- Enter active learners. Use the cohort that is actually eligible to complete during the forecast period.
- Enter the baseline completion rate. Use a comparable historical or planning rate expressed as a percentage.
- Add the expected rate adjustment. Enter a positive or negative change in percentage points, not a relative percent change.
- Review the adjusted rate. The calculator caps the adjusted completion rate between 0% and 100%.
- Compare counts. Review forecast completions, expected non-completers, and the baseline completion count to understand the size of the modeled change.
AI Tutoring Completion Forecast Estimator
This estimator forecasts how many active learners may complete a AI tutoring program based on a baseline completion rate and a clearly stated percentage-point adjustment. It also shows the implied non-completer count and the adjusted completion rate so the forecast can be reviewed rather than treated as a single unexplained total.
Use it for cohort planning, internal targets, or comparing conservative and optimistic scenarios. The adjustment is intentionally simple: it does not claim that engagement changes cause completion. Instead, it gives program teams a transparent way to model an expected improvement or decline while keeping the result capped between 0% and 100%.
Forecast assumptions
learners
%
pts
Result
—
forecast completions
Adjusted completion rate—
Expected non-completers—
Baseline completions—
Adjusted completion rate = clamp(Baseline rate + Rate adjustment, 0%, 100%)
Forecast completions = Active learners × Adjusted completion rate
Forecast completions = Active learners × Adjusted completion rate
The rate adjustment is measured in percentage points. For example, moving from 70% to 75% is a +5 point adjustment, not a 5% relative increase.
What the result means
The main result is the expected number of learners who complete the program under the adjusted completion-rate scenario.
This is a scenario forecast. It does not establish that any specific intervention will cause the modeled change in completion.
Given: 850 active learners, a 68% baseline completion rate, and a +8-percentage-point adjustment.
Calculation: Adjusted rate = 68% + 8 points = 76%. Forecast completions = 850 × 0.76 = 646. Baseline completions would be about 578.
Result: 646 forecast completions.
This scenario implies about +68 completions versus the baseline, assuming the cohort size stays unchanged.
What is a percentage-point adjustment?
It is an arithmetic change to the completion rate. A baseline of 68% with a +8 point adjustment becomes 76%, whereas an 8% relative increase would be calculated differently.
Should I use enrolled learners or active learners?
Use the population that still has a realistic opportunity to complete in the forecast window. Mixing total historical enrollment with a current completion rate can distort the result.
Why is the adjusted rate capped at 100%?
A completion rate cannot exceed every learner in the modeled cohort. The calculator also prevents negative completion rates when a large negative adjustment is entered.
Can I use this to predict an individual learner?
No. The model forecasts a cohort-level count from aggregate rates; it does not estimate the probability that a specific learner will complete.
How should I compare two program scenarios?
Keep the learner count and baseline definition consistent, then change the adjustment for each scenario. Comparing the resulting completion counts shows the operational impact of the different assumptions.