How Welica Career Fit Quiz suggests careers and study areas
A quick guide first. The research, data and worked example follow below.
This edition describes release discovery-2026-10-13.1. The worked example is fictional.
The short version
For a quick lookWhat you tell us
- Tell us what you enjoy
Answer 30 activity questions from the researched O*NET® Mini Interest Profiler.
- Add how you like to work
Choose up to 4 work preferences, such as teamwork or freedom to make decisions.
What you can explore
- Find careers worth exploring
We compare your answers with 406 career profiles, using job tasks, published data and labelled estimates.
- See what you could study
We suggest study areas that build knowledge for your matching careers.
The interest questions come from a U.S. Department of Labor programme. Welica adds its own preferences and matching rules.
The research behind the method
We build on career-interest research and evidence about what jobs involve.
Where the interest questions come from
- O*NET: a U.S. Department of Labor-sponsored programme providing public career information. [1]
- University researchers: the Mini Interest Profiler was developed with the University of Illinois at Urbana-Champaign and the National Center for O*NET Development. [2]
The studies checked that the questions worked consistently and measured the intended interests. They did not test career-success predictions. [2]
How Welica uses this research
- Six interest areas. Holland’s RIASEC framework groups practical, investigating, creative, helping, leading and organising activities. [3]
- Matching interest patterns. We use the profile-comparison method described in O*NET’s manual to connect your interests with careers. [3]
- Understanding the work. We use job tasks, shared rating definitions and O*NET’s working-condition concepts. [4] [5]
Welica adds preference questions, gap estimates, weights and study-ranking rules. Research on the interest questions does not validate these additions.
Your answers and our career profiles
What you tell us
- 30 interest answers. Five questions for each of six interest areas.
- 4 optional preferences. Freedom to make decisions, teamwork, strict deadlines and accuracy.
- Your study situation. School or college, and the studies you confirm with your answers.
The preference questions are Welica’s own. They are separate from the O*NET interest questions.
How we describe a career
- Start with the work. Define the role and read its main tasks.
- Find a suitable job profile. Keep published ratings where the work is a good match.
- Fill the gaps. Use AI-assisted estimates with fixed scales, available evidence and recorded limits.
Each career has six interest ratings and four working-condition ratings.
How job tasks become interest ratings
Battery EngineerWe connect everyday tasks to researched interest definitions, then rate how strongly each interest describes the whole role.
Working with physical materials and equipment.
Using evidence to understand and solve problems.
One shared 1–7 scale: 1 means the interest does not describe the work; 7 means it describes it very strongly. These two tasks illustrate the connections. Ratings consider the full role, not just one task.
Freedom, teamwork, deadlines and accuracy use their own evidence and 1–5 scales. Gaps are recorded as estimates. All ten ratings for this specialist example are Welica estimates.
4,060 ratings across 406 careers in this version. These are source counts, not an accuracy score.
Some careers share a broad job profile and can receive the same points. Work also varies by employer and setting.
How career matching works
We score every career using fixed formulas. AI helps prepare career data; it does not make a new judgement about you during the survey.
Activities you enjoy We compare your six interest totals with each career’s interest ratings. We look for a similar pattern of stronger and weaker interests.
How you like to work We compare each answered preference with the career’s working conditions. Closer choices give more points.
Our default when both parts can be used
Our default mix, not a proven best mix for every student. Individual results may use a different mix.
The formulas and special cases
Interest points = 50 × (1 + profile correlation). Pearson correlation compares the pattern across the six interest areas. It ranges from −1 to +1; Welica converts it to 0–100 points. [3]
- Each interest answer gives 0–4 points. Five answers give each area a total of 0–20.
- Career interest ratings use a 1–7 scale. Correlation compares the patterns, so the scales do not need to match.
Preference points = 100 − 25 × the absolute rating gap. Choices and role estimates use a 1–5 scale. A one-step gap gives 75 points; two steps give 50. We average the active, answered preferences. Equal steps between choices are a Welica modelling choice.
For the default 50–50 mix, combined points = half the interest points + half the preference points when both parts can be used. For 75–25, we use three quarters of the interest points and one quarter of the preference points. Published and estimated ratings use the same formula.
- No answered preferences: only interests count.
- Six equal interest totals: only answered preferences count.
- One preference: we can use it, but it gives a narrower picture.
- Neither part usable: we offer browsing, without personal match labels.
- Turn a part off: explore a different mix temporarily; saved answers stay unchanged.
We rank using full values. Rounded points can look the same even when the order differs.
These are provisional Welica display categories, not validated cut-offs. Points compare answers with a role profile; they are not a percentage chance of success.
How we suggest study areas
We connect your matching careers with study areas that can help you learn about that work.
- Find study areas connected to all scored careers—not just the first six you see.
- Order each area by its strongest matching connected career, not an average or the number of links.
- Explain the learning connection. Show two career previews first, with a third available to expand.
Check the actual course subjects, entry requirements and professional qualifications. A learning link does not confirm these. Areas without career links remain available to browse.
A worked example
This fictional college student studies biochemistry and is exploring careers more widely. Their answers show stronger investigating and practical interests.
Illustrative case C01 · release discovery-2026-10-13.1
Their answers
Enjoys investigating and practical activities
A career to explore
Battery Engineer
Develop and test battery cells and packs.
A study area to explore
Chemistry
Build knowledge used in battery materials and reactions.
Battery engineering is one career path suitable for this example. Chemistry helps build knowledge for that path. It is one possible route, not a complete qualification.
Figures are rounded here; calculations use full values. All ten Battery Engineer ratings in this example are Welica estimates.
Battery Engineer is Chemistry’s strongest connected career in this example. Its 94.58 career points therefore determine Chemistry’s ordering value. This is not a Chemistry fit percentage. Electrical engineering and Materials science and metals also connect to battery engineering, so several study routes can be worth exploring.
Inspect the inputs and calculation
The student’s six totals, in RIASEC order, are 12, 19, 6, 9, 5, 14. Battery Engineer’s interest ratings are 5.5, 6, 2, 1.5, 2.5, 4.5. Their profile correlation is 0.8457093304, giving 92.2854665200 interest points.
The student’s four condition choices are 4, 4, 3, 5. The role’s condition estimates are 4, 4, 3, 4.5. The four comparison results are 100, 100, 100, 87.5; their average is 96.875.
Half of 92.2854665200 plus half of 96.875 gives 94.5802332600. Chemistry’s next two preview careers are Forensic Scientist at 93.1117 and Chemist at 92.4962. We use the strongest connected score, not their average.
Evidence and validation
This method needs a sound research foundation, reliable career data, correct calculations and testing with students.
Research behind interests and career matching
Published researchMini-IP research supports interest measurement. O*NET’s manual describes the interest-comparison approach we use. [2] [3]
Career data and AI-assisted ratings
Process checkedPublished job data, task-based research definitions, fixed scales and AI review guide the ratings. Sources and assumptions are recorded. [4] [5]
Calculations and ranking behaviour
CheckedAll 406 profiles and formulas checked, including 12 invented student profiles, on/off settings and changes to inputs.
Student understanding and usefulness
NextTest clarity, usefulness and consistency with school and college students across our intended markets.
Weighting and later outcomes
Planned comparisonCompare 50–50 and 75–25 using later preparation choices. Long-term study and career outcomes need further follow-up.
Established interest research and technical checks are in place. Student testing will help evaluate the complete Welica experience.
Read the check details
- The published interest research belongs to the source instrument. It does not validate all Welica additions or every country and age group.
- Welica’s data checks cover completeness, source values and calculations. Invented profiles are test cases, not student research participants.
- An early comparison of estimates with 11 published job profiles helped improve our instructions. Earlier context could reveal reference values, so it was not a blinded accuracy study.
- AI review can share model errors. A task-based framework gives estimates a clear basis; independent human checks are still needed.
Limits to keep in mind
- Interest is not ability. Results do not predict grades, admission or career success.
- Jobs vary. Much of the reference data describes U.S. work. Employers, countries and settings can differ, and some ratings are estimates.
- Study routes need a course check. Look at the actual subjects, entry requirements and professional qualifications.
- Small differences are not certainty. Shared career profiles, estimated ratings and weight choices can affect the order.
We will review new research, improve career data and update the method as student feedback and stronger evidence become available. We will record changes by version, so the basis for each assessment stays clear.
References and method record
- National Center for O*NET Development. About O*NET. Programme sponsorship, purpose and occupational information.
- Rounds and colleagues (2016). Development of the O*NET® Mini Interest Profiler. Development and validation of the 30-question instrument; two research samples.
- Rounds, Hoff and Lewis, editors (2021). O*NET® Interest Profiler Manual. RIASEC foundation, interest measurement and profile correlation; especially chapters 2 and 7.
- O*NET® Content Model. Interest definitions and the separate Work Context concepts.
- Putka and colleagues (2023). Developing occupational interest profiles. Task-based interest-rating materials. Welica’s AI-assisted estimates do not reproduce O*NET’s research or inherit its validation.
Versions, Welica’s additions and credits
This paper describes discovery release discovery-2026-10-13.1, instrument and preference definitions 0.1.0, role ratings 0.2.0, method 0.1.1, scorer point-0.1.0, and study projection max-career-1.
The interest questions and response scale come from the O*NET® Mini Interest Profiler. Welica word help is separate from the original items. Work-preference questions, missing-role estimates, conversion to comparison points, combined weights, match categories and study links are Welica additions.
O*NET’s manual also describes its own occupation-return rules. Welica does not reproduce that complete results algorithm: we use our catalogue, preference component, education presentation and provisional display categories.
O*NET® is a trademark of the U.S. Department of Labor, Employment and Training Administration. O*NET information does not imply endorsement of Welica.
This application includes information from the O*NET Career Exploration Tools by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY-ND 4.0 license. O*NET® is a trademark of USDOL/ETA.
This application includes information from the O*NET 31.0 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license. O*NET® is a trademark of USDOL/ETA. Welica has modified all or some of this information. USDOL/ETA has not approved, endorsed, or tested these modifications.
Website answers, account handover and privacy
Unfinished website answers can be kept for seven days in that browser. They do not follow you to another browser or device. If browser storage is unavailable, they may last only while the tab is open.
A private account-handover link lasts 24 hours. After your account acknowledges that the answers were saved, those answers are removed from the transfer. Outstanding study choices can be retried while the link is valid.
Expired links stop working immediately. Physical deletion of expired records happens later; local draft cleanup occurs on a later visit. Your answers, handover token and account identity are not included in optional website analytics.
A saved assessment, current studies and future study choices remain separate. Editing current studies does not rewrite an old assessment. See the privacy policy for account and deletion information.
Explore your own options.
Use the results to find careers and study routes worth a closer look.