What is Acadevo?

Acadevo is India's first truly adaptive learning platform purpose-built for students in classes 6 through 10. Unlike traditional ed-tech apps that serve the same static content to every student, Acadevo uses Item Response Theory (IRT), Bayesian Knowledge Tracing (BKT), and spaced repetition algorithms to build a unique learning path for each student in real time.

Every question a student answers informs the system about their ability level, and the next question is dynamically selected to sit in their Zone of Proximal Development, the sweet spot where learning happens fastest. The result is a practice experience that is never too easy, never too hard, and always moving students forward.

📚

47,000+ Questions

A massive calibrated question bank spanning five subjects, 312 topics, and difficulty levels from foundational to expert.

👤

Three Dashboards

Purpose-built interfaces for students, parents, and teachers with distinct tools, insights, and controls for each role.

🧠

Proven Science

Built on IRT, BKT, and SM-2 spaced repetition, the same frameworks used in GRE, GMAT, and leading global assessment systems.

Subject Coverage

SubjectTopicsQuestionsClasses
Mathematics728,640+6-10
Science727,200+6-10
Social Science725,760+6-10
English484,800+6-10
Hindi483,840+6-10
Total31230,240+6-10

Board coverage: All content is aligned to CBSE curriculum with ICSE mapping in progress. Questions are tagged by chapter, topic, and sub-topic for granular tracking.

The Adaptive Learning Engine

Powered by Item Response Theory (IRT)

Most learning apps assign questions randomly or in a fixed sequence. Acadevo's adaptive engine treats every practice session as a real-time assessment, continuously estimating each student's ability and selecting the optimal next question. This is the same family of algorithms that powers the GRE, GMAT, and other high-stakes adaptive tests, now available for daily practice.

Question Properties

Each question in the bank has three IRT parameters calibrated through data:

  • a (Discrimination): How well the question differentiates between ability levels
  • b (Difficulty): The ability level at which a student has a 50% chance of answering correctly
  • c (Guessing): The probability of getting it right by chance (typically 0.25 for MCQ)

Student Ability (Theta)

Each student has a continuously updated ability estimate (theta) per topic, measured on a standard scale:

  • Starts at 0.0 (average) for new students
  • Ranges from -3.0 (foundational) to +3.0 (expert)
  • Updated after every single response using maximum likelihood estimation

Selection Algorithm

The engine uses Fisher Information to select the next question:

  • Calculates information value of every available question at student's current theta
  • Selects the question with maximum information (most diagnostic value)
  • Applies exposure control to prevent overuse of any single item

The Learning Zone

The engine keeps every student in their Zone of Proximal Development (ZPD), the range where questions are challenging enough to promote growth but achievable enough to maintain motivation.

Too Easy Low engagement Zone of Proximal Development Optimal learning happens here Questions matched to ability Too Hard Frustration zone Student ability level (theta)

Skill Levels

LevelTheta RangeDescriptionStudent sees
Foundational-3.0 to -1.5Significant gaps in prerequisite conceptsBasic concept-building questions
Developing-1.5 to -0.5Partial understanding, inconsistent applicationScaffolded practice problems
Proficient-0.5 to +0.5Solid grasp of core conceptsGrade-level standard problems
Advanced+0.5 to +1.5Strong command, can apply to novel situationsApplication & analysis questions
Expert+1.5 to +3.0Deep mastery, ready for competition-level workOlympiad-style challenges

BKT Mastery Tracking

Beyond ability estimation, the engine uses Bayesian Knowledge Tracing (BKT) to estimate the probability that a student has truly mastered each skill. BKT models four parameters: initial knowledge (P(L0)), probability of learning on each attempt (P(T)), probability of slipping (knowing but answering wrong, P(S)), and probability of guessing (not knowing but answering right, P(G)).

After each response, the system updates the mastery probability. A skill is considered mastered when P(mastery) exceeds 0.85. This ensures students are not just answering correctly by chance but have genuinely learned the concept.

0%
Not started
35%
Developing
65%
Progressing
85%
Mastered

For Students

A practice experience that adapts to you, every single session.

3.1 Daily Practice Targets

Students see a simple dashboard showing their daily practice goals across all subjects. Each subject requires 5 questions per day. As questions are answered, the rings fill up in real time, giving students a clear sense of progress and completion.

Math
5/5 Done
Science
5/5 Done
3/5
English
3/5 Done
0/5
Soc Sci
0/5 Pending
0/5
Hindi
0/5 Pending
Today's Progress 13 / 25 questions

3.2 Practice Sessions

Each practice session follows a structured adaptive flow. The engine selects each question in real time based on the student's ongoing performance within the session.

1. Select
Subject
2. Engine selects
optimal question
3. Student
answers
4. Theta
updated
5. Next question
selected
6. Session
summary

Sessions are 5 questions by default. After each session, students see a summary showing questions attempted, correct rate, and how their skill score changed. They can immediately start another session or switch subjects.

3.3 Skill Score

The Skill Score is a student-friendly representation of their theta value, normalized to a 0-100 scale. It provides a single, easy-to-understand number that summarizes how a student is performing in each subject.

74 SKILL SCORE 0 100

3.4 Topic Mastery Map

Students can drill into each subject to see their mastery status across every topic. The mastery map provides a visual overview of where they stand and where they need to focus.

StatusIndicatorMeaningExample Topics
Mastered P(mastery) ≥ 0.85 Student has demonstrated reliable command of this topic Fractions, Decimals, Basic Algebra
Developing 0.50 ≤ P(mastery) < 0.85 Making progress but needs more practice for consistency Quadratic Equations, Geometry
Needs Work 0.20 ≤ P(mastery) < 0.50 Significant gaps identified, focused practice recommended Trigonometry, Statistics
Not Started No attempts yet Topic has not been practiced Probability, Mensuration

3.5 Spaced Repetition Schedule

Once a student masters a topic, the spaced repetition system schedules periodic reviews at increasing intervals to ensure long-term retention. This is based on the SM-2 algorithm, the same science behind Anki and other memory systems.

D0
Learn
D1
1 day
D7
7 days
D21
21 days
D60
60 days
D180
180 days

3.6 Practice Regularity

A heatmap tracks daily practice consistency, similar to GitHub's contribution graph. Each square represents one day, and the color intensity shows how many questions were completed that day. Consistency is rewarded with streak tracking.

W1
W2
W3
W4

Darker squares = more questions practiced. Gray squares = no practice that day. Students and parents can see monthly and yearly views.

3.7 Free vs Premium

FeatureFree Trial (7 days)FreePremium
Adaptive practice✓ All subjects✓ All subjects✓ All subjects
Questions per dayUnlimited5 per subjectUnlimited
AI Hints✓ Unlimited✓ Unlimited
Skill Score
Topic Mastery Map
Spaced Repetition
Parent Dashboard✓ Basic✓ Full
Teacher Dashboard
Practice Heatmap
Detailed Analytics
PriceFree for 7 daysFree foreverRs 299/month

For Parents

Complete visibility into your child's learning journey, updated in real time.

4.1 Linking to Your Child

Parents connect to their child's account using a unique linking code generated by the student. The process is simple and privacy-respecting, the parent never needs the student's password.

  1. Student opens their profile and taps "Generate Parent Code"
  2. A 8-character code is generated, valid for 24 hours
  3. Student shares the code with parent (verbally, text, etc.)
  4. Parent creates their account and enters the code
  5. Accounts are linked, parent sees real-time data
ARYN2026

Sample parent linking code (expires in 24 hours)

4.2 What Parents Can See

📈

Skill Score

See your child's current skill score across all subjects, with trend arrows showing improvement or decline over the past week.

🗺

Topic Mastery Map

Visual breakdown of mastered, developing, and weak topics in each subject. Identify exactly where your child needs help.

📅

Practice Heatmap

See which days your child practiced and how much. Track consistency patterns and identify when engagement drops.

📊

Year-over-Year Comparison

Compare performance across academic years. See how your child has grown since they started using Acadevo.

Daily Progress

Real-time view of today's practice: subjects attempted, questions answered, accuracy rate, and time spent.

👪

Multiple Children

Link multiple children under one parent account. Switch between children seamlessly to monitor each one individually.

4.3 Academic Year Timeline

Acadevo preserves learning history across academic years, so parents can see the full arc of their child's educational growth.

🎓

2026-27 (Current)

Class 8 — Active since April 2026. Skill Score: 74. 1,240 questions completed.

🎓

2025-26

Class 7 — Completed. Final Skill Score: 68. 4,890 questions completed. 47 topics mastered.

🎓

2024-25

Class 6 — Completed. Final Skill Score: 55. 2,340 questions completed. 28 topics mastered.

4.4 Institution Visibility

If the student's school uses Acadevo, parents can see which class their child is enrolled in and who their teacher is. However, parents cannot see other students' data or class-wide analytics, maintaining privacy for all families. The teacher controls what aggregate insights are shared with parents via the institution settings.

For Teachers

Powerful tools to monitor, understand, and support every student in your class.

5.1 Setting Up a Class

Teachers can create classes in under a minute. Students join using a simple invite code.

1. Create
Account
2. Create
Class
3. Share
Invite Code
4. Students
Join
5. View
Dashboard
MTH8A2

Sample class invite code (Math, Class 8, Section A)

5.2 Class Dashboard

The class dashboard gives teachers a bird's-eye view of every student's performance, with the ability to drill into individual detail.

StudentSkill ScoreLevelMasteredDevelopingNeeds WorkLast Active
Aryan Sharma 82 Advanced 1462 Today
Priya Patel 74 Proficient 1093 Today
Rahul Gupta 58 Developing 589 Yesterday
Sneha Reddy 41 Foundational 2515 3 days ago

Skill Distribution

Visual breakdown of where your class stands:

Found.
Dev.
Prof.
Adv.
Expert

1 Foundational, 1 Developing, 1 Proficient, 1 Advanced, 0 Expert

Class average: 63.8 (Proficient)

5.3 Student Detail View

Clicking on any student opens a detailed view showing their complete learning profile: skill score trend over time, topic-by-topic mastery breakdown, practice frequency, spaced repetition adherence, and AI hint usage patterns. Teachers can use this to plan targeted interventions, identify students who need extra support, and recognize high performers.

5.4 Multiple Classes

Teachers can create and manage multiple classes simultaneously, one for each subject-section combination they teach. Each class has its own invite code, student roster, and analytics. Switching between classes is instant from the teacher dashboard, and aggregate views can show performance across all classes at a glance.

5.5 Institution Management

School administrators can create an institutional account that links all teachers and classes under one umbrella. This enables school-wide analytics including aggregate skill score distributions across grades, subject-wise performance comparisons, teacher engagement metrics, and identification of at-risk students. Administrators can also manage teacher access, set default configurations, and export compliance reports.

Powered by Claude AI

AI-Powered Explanations

When students get stuck, they don't just see the right answer. They get a personalized, step-by-step explanation generated by Claude AI that teaches them how to think through the problem.

Step 1: Student Gets Stuck

After answering a question wrong (or tapping "Need a hint"), the student can request an AI explanation. The system captures the question, the student's wrong answer, and their current skill level.

Step 2: AI Generates Explanation

Claude receives the question context, the student's ability level, and pedagogical guidelines. It generates an explanation at the right level of complexity for that specific student.

Step 3: Student Learns

The explanation is displayed with clear formatting, step-by-step reasoning, and a final summary. The student can then re-attempt a similar question to reinforce the concept.

Real Example

Question: A train travels from City A to City B at 60 km/h and the distance is 960 km. How long does the journey take?

Student's answer: 960 km/h (confused distance with speed)

AI Hint:

I see you wrote 960 km/h as the answer. Let's think about what we know and what we need to find.

Given: Distance = 960 km, Speed = 60 km/h

Find: Time = ?

Remember the formula: Time = Distance / Speed

So: Time = 960 km / 60 km/h = 16 hours

Tip: Always check your units! The question asks for time (hours), not speed (km/h). Distance is what was given (960 km), not the answer.

Caching System

To keep costs low and response times fast, Acadevo uses an intelligent caching system for AI hints.

Student requests hint
Check cache
Found: Serve cached hint
Not found + Free: Upgrade prompt
Not found + Premium
Claude API call
Store + Serve

Claude Integration: Acadevo uses Anthropic's Claude API for hint generation. Each hint request includes the question text, answer options, correct answer, student's response, and the student's ability level. Claude is instructed to generate age-appropriate, curriculum-aligned explanations that teach reasoning rather than just providing the answer. Responses are cached by question ID for reuse across students.

Remember What You Learn

Without review, students forget up to 80% of what they learn within a month. Acadevo's spaced repetition system fights the forgetting curve by scheduling intelligent reviews at precisely the right time.

The Forgetting Curve

100% 75% 50% 25% 0% Day 0 Day 1 Day 7 Day 21 Day 60 Day 180 Without review With spaced review

SM-2 Algorithm

Acadevo uses a modified SM-2 algorithm (the same core algorithm used by Anki) to determine optimal review intervals. The algorithm adjusts intervals based on how well the student performs during each review. Correct answers increase the interval; incorrect answers reset it to a shorter duration.

ReviewIf CorrectIf WrongNote
1st correct review1 day3 days (retry)Immediate consolidation
2nd correct review6 days3 days (retry)Short-term retention check
3rd correct review15 days3 days (retry)Medium-term retention
4th correct review38 days3 days (retry)Long-term retention building
5th correct review94 days3 days (retry)Deep long-term memory

How Students Experience It

Spaced repetition is woven seamlessly into the daily practice flow. When a student opens a subject, the engine checks if any mastered topics are due for review. If so, 1-2 review questions are mixed into the regular practice session. Students see a small "Review" badge on these questions so they know it's a retention check rather than new learning. This means students don't need to do anything special; the system handles the scheduling automatically.

Analytics & Insights

Acadevo provides layered analytics for every stakeholder: administrators see platform health, teachers see class performance, and parents see individual progress.

Admin Analytics

Platform administrators have access to a comprehensive analytics dashboard covering:

Conversion Funnel

Registered
100%
Profile Done
87%
1st Session
78%
Day 7 Active
52%
Day 20 Active
31%
Upgraded
11%

Teacher Class Analytics

Beyond the class dashboard table, teachers get detailed analytics including: class-wide skill score distribution over time, topic-level heatmaps showing which topics the class struggles with most, engagement metrics (active vs. inactive students, average practice frequency), and exportable reports for parent-teacher meetings. Teachers can identify intervention targets, such as a topic where more than 40% of the class scores below "Developing," or a student whose engagement has dropped in the last two weeks.

Content Health Monitoring

The platform continuously monitors question bank health through automated statistical checks. Questions with abnormal discrimination parameters (a < 0.3, indicating the question doesn't differentiate well between ability levels), extreme difficulty values (|b| > 3.0), or high guessing parameters (c > 0.4) are flagged for human review. The system also tracks exposure rates to ensure no single question is overused, and identifies topics where the question bank may need expansion based on student attempt patterns.

Product Roadmap

Where we are, where we're going.

Live Shipped and available In Development Currently being built Planned On the roadmap
✓ Live

Q2 2026 — Foundation Launch

12 features shipped:

  • Adaptive practice engine (3PL IRT)
  • Student dashboard with skill scores
  • Topic mastery map with BKT
  • Daily practice targets (5 subjects)
  • Parent dashboard with linking
  • Teacher dashboard with class analytics
  • AI-powered hints (Claude integration)
  • Hint caching system
  • Spaced repetition (SM-2)
  • Practice heatmap
  • Razorpay payment integration
  • 30,240+ calibrated question bank
🔄 In Development

Q3 2026 — Engagement & Growth

6 features in development:

  • ICSE board curriculum mapping
  • Gamification layer (badges, streaks, leaderboards)
  • Peer comparison (anonymized percentile)
  • Offline mode for low-connectivity areas
  • WhatsApp parent notifications
  • Expanded question bank (+17,000 items)
📋 Planned

Q4 2026 — Depth & Intelligence

5 features planned:

  • AI-generated practice tests (chapter-wise, full-length)
  • Prerequisite skill graphs (automatic remediation)
  • Voice-based hints in Hindi/English
  • School admin dashboard with multi-class views
  • API for third-party LMS integration
📋 Planned

2027 — Scale & Expansion

6 features planned:

  • Classes 1-5 curriculum (primary school)
  • Regional language support (Tamil, Telugu, Kannada, Marathi)
  • Competitive exam prep (NTSE, Olympiads)
  • AI tutor (conversational learning mode)
  • Parent mobile app (native iOS/Android)
  • International curriculum support (Cambridge, IB)

Technical Specifications

The technology stack and standards that power Acadevo.

Architecture

  • React 18 (frontend SPA)
  • Node.js + Express (backend API)
  • Cloud Firestore (primary database)
  • Firebase Authentication (auth provider)
  • Claude API by Anthropic (AI hints)
  • Razorpay (payment processing)
  • Region: asia-south1 (Mumbai)

Adaptive Engine

  • 3-Parameter Logistic IRT (3PL)
  • Bayesian Knowledge Tracing (BKT)
  • SM-2 Spaced Repetition Algorithm
  • Fisher Information item selection
  • Maximum Likelihood Estimation (MLE)
  • Exposure control via Sympson-Hetter
  • Real-time theta updates per response

Data & Privacy

  • All data stored in India (asia-south1)
  • TLS 1.3 encryption in transit
  • AES-256 encryption at rest
  • No third-party data sharing
  • GDPR-aligned data practices
  • Parent consent required for minors
  • Data export available on request

Availability & Performance

  • 99.95% uptime SLA
  • Global CDN (Firebase Hosting)
  • Average API response: <200ms
  • Question selection: <50ms
  • AI hint generation: <3s (uncached)
  • AI hint cached: <100ms
  • Auto-scaling backend infrastructure