Faculty Course Allocator
An intelligent web platform designed to streamline the complex process of assigning subjects to university faculty based on preferences and constraints.
The Challenge
The university's manual process for assigning subjects to faculty was time-consuming, prone to errors, and often resulted in suboptimal allocations. This traditional method struggled to effectively balance faculty preferences, departmental requirements, and course load, leading to administrative delays and reduced faculty satisfaction.
The Goal
The objective was to develop a centralized, role-based web application that automates subject allocation using a custom algorithm. The goal was to ensure a fair, efficient, and transparent process for both administrators and faculty members, saving significant administrative hours.
The Approach
Discovery & Planning
I started by meeting with department heads and faculty to understand the key criteria for subject assignment. I then mapped out the distinct workflows required for an Administrator role and a Faculty role.
Algorithm & System Design
I designed a core allocation algorithm based on a weighted scoring system. The database schema was structured to handle relationships between faculty, subjects, and preferences, and I created wireframes for the key interfaces.
Development & Technology
The backend i used was serverless firebase hosting and allocation algorithm. The front-end used React.js to provide secure, role-based interfaces for administrators and faculty.
Key Features
Role-Based Access Control
Separate, secure panels for Administrators (to oversee allocations) and Faculty (to submit preferences).
Preference Submission System
An intuitive interface for faculty to rank their preferred subjects for the upcoming semester.
Automated Allocation Algorithm
A core engine that processes preferences and constraints to generate an optimized allocation list.
Admin Dashboard & Override
A comprehensive dashboard for admins to trigger the algorithm, review suggestions, and make manual adjustments.
The Result
The final application provided a simple yet powerful solution to a significant administrative bottleneck. It reduced the allocation time from weeks to just a few hours, demonstrably increased faculty satisfaction, and provided a transparent, data-driven foundation for academic planning.
What I Learned
This project deepened my skills in both algorithm design and full-stack development. I learned how to translate complex real-world constraints into logical, executable code and reinforced the importance of designing user-centric interfaces tailored to different user roles.