Tackling Exam Malpractice with Technology: The RedCard Story

preciousanyi

Precious Ifeanyi

Posted on July 24, 2024

Tackling Exam Malpractice with Technology: The RedCard Story

Examination question paper

Imagine a world where maintaining exam fairness is as simple as a tap on your screen. Welcome to the Red Card App – a revolutionary application crafted for students and faculty in tertiary institutions. Our mission is straightforward: to combat examination malpractice and cultivate a culture of academic integrity through a transparent, point-based system.

Meet the Team:

  • Precious Anyi (Project Lead): I spearheaded the backend development, focused on API design, and ensured the authentication was secure and reliable.

Project Timeline:

  • Planning Phase: 2 weeks of brainstorming and sketching out models and API routes.
  • Development Phase: 2 weeks of intense coding and troubleshooting.
  • Testing and Deployment: 1 week to refine, document and host the API.

Who’s It For?: The Red Card App is crafted for students and faculty who are committed to maintaining academic honesty and reducing examination malpractice. It’s a tool for those who believe in fair play and accountability in education.

My Role and Focus: My primary focus was on the backend of the application. From designing robust models to setting up API routes and implementing secure authentication and authorization mechanisms, I aimed to ensure the system was both powerful and user-friendly.

What We’ve Accomplished

The Red Card App integrates a comprehensive point-based system that assigns values to different offences committed during an examination. This ensures transparency and accountability, making it easier to identify and deter malpractice.

Technologies I Used:

  • Backend: Django and Django Rest Framework (DRF) for a robust and scalable system.
  • Authentication: JWT (JSON Web Tokens) for secure access.
  • API Documentation: Swagger for clear and accessible API docs.

Key Features

  1. Point Allocation System: Assigns points to different exam offenses based on severity.
  2. Automatic Referral: Automatically refers students to the exam committee once they reach a predetermined threshold.
  3. Transparency and Accountability: Provides clear information about the point system and its consequences.

Most Challenging Technical Hurdle

One of the biggest challenges was designing the models. Initially, I was unsure about which fields to include and how they should relate to each other. This confusion led to several iterations and feedback sessions with the team, which eventually helped us nail down the right structure.

Setting up the API routes and determining the correct HTTP methods for RESTful operations was another challenge. Implementing secure authentication and authorization mechanisms also required a lot of attention and fine-tuning.

Lessons Learned

Technical Takeaways: Iterative design and constant feedback are crucial for developing a robust model. Authentication and authorization must be meticulously planned and implemented.

What I Might Do Differently: Spend more time in the planning phase to thoroughly map out the models and their relationships, saving time and reducing rework during development.

Personal Growth: This project strengthened my problem-solving skills. It also solidified my understanding of Django and DRF for backend development.

Future Implications: The lessons learned from this project will guide my approach to future projects, especially in backend development, API design, and security.

About Me

Hi, I’m Precious Ifeanyi, a passionate software engineering student at ALX dedicated to creating impactful technological solutions. My expertise lies in backend development, with a focus on building secure and scalable applications.

Project Links:

Feel free to explore our project, and let’s work together to promote academic integrity and fairness!

💖 💪 🙅 🚩
preciousanyi
Precious Ifeanyi

Posted on July 24, 2024

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