Capture the lesson
Mark a planned lesson as taught, log it manually, or upload a screenshot, worksheet, PDF, or notes. FellowScholar drafts the learning log for your approval.
FellowScholar turns today’s lesson into a short, personalized Recall session. It finds the weak spots, strengthens them, and tells you exactly what needs your attention tomorrow.
The learner recognized equivalent ratios but initially used additive reasoning on a missing-value problem.
Next retention check: tomorrow at 4:30 PM
Most homework assigns more work before anyone knows what the learner retained. FellowScholar starts by finding out what actually stuck.
FellowScholar works around your curriculum and your teaching—not the other way around.
Mark a planned lesson as taught, log it manually, or upload a screenshot, worksheet, PDF, or notes. FellowScholar drafts the learning log for your approval.
A few hours later, the learner completes a short session without notes or hints. FellowScholar records what can be recalled, explained, and applied independently.
FellowScholar distinguishes forgetting, partial understanding, a misconception, or a prerequisite gap—then supports only what needs attention.
You receive what stuck, what did not, the evidence behind it, and the one action worth taking before the next lesson.
The workflow is designed to make the learning coach faster—not to create another system to manage.
Explore the three moments that matter most.
PDF, DOCX, image, notes—or take a photo on your phone.
Completed in 9 minutes
FellowScholar keeps the initial Recall phase separate from teaching. That way, your report shows what the learner knew independently—not what the AI helped them produce.
Baseline evidence is recorded before the system reveals instruction.
FellowScholar targets terminology, partial understanding, misconception, or prerequisite knowledge.
A new item checks whether the support transferred beyond the original question.
FellowScholar adapts how it asks, supports, and reports without turning each grade band into a different product.
Short prompts, concrete examples, prerequisite checks, and clear escalation when a learner remains stuck.
More multistep reasoning, explanation in the learner’s own words, and clearer documentation of assistance.
Research, argumentation, source evaluation, and evidence that distinguishes tutoring from work completed independently.
You decide how lesson material and learner responses are stored, whether approved outside AI services may process minimized content, and when information is deleted.
Simple household controls. Technical details stay out of the daily learning workflow.
“The challenge wasn’t giving our children access to AI. It was knowing what actually stuck—and where the learning coach should step in.”
FellowScholar began inside a real homeschool household with learners in seventh, ninth, and twelfth grade. The Family Alpha is being shaped around the daily work of one learning coach managing three very different learners.
Set up your household, capture one real lesson, and let FellowScholar turn it into a measurable learning loop.