Anik Nandi.
//Case study·Production

firefighter recruitment australia

Firefighter Recruitment Australia (FRA) is an AI-powered Learning Management System designed to help candidates prepare for the firefighter recruitment process in Australia.

Stack
13components
Shipped
10features
Frames
10captures
Status
SHIPPEDarchived
Firefighter Recruitment Australia
01.

overview.

Firefighter Recruitment Australia (FRA) is an AI-powered Learning Management System designed to help candidates prepare for the firefighter recruitment process in Australia. The platform provides structured learning through video lessons, practice exams, physical training guides, and assessment preparation materials.

I was responsible for the end-to-end development and operation of the application, including backend development, frontend implementation, API design, DevOps, deployment, and ongoing support.

The backend was built with Laravel, Filament PHP, Livewire, and MySQL, while the frontend was developed using Next.js, React.js, and Tailwind CSS. The platform enables users to enroll in courses, complete lessons and quizzes, track their performance, and create personalized learning roadmaps with individual goals.

A key feature is the AI-powered learning assistant, which provides instant explanations, exam-solving guidance, result analysis, mock interview feedback, and personalized recommendations to improve candidate performance.

The platform also includes preparation modules for aptitude tests, psychometric assessments, written application exams, mock interviews, note-taking exercises, group scenarios, incident briefings, and self-introduction training, creating a comprehensive training ecosystem for firefighter recruitment candidates.

02.

the problem.

  • 01Firefighter recruitment candidates needed a single platform to prepare for the various stages of the Australian firefighter selection process.
  • 02Learning resources, practice exams, interview preparation materials, and performance tracking were fragmented across multiple sources.
  • 03Candidates lacked personalized guidance and feedback while preparing for aptitude tests, psychometric assessments, mock interviews, and scenario-based evaluations.
  • 04Instructors required an efficient system to manage course content, monitor learner progress, and support a growing student base.
03.

approach.

  • 01Designed and developed a full-featured Learning Management System tailored specifically for firefighter recruitment preparation.
  • 02Built a scalable backend using Laravel, Filament PHP, Livewire, and MySQL, with a comprehensive administrative portal for content and user management.
  • 03Developed a responsive frontend using Next.js, React.js, and Tailwind CSS to provide a seamless learning experience across devices.
  • 04Implemented course enrollment, structured learning modules, interactive quizzes, performance analytics, and personalized learning roadmaps.
  • 05Integrated AI-powered assistance to provide real-time explanations, result analysis, interview feedback, and personalized improvement recommendations.
  • 06Managed the complete application lifecycle, including backend architecture, frontend development, API design, DevOps, deployment, and ongoing operational support.
04.

what shipped.

  • 01Complete firefighter recruitment preparation LMS platform.
  • 02Course enrollment and learning management system with video-based lessons and structured training modules.
  • 03Interactive quizzes and practice examinations.
  • 04Aptitude test and psychometric assessment preparation modules.
  • 05Mock interview practice with AI-powered feedback.
  • 06Incident briefing, note-taking, self-introduction, and group scenario training modules.
  • 07AI-powered learning assistant for question-solving guidance, result clarification, and personalized recommendations.
  • 08personalized study roadmap features.
  • 09Detailed student performance analytics and progress tracking.
  • 10Scalable platform supporting 35,000+ students.
05.

stack.

PHPLaravelFilament PHPLivewireMySQLJavaScriptNextReactTailwind CSSReverbGithub ActionsCI/CDAWS ECS, RDS, S3
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