Degree

Bachelor of Science (Computer Science)

Department

Department of Computer Science

School

School of Mathematics and Computer Science (SMCS)

Advisor

Jawwad Farid, Professor of Practice, Department of Computer Science

Keywords

Game-based assessment, Recruitment, Soft skills, MBTI, Personality traits, Scenarios

Abstract

The primary objective of our project is to develop a game-based recruitment system that modernizes traditional personality assessments by making them more engaging, adaptive, and relevant by incorporating real scenarios. We began by examining established models such as the Myers-Briggs Type Indicator (MBTI) and the Big Five personality traits. While these tools provide meaningful psychological insights, their formats are too lengthy, and repetitive. To address this, we selected approximately 20 questions most relevant to workplace behavior and hiring decisions and imitated the scoring process of the MBTI questionnaires. This not only shortens the assessment process but also improves candidate engagement. To ensure that our scenarios accurately measure key soft skills, we incorporated a variety of different frameworks relating to different soft skills such as Leadership and Emotional Intelligence. These frameworks guided the creation of adaptive dialogue-based scenarios that assess not only soft skills but provide an interactive, game-like experience for the candidate. These scenarios also encapsulate many workplace challenges and assess how the candidate would react.

Tools and Technologies Used

Frontend: React.js, Tailwind CSS, shadcn/ui, React Router, JavaScript

Backend: Node.js, Express.js, REST APIs, JavaScript

Game Engine: Unity (WebGL module integration), C#

Database: MongoDB Atlas (cloud-hosted)

Authentication: JWT

Tools & Platforms: Git/GitHub, Visual Studio, Axios, Lucide Icons

Methodology

The team employed the agile SCRUM methodology using Jira to manage iterative sprints, continuous feedback, and milestone-based feature releases. Development began with thorough requirement gathering and system architecture planning. The backend was developed as a modular API service, with the frontend built in React and integrated with a Unity-powered game engine. Each sprint cycle included functional and usability testing, ensuring a robust and user-friendly interface throughout development. Scenario-based question logic was embedded into the gameplay to derive personality scores with high accuracy.

Document Type

Open Access

Submission Type

BSCS Final Year Project

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