📊 Zeba Academy Study Analytics #

A powerful study behavior analytics engine for Flutter applications that helps analyze student learning patterns, detect weak topics, predict performance, and generate exportable reports.

🚀 Overview #

zeba_academy_study_analytics provides an easy‑to‑integrate analytics layer for education apps. It transforms raw study session data into meaningful insights that help students and educators improve learning outcomes.

This package is designed using clean architecture principles and is optimized for production Flutter applications.

✨ Features #

• ✅ Weak topic detection
• 📈 Study pattern insights
• 🔮 Performance prediction
• 📄 Exportable analytics reports (JSON & CSV)
• ⚡ Lightweight and fast analytics engine
• 🧩 Easy integration into existing Flutter apps

📦 Installation #

Add the dependency in your pubspec.yaml:

dependencies:
  zeba_academy_study_analytics: ^1.0.0

Then run:

flutter pub get

🧠 Core Concepts #

Study Session #

Represents a single study activity including topic, duration, and performance score.

Analytics Engine #

Processes multiple study sessions and generates insights.

Analytics Report #

Contains:

• Weak topics
• Study insights
• Predicted performance score

🛠 Usage #

1️⃣ Import Package #

import 'package:zeba_academy_study_analytics/zeba_academy_study_analytics.dart';

2️⃣ Create Study Sessions #

final sessions = [
  StudySession(
    topic: "Math",
    date: DateTime.now(),
    durationMinutes: 60,
    score: 45,
  ),
  StudySession(
    topic: "Science",
    date: DateTime.now(),
    durationMinutes: 90,
    score: 80,
  ),
];

3️⃣ Generate Analytics Report #

final engine = StudyAnalyticsEngine();

final report = engine.generateReport(sessions);

print(report.weakTopics);
print(report.predictedScore);

4️⃣ Export Reports #

Export JSON

final jsonReport = ReportExporter.exportToJson(report);

Export CSV

final csvReport = ReportExporter.exportToCsv(report);

📊 Example Output #

{
  "weakTopics": ["Math"],
  "predictedScore": 78.5
}

🏗 Architecture #

lib/
 ├── models
 ├── engine
 ├── export
 └── utils

The modular structure allows easy extension and testing.

🧪 Testing #

Run tests using:

flutter test

🔧 Supported Platforms #

• ✅ Android
• ✅ iOS
• ✅ Web
• ✅ Windows
• ✅ macOS
• ✅ Linux

📚 Use Cases #

• Student learning apps
• Coaching institute dashboards
• LMS analytics systems
• Study tracking applications
• Educational AI assistants

🛣 Roadmap #

• 📊 Visualization dashboards
• 🤖 Advanced ML prediction models
• 📄 PDF report export
• ☁️ Cloud analytics integration
• 📅 Weekly improvement tracking

🤝 Contributing #

Contributions are welcome!

1. Fork the repository
2. Create a feature branch
3. Commit changes
4. Open a pull request

📄 License #

This project is licensed under the GPL License.

👨‍💻 Author #

Zeba Academy

⭐ Support #

If you find this package useful, consider giving it a star on GitHub and sharing it with the Flutter community.