Conversational AI for Technical Interview Practice

A web-based platform that uses conversational AI to help Computer Science students practice the think-aloud process during technical interviews. This system was developed as part of the research presented in the paper "Designing Conversational AI to Support Think-Aloud Practice in Technical Interview Preparation for CS Students" published at IEEE VL/HCC 2025.

• Paper: arXiv:2507.14418
• Conference: IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) 2025

🎯 Overview

Technical interviews are crucial for CS students, but the think-aloud process—where candidates verbalize their thought processes while solving coding problems—remains challenging to practice. This platform addresses this gap by providing an LLM-based conversational AI system that offers:

• Techincal Interview Simulation: AI-facilitated mock interview tool that simulates a technical interview experience through voice-based natural conversation
• AI Feedback on Think-Aloud Practice: Providing feedback on users’ think-aloud performance based on the interview simulation (A) transcript
• AI-Generated Think-Aloud Example Dialogue: Providing (A) AI-generated dialogues that model thinking aloud during a technical interview for each coding problem. The goal is to help users learn from examples relevant to their current task and better articulate their thought processes

🛠️ Technology Stack

Backend

• Python Flask - Web framework with async support
• OpenAI API - Large Language Model integration
• MongoDB - Database for storing sessions and user data

Frontend

• Vue.js 3 - Progressive JavaScript framework
• TypeScript - Type-safe JavaScript development
• CodeMirror 6 - Advanced code editor with syntax highlighting
• Bootstrap 5 - Responsive UI framework
• Axios - HTTP client for API requests

📋 Prerequisites

• Python 3.8+
• Node.js 18+
• MongoDB (local or cloud instance)
• OpenAI API Key

🔧 Installation & Setup

1. Clone the Repository

git clone https://github.com/your-username/coding_interview_practice_platform.git
cd coding_interview_practice_platform

2. Backend Setup

cd backend

# Install Python dependencies
pip install -r requirements.txt

# Set up environment variables
cp .env.example .env
# Edit .env file with your API keys and database URLs

3. Frontend Setup

cd frontend

# Install Node.js dependencies
npm install

# Set up environment variables
cp .env.example .env
# Edit .env file with your backend API URL

4. Environment Configuration

Create a .env file in the backend directory:

OPENAI_API_KEY=your_openai_api_key
MONGODB_URI=your_mongodb_connection_string
FIREBASE_CREDENTIALS_PATH=path_to_firebase_credentials.json
JWT_SECRET_KEY=your_jwt_secret_key
FLASK_ENV=development

🚀 Running the Application

Development Mode

1. Start the Backend Server:

   cd backend
   flask --app src/app run
   # Server runs on http://127.0.0.1:5000

2. Start the Frontend Development Server:

   cd frontend
   npm run dev
   # Application runs on http://localhost:5173

Production Build

1. Build the Frontend:

   cd frontend
   npm run build

2. Deploy Backend:

   cd backend
   # Use the provided deploy.sh script or deploy manually
   gunicorn --bind 0.0.0.0:5000 src.app:app

📁 Project Structure

coding_interview_practice_platform/
├── backend/                    # Flask backend application
│   ├── src/
│   │   ├── app.py             # Main Flask application
│   │   └── routes/            # API route implementations
│   ├── requirements.txt       # Python dependencies
│   ├── Dockerfile            # Docker configuration
│   └── deploy.sh             # Deployment script
├── frontend/                  # Vue.js frontend application
│   ├── src/
│   │   ├── App.vue           # Main Vue application
│   │   └── components/       # Vue components
│   ├── package.json          # Node.js dependencies
│   └── vite.config.ts        # Vite build configuration
└── public/                   # Static assets and documentation images
    ├── 1_interview simulation.png
    ├── 2_feedback.png
    └── 3_example.png

📝 Citation

If you use this platform in your research or find it helpful, please cite our paper:

@inproceedings{daryanto2025designing,
  title={Designing Conversational AI to Support Think-Aloud Practice in Technical Interview Preparation for CS Students},
  author={Daryanto, Taufiq and Stil, Sophia and Ding, Xiaohan and Manesh, Daniel and Lee, Sang Won and Lee, Tim and Lunn, Stephanie and Rodriguez, Sarah and Brown, Chris and Rho, Eugenia},
  booktitle={2025 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)},
  year={2025},
  organization={IEEE}
}

📞 Contact

For questions about this research or the platform, please contact:

• Taufiq Daryanto - Email

🔗 Links

• Paper: arXiv:2507.14418
• Conference: IEEE VL/HCC 2025

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