Project: [Creative app (AI-Assisted Development via github copilot)] - [Wajiha Imran]

[jk0409603-sys]

Track

Creative Apps (GitHub Copilot)

Project Name

Adaptive IT learning Hub : AI powered Quiz & Tutoring System ( with Azure OpenAI Tutor)

GitHub Username

jk0409603-sys

Repository URL

https://github.com/jk0409603-sys/Online-Quiz-System.git

Project Description

Adaptive IT Learning Hub is an AI-powered learning platform designed to solve a real problem facing millions of IT students in Pakistan — lack of access to personalised exam preparation.

The platform uses Azure OpenAI (gpt-4o-mini) to generate adaptive study recommendations tailored to each student, and Azure AI Language to detect weak topics from student answers in real time. Students can attempt quizzes across 4 subjects (Python, Programming Basics, Mathematics, Data Structures) with 3 difficulty levels and 10 questions each — 120 questions total.

Key features:

• AI-generated personalised study insights via Azure OpenAI
• Weak topic detection via Azure AI Language Key Phrases API
• Full Urdu/English bilingual UI for inclusion
• Teacher analytics dashboard showing sessions and weak topic trends
• Live deployed and accessible from any device

Built solo in 4 days by a 1st year BS IT student from Bahauddin Zakariya University, Pakistan.

Demo Video or Screenshots

bandicam.2026-06-14.11-34-23-339.mp4

Primary Programming Language

Other

Key Technologies Used

Core Technologies
Primary Language: C++ , python and other language e.g HTML
Database Management: SQL (Structured Query Language)
Architecture: Object-Oriented Programming (OOP)

AI & Copilot Integration
Development Assistant: GitHub Copilot (Used for code drafting, SQL optimization, and structural debugging)
Cloud AI Service: Azure OpenAI Service (Powering the conversational engine)
Core Feature: Natural Language Processing / "Talk to AI" Interactive Tutor

Submission Type

Individual

Team Members

-Indivisual
-Name : Wajiha Imran

Submission Requirements

• My project meets the track-specific challenge requirements
• My repository includes a comprehensive README.md with setup instructions
• My code does not contain hardcoded API keys or secrets
• I have included demo materials (video or screenshots)
• My project is my own work with proper attribution for any third-party code
• I agree to the Code of Conduct
• I have read and agree to the Disclaimer
• My submission does NOT contain any confidential, proprietary, or sensitive information
• I confirm I have the rights to submit this content and grant the necessary licenses

Quick Setup Summary

1. Live Demo: Access the deployed web application instantly on Render here: [https://online-quiz-system-jr8q.onrender.com/]
2. Clone the repo: git clone https://github.com/jk0409603-sys/Online-Quiz-System.git
3. Set up database: Import the SQL schema file into your local SQL server environment.
4. Configure environment variables: Set your local environment system variables for AZURE_OPENAI_KEY and AZURE_OPENAI_ENDPOINT to power the AI tutor feature.
5. Live Web App: Access the live, functioning Adaptive IT Learning Hub hosted on Render here: [https://online-quiz-system-jr8q.onrender.com/]
6. Source Code: Review the underlying C++, SQL schema, and architecture implementation directly in the public repository link provided below.
   link:[https://github.com/jk0409603-sys/Online-Quiz-System.git]
7. AI Capabilities: The "Talk to AI" tutoring feature is pre-configured within the cloud deployment using the Azure OpenAI Service.

Technical Highlights

1.Cloud Deployment via Render: Successfully migrated and hosted the application's interface live on Render, ensuring the system is fully accessible via the web without requiring complex local C++ compilation or manual database setups for the end user.
2.Robust Backend Logic: Built using C++ and an structured SQL database to efficiently handle quiz management, student profiles, and session tracking.
3.Live Azure OpenAI Integration: Connected the deployed application to the Azure OpenAI Service, powering a live, interactive "Talk to AI" tutor that analyzes student mistakes and explains concepts in real time.
4. AI-Assisted Engineering: Utilized GitHub Copilot throughout the development lifecycle to streamline writing the core logic, optimize SQL queries, and accelerate the cloud deployment configuration.

Challenges & Learnings

🚀 Challenges Overcome
1.Local to Cloud Migration: Moving a C++ and SQL-backed system into a live web environment on Render presented structural challenges. I had to rethink how the application handles environments, data flows, and web access compared to a standard local console app.
2. Managing Cloud API Integrations: Connecting the application securely to the Azure OpenAI Service without exposing sensitive environment variables or API keys on GitHub required careful configuration and learning how to implement a proper web backend workflow.
3. Database Management in Production: Ensuring the SQL schema deployed correctly and maintained data persistence while connecting seamlessly with our logic layer in a live, hosted setting.

💡 Key Learnings

1. Cloud Infrastructure & Deployment: Gained hands-on, practical experience hosting applications on Render and managing live web deployments.
2. AI-Assisted Development: Learned how to effectively use GitHub Copilot as a programming collaborator to draft object-oriented structures, accelerate boilerplate writing, and optimize complex database queries.
3. Production-Level Security: Mastered the vital industry practice of removing hardcoded secrets from source files, shifting instead to using secure environment variables for cloud engines like Azure OpenAI.

Contact Information

jk0409603@gmail.com

Country/Region

Pakistan/Punjab

[jk0409603-sys]

🌐 Live Deployment & Access
The project is fully deployed and optimized to run in a cloud environment. There is no need for local configuration or compilation to evaluate the application.

Live Web App: Access the live, functioning Adaptive IT Learning Hub hosted on Render here: [PASTE_YOUR_RENDER_LINK_HERE]
Source Code: Review the underlying C++, SQL schema, and architecture implementation directly in the public repository link: https://github.com/jk0409603-sys/Online-Quiz-System.git
AI Capabilities: The "Talk to AI" tutoring feature is pre-configured within the cloud deployment using the Azure OpenAI Service.
🛠️ Technical Highlights
Cloud Deployment via Render: Successfully migrated and hosted the application's interface live on Render, ensuring the system is fully accessible via the web without requiring complex local C++ compilation.
Robust Backend Logic: Built using C++ and a structured SQL database to efficiently handle quiz management, student profiles, and session tracking.
Live Azure OpenAI Integration: Connected the deployed application to the Azure OpenAI Service, powering a live, interactive "Talk to AI" tutor that analyzes student mistakes and explains concepts in real time.
AI-Assisted Engineering: Utilized GitHub Copilot throughout the development lifecycle to streamline writing the core logic, optimize SQL queries, and accelerate the cloud deployment configuration.

🚀 Challenges & Learnings
Local to Cloud Migration: Moving a C++ and SQL-backed system into a live web environment on Render presented structural challenges. I had to rethink how the application handles environments, data flows, and web access compared to a standard local console app.
Managing Cloud API Integrations: Connecting the application securely to the Azure OpenAI Service without exposing sensitive environment variables or API keys on GitHub required careful configuration.
Key Learnings: Gained hands-on experience hosting applications on Render, effectively using GitHub Copilot as a programming collaborator, and mastering production-level security by shifting to secure environment variables.