How Zelvi is meant to help, and how we check.
What Tier 4 means
Under the Every Student Succeeds Act, Tier 4 means a product has a well-specified logic model informed by research, and an ongoing effort to study its effects. It is not a claim that Zelvi has been shown to raise results. We will update this page when a study reaches a higher tier.
The problem
Mistakes that never get fixed.
Inputs
- The instructor’s own course material
- A list of common mistakes for each idea, reviewed by teachers
- Class lists from the LMS or school system
- Zelvi: a tutor that explains with pictures and voice
Activities
- Students practise from the course material
- On a wrong answer, Zelvi names the mistake and re-teaches it from the material
- A hint comes before any answer, and the student tries again
- Students still stuck are passed to a teacher or tutor, with their attempts attached
- Teachers see who is stuck on what, and send a short re-teach to those students
Outputs
- Practice attempts and retries after a re-teach
- Mistakes matched to the reviewed list
- Hand-offs to people
- Re-teach checks sent by teachers
Short term
Within weeks
- More stuck students get it right on their own next try
- Fewer students repeat the same mistake
- Teachers know who needs help before the test
Mid term
Within a term
- Higher scores on the unit tests for the targeted ideas
- Fewer students needing remediation
Long term
Within a year
- Higher course pass rates
- Fewer students dropping, failing or withdrawing
What the model assumes
- Students learn more when they still do the thinking, so Zelvi gives a hint first and keeps the answer hidden after a first miss.
- Feedback works best when it is about the specific mistake and comes while the idea is still fresh.
- Teachers act on a short, clear list of who is stuck and on what.
The research
What the model rests on.
Nearly 1,000 high-school maths students. With plain ChatGPT, practice scores rose 48%. Once it was taken away, exam scores fell 17% below students who never had it. A tutor built to give hints, not answers, largely removed that harm.
Bastani et al., PNAS, 2025A randomised trial in a Harvard physics course. Students using a carefully designed AI tutor learned significantly more, in less time, than in an active-learning class.
Kestin et al., Scientific Reports, 2025Feedback is among the strongest influences on learning, most of all when it tells the student about the task and how to improve, not about themselves.
Hattie & Timperley, Review of Educational Research, 2007Classroom assessment used to adjust teaching, rather than to grade, produced substantial learning gains across many studies.
Black & Wiliam, Assessment in Education, 1998Practising recall of material led to better long-term retention than re-studying it.
Roediger & Karpicke, Psychological Science, 2006
The study plan
How we find out if it works.
- Design
- Each pilot compares a course with the same course in an earlier term, or with a section that did not use Zelvi. The comparison is agreed with the institution before day one.
- Measures
- The measures below, defined in writing before the pilot starts. Every number is shown with its sample size.
- Timing
- Class map at week 2, evidence report at week 6, course outcomes at the end of term.
- Independence
- Institutions can export their data for their own research office or an outside evaluator. We publish results whether or not they favour Zelvi.
- Next level
- Once enough pilots have finished, we will run a study with a comparison group and statistical controls, aimed at ESSA Tier 3 (“promising evidence”).
What every pilot measures
- First-retry recovery
- Share of struggles resolved on the student’s next attempt.
- Eventual recovery
- Share resolved within the term, and how long it took.
- Repeat misconception
- Students who made the same mistake again after help.
- Hand-offs to people
- How many reached a tutor or instructor, and what happened next.
- Material gaps
- Questions your material could not answer, by topic.
- Course outcome
- Assessment scores and drop / fail / withdraw rate against your baseline.
Want to see the report a pilot produces? See a sample week-6 report.