27001, Unipark satisfies it directly. (Koji is EU-hosted and GDPR-aligned, which meets most European procurement requirements, but a Germany-only clause is worth checking.)
- You already standardise on it for research. If Unipark/EFS is your institution's research survey backbone, there is real value in tool consolidation — though many institutions run a dedicated evaluation tool alongside it precisely because the jobs differ.
In several of these cases the pragmatic answer is both: keep Unipark for research and statutory numeric reporting, and add Koji for the qualitative, conversational, closing-the-loop layer that turns course feedback into action and accreditation evidence.
Where Koji is the better choice
- You want qualitative depth at scale without manually coding thousands of comments.
- You need comparable evidence across departments for quality assurance and accreditation (ESG, national agencies), with standardized moderation.
- You want students to see that feedback led to change, improving trust and response rates over time.
- You value formative, mid-semester feedback that can still help the current cohort, not just summative end-of-term ratings.
The bottom line
Unipark/EFS is a strong, credible, German-hosted survey platform with deep roots in academic research — and for research surveys and panels it remains an excellent choice. But course evaluation is a distinct job. It rewards conversational depth, automatic thematic analysis, standardized bias-aware moderation, and a closed feedback loop — the things a questionnaire, however well engineered, cannot provide on its own. For institutions whose priority is better, fairer, more actionable course feedback and accreditation-ready evidence, Koji is built for exactly that.
See how Koji works for your institution at edu.koji.so.
How to run a fair side-by-side trial
Procurement decisions in higher education deserve evidence, not vendor claims — including ours. If you are weighing Unipark against Koji, the most honest way to decide is a parallel pilot on the same courses in a single semester.
- Pick three to five representative modules. Include at least one large lecture course (where qualitative analysis usually breaks down) and one small seminar (where statistical significance is weak and narrative matters most).
- Run both tools on the same cohorts. Use your existing Unipark/EFS questionnaire for the numeric indicators you already report, and run a parallel Koji conversation for the same students.
- Compare the outputs your committee actually uses. Look past the raw data and ask: which tool gives a department head a usable synthesis in under ten minutes? Which surfaces a specific, actionable issue the other missed? Which produces evidence you could hand an external reviewer without further work?
- Measure response quality, not just response rate. Count how many responses contain a concrete, actionable suggestion versus a one-line rating. Conversational follow-ups tend to lift the share of actionable feedback noticeably.
- Test the loop. Take one finding from each tool, make a change, and see which tool lets you document and re-evaluate that change without spreadsheet gymnastics.
A pilot like this usually settles the question quickly, because the difference is not about survey quality — Unipark's surveys are excellent — but about how much human labour stands between raw feedback and a decision. Whichever tool you choose, insist on seeing it run on your courses before you sign.