Evidence of competence, from what learners actually did.
FEONA scores entrepreneurial competence from observed behaviour and artefacts produced in the real world, mapped to EntreComp — instead of asking participants to rate themselves on a questionnaire.
Status: in development. FEONA Oy is part of the autumn 2026 cohort of the Helsinki Education Hub EdTech Incubator. We have not run a pilot yet, and we are looking for programmes willing to be the first.
The problem
Programmes build real capability, then measure it with a questionnaire.
empirical studies of entrepreneurship education reviewed by Nabi and colleagues in 2017. Impact research predominantly uses short-term, subjective outcome measures, and under-describes the pedagogy being tested.
existing assessment instruments for entrepreneurial competence are self-report. The field measures what people say about themselves.
of the most-used methods in Finnish practice — stories and business-idea assignments — involve nobody outside the classroom, so they generate nothing observable to record.
The programme cannot show its funder that competence developed. The teacher carries the reporting burden with no instrument.
How it works
Four steps, and none of them ask a participant to rate themselves.
Challenge
Work that has to create value for someone outside the group. Peers and teachers are excluded — that exclusion is the test for whether the activity counts at all.
Observation
The instructor records behaviour against a scaled indicator rubric running from novice to expert, rather than filling in a rating scale afterwards.
Peer defense
The participant defends the work to peers against a fixed grid written by staff. Evaluating is itself observable, so the session produces evidence on both sides.
Evidence
An artefact from the real world is attached — a payment, a signature, a reply from a stranger — and mapped to EntreComp competences at a progression level.
Assessment is carried out by certified instructors. The validity of the evidence comes from calibrating the people who record it, not from the software. Training and certification are part of the product, not an add-on.
No aggregate score, and no ranking between participants. Gaps in the evidence are shown as gaps, never as a score of zero. A single number attached to a person becomes a label, and we do not produce one.
The map
Twenty competences, four areas, eight levels of progression.
Challenges do not form a chain. Each one writes evidence to several competences at once, which is why this is a wheel rather than a tree — EntreComp itself states that no sequence is implied between competences.
What it is built on
Four sources, and none of them are ours.
EntreComp — JRC, 2016
The European Commission's reference framework for entrepreneurial competence: fifteen competences across three areas, on an eight-level progression. This is what evidence is mapped to.
Lackéus — OECD, 2015
Value creation pedagogy. The defining test is whether learners create value for people outside their own group. Competence develops whether or not the attempt succeeds, so a failure still produces evidence.
Schelfhout, Bruggeman & De Maeyer, 2016
Assessing entrepreneurial competence through scaled behavioural indicators instead of Likert self-report. The direct methodological precedent for the rubrics.
Sarasvathy — effectuation
Supplies the novice-to-expert contrast that grades every indicator scale, because that contrast was derived from comparing expert entrepreneurs with novices rather than invented.
What we do not claim. No instrument in this literature has been shown to predict venture outcomes from a competence profile. FEONA evidences development, not destiny. Anyone telling you their assessment predicts who will succeed is ahead of the evidence.
Who we are
A non-profit that runs programmes, and a company that measures them.
AurinkoLab ry
Designs and runs non-formal learning programmes in entrepreneurship and STEM. Grant funded, works inside European project consortia. This is where the learning happens.
FEONA Oy
Builds the platform that turns what participants did into evidence a funder can read. Sold to other programme providers, not only used by AurinkoLab.
Co-founder and education programme lead, AurinkoLab. Doctoral research on human–AI collaboration, intention and digital twins. Commercial and technical background.
Co-founder, AurinkoLab. Builds the research base and maps the certification landscape. Bachelor's student, Faculty of Science, University of Helsinki.
Communications and audience growth. Reaching the programmes, teachers and participants the work depends on.
Contact
We are looking for pilot sites.
Two or three challenges, instructors willing to record what they see, and an honest conversation afterwards about whether any of it worked.