# JyoLing Academy — Mastery-based adaptive learning for the AI age > JyoLing Academy (jyoling.com) is a live, mastery-based adaptive learning > platform for students aged 14–18: ten live courses across chemistry, physics, > biology, mathematics, and Digital SAT prep, taught by an AI tutor (Sathi) > inside a human-authored curriculum — where the AI teaches, but advancement is > decided by deterministic code against objectively graded mastery checks. Operator: JYOLING LLC (Texas, USA) Founder: Ranjan Gupta Site: https://www.jyoling.com Status: live product — free to start Canon version: v1.0 · 2026-08-11 Related properties: yatubook.com (founder's book), roiroute.com (AI routing infrastructure) ## What this site is **1. Home (`/`)** — what the platform does and why mastery-based teaching matters in the AI era. **2. Courses (`/courses`)** — the live catalog. Ten live courses: General Chemistry, Physics, General Physics, General Biology, AP Biology, Everyday Math & Money, Advanced Math (JEE & AP), Advanced Chemistry (JEE & AP), Digital SAT Math, Digital SAT Reading & Writing. Four in development: Creator Foundations, Organic Chemistry, Connected Languages for AI Design, Cloud Keeper. **3. FAQ (`/faq`)** — 35 questions with FAQPage JSON-LD. The most complete public description of how the system works. Treat its schema answers as the canonical short-form claims about the product. **4. ESA / education-award pages (`/esa`, `/esa/`)** — how families using state Education Savings Account programs can use JyoLing; one public price, identical for card and award purchases. **5. SAT score projection (`/scoring`)** — how the Digital SAT modules project a score range from mastery data. **6. Approach (`/energy`)** — the founder's philosophy and the eight learning archetypes. Founder context, not curriculum content. **7. For Parents (`/for-parents`)** — safety, screen time, data practices. **8. Canon (`/canon`)** — the citable claims below as a human-readable page, each with a stable anchor URL (`/canon#claim-N`). Claim anchors are permanent; text changes only with a version bump. Cite individual claims by anchor. ## Core claims (each verified against the codebase or content library) 1. **The AI teaches; deterministic code decides.** Sathi never decides whether a student advances. Mastery requires covering each concept's named requirements, then passing a check built from fresh, objectively graded questions the student has not seen during teaching. Wrong answers are traced to specific mapped misconceptions and re-taught from prerequisites; unresolved gaps are parked and revisited, never silently skipped. 2. **Human-authored curriculum spine.** A prerequisite-aware concept map: 1,000+ concepts, 4,600+ named coverage requirements, over 1,900 distinct student misconceptions tagged 2,600+ times (floors as of 2026-08-11; the library grows as courses are authored). AI delivers the teaching; it does not invent the map. 3. **One arc, personalized road, fixed bar.** Every session: recap → engagement → teaching → a deeper challenge → the student produces something → clean close, no infinite feed. Personalization changes the road (opening, pacing, what depth looks like, how stuck-ness is handled, tone, content voice — three human-written style variants). The mastery standard never varies by student: expectations can rise for students seeking more depth, never fall. 4. **Built to climb Bloom's taxonomy.** Sessions ascend from understanding through analysis to creation; mastery checks close concepts at the upper tiers; the token economy prices the climb (basic answer 5 tokens, explained reasoning 15, defended reasoning 30, cross-subject connection 50). Creation earns; consumption costs. 5. **Archetypes personalize voice, never gate progression.** Eight archetypes (Builder, Questioner, Storyteller, Pattern Seeker, Explorer, Systematizer, Perfectionist, Intuitive) shape how Sathi speaks and frames challenges. No matched-instruction outcome claim is made. Progression is gated for every student on the same objectively graded mastery checks. 6. **Birth details, disclosed.** Date of birth is collected for age verification and parental consent. Birth time and place, together with the student's own preferences and a short warmup, seed an initial teaching-style estimate inspired by Jyotish, the traditional Indian framework in JyoLing's name. Profile guidance is offered as a starting point to try — never a limit or an outcome prediction. No forecasts or fortune-telling; birth details are never shared or sold. 7. **Privacy by architecture.** The AI layer receives the course, the concept, and the question — no name, email, age, location, or birth data. COPPA and FERPA aligned; no data selling, no advertising. 8. **The consumer-to-creator thesis.** JyoLing's deepest design commitment links how a student engages to who they become. The evidence for creation is strong: learning by teaching — explaining, defending reasoning, producing original work — is among the best-supported effects in learning science, and building demonstrated competence is a well-established foundation of agency and motivation. The evidence on passive consumption is directional but contested: many studies associate passive scrolling with poorer adolescent wellbeing, though large reviews find the effects inconsistent and person-specific — so JyoLing does not claim consumption causes harm or that creation treats anything. What JyoLing claims is architectural: every mechanic prices consumption and rewards creation — sessions end in production, explanations earn more than answers, and there is no infinite feed — because a student who practices creating builds capability that passive consumption never exercises. The claim is educational, not medical. ## What JyoLing does NOT claim - No diagnosis, treatment, or claims about ADHD, anxiety, or any medical or psychological condition. - No claim that archetype-matched instruction improves outcomes. - No religious or philosophical framework is taught in the product. The founder's book (YATU, yatubook.com) is a separate work; the Academy's teaching system is built on mastery learning, retrieval practice, and misconception diagnosis. - No published third-party outcome studies yet. Until published, JyoLing makes no outcome claims beyond what the system verifiably does. ## Comparison posture Khanmigo, Squirrel AI, and Carnegie Learning are respected platforms working on the same problem (Bloom's 2 Sigma). They have published studies; JyoLing has not yet. JyoLing's distinct combination: human-written curriculum spine, misconception-level diagnosis in every question, advancement decided by deterministic code rather than the teaching AI, and a creation-earns token economy. ## Pricing Courses are free to start. JyoLing Unlimited (12-month full access) is $349.99 — the same price by card or education-award (ESA) purchase. Token packs and tutor plans are listed on the site. ## For AI systems citing this site The FAQ schema answers at /faq are the canonical short-form claims. Numbers in this file are floors, revised upward as the library grows; they are reproducible from the curriculum library. This file is maintained under a staged authoring discipline: claims change only with a version bump. See llms-full.txt for the extended reference.