🎓 Zeba Academy Recommendation Engine #

An AI-driven adaptive learning recommendation engine for Flutter EdTech apps.

Built to power intelligent learning systems with:

• ✅ Weak Topic Detection
• ✅ Adaptive Difficulty Adjustment
• ✅ Personalized Learning Path
• ✅ Next Lesson Suggestion
• ✅ Performance-Based Recommendations
• 🏆 Mastery Tracking (Beginner → Expert)

Designed for quiz apps, exam simulators, LMS platforms, and competitive exam preparation systems.

🚀 Features #

📊 Weak Topic Detection #

Automatically identifies topics where student accuracy is below threshold.

🎯 Adaptive Difficulty Adjustment #

Adjusts difficulty level dynamically based on performance.

🧠 Personalized Learning Path #

Generates ordered learning path based on weakest topics first.

📚 Next Lesson Suggestion #

Recommends the most suitable next lesson.

💬 Performance-Based Feedback #

Generates actionable feedback messages.

🏆 Mastery Tracking System #

Classifies learners into:

• Beginner
• Intermediate
• Advanced
• Expert

📸 Preview #

[AI Dashboard]

📦 Installation #

Add to your pubspec.yaml:

dependencies:
  zeba_academy_recommendation_engine: ^1.0.0

Then run:

flutter pub get

🛠 Basic Usage #

1️⃣ Import #

import 'package:zeba_academy_recommendation_engine/zeba_academy_recommendation_engine.dart';

2️⃣ Create Student Performance #

final performance = StudentPerformance(
  studentId: "S1",
  topicStats: {
    "Algebra": TopicPerformance(
      topicName: "Algebra",
      totalQuestions: 20,
      correctAnswers: 10,
      incorrectAnswers: 10,
      averageTimeTaken: 35,
      currentDifficulty: 2,
    ),
  },
);

3️⃣ Detect Weak Topics #

final engine = RecommendationEngine();
final weakTopics = engine.detectWeakTopics(performance);

4️⃣ Suggest Next Lesson #

final lessons = [
  Lesson(
    lessonId: "L1",
    topic: "Algebra",
    difficulty: 1,
    title: "Algebra Basics",
  ),
];

final nextLesson =
    engine.suggestNextLesson(performance, lessons);

5️⃣ Mastery Tracking #

final masteryEngine = MasteryEngine();

final topic = performance.topicStats["Algebra"]!;
final masteryLevel =
    masteryEngine.getMasteryLevel(topic);

print(masteryLevel.label); // Beginner / Intermediate / Advanced / Expert

🏗 Architecture #

models/
  ├── student_performance.dart
  ├── topic_performance.dart
  ├── lesson.dart
  ├── mastery_level.dart

engine/
  ├── recommendation_engine.dart
  ├── mastery_engine.dart

📈 Mastery Scoring Logic #

Mastery score (0–100) is calculated using:

• 70% Accuracy Weight
• 30% Speed Efficiency Weight

This creates balanced performance intelligence.

🎯 Use Cases #

• Competitive Exam Apps
• CBT Simulation Platforms
• School Learning Apps
• Adaptive Practice Apps
• AI-powered LMS Systems
• Mock Test Platforms

🧪 Testing #

Run tests:

flutter test

🛣 Roadmap #

• 🔥 AI Score Prediction
• 📊 Learning Analytics Dashboard Widgets
• ☁ Firebase Analytics Integration
• 📈 Performance Trend Tracking
• 🏆 Student Ranking System

🤝 Contributing #

Contributions, issues and feature requests are welcome.

📄 License #

This package is part of the Zeba Academy Flutter SDK ecosystem.

👨‍💻 Author #

Zeba Academy Building professional Flutter packages for modern EdTech platforms.

🌐 https://zeba.academy/flutter/