AI-Powered Educational Technology Development

Project Overview

As Lead Backend Developer for BeNakama, a London-based EdTech startup, I have been developing advanced classroom systems and educational technology serving UK high schools since February 2025. Additionally, I led the development of Aluminotes, an AI-leveraging note-taking app that won 1st place in the Inn-eaux-vate pitch competition.

Current Work: BeNakama Educational Platform

Technical Implementation

• AI Student Question System: Developing AI-powered student question matching for best-fit academic ability assessment
• Secure Classroom Systems: Leading backend architecture for “Ascend” gamified learning tool
• International Development: Managing remote development from Louisiana for UK deployment
• Accessibility Focus: Empowering students with learning difficulties through intelligent technology

Design Philosophy

The development prioritizes genuine learning over compliance metrics, directly opposing the failures of systems like Edgenuity that make learning unnecessarily difficult. Every design decision centers students with learning difficulties as primary users, creating universally beneficial solutions.

Aluminotes: Award-Winning Accessibility Application

Project Leadership

• Tech Lead Role: Led 3-person development team creating AI-leveraging note-taking app for students with disabilities
• Technical Stack: Django, HTML, JavaScript, Python for accessibility-focused educational technology
• Competitive Success: Won 1st place in Inn-eaux-vate pitch competition
• Mission Impact: Reformatting and rewording text to assist students with disabilities

Development Insights

Overcame initial code conflicts through intensive communication protocols that became highly efficient. The experience demonstrated how technical challenges are often secondary to coordination and team dynamics in successful project delivery.

Skills Developed

Through these projects, I have gained experience in:

• Full-Stack Development: React, Mantine UI, Django backend architecture for educational systems
• AI Integration: Implementing AI-powered student question systems and accessibility features
• International Collaboration: Managing technical development across time zones and cultural contexts
• Mission-Driven Development: Balancing technical excellence with social impact objectives
• Team Leadership: Leading technical teams while maintaining focus on accessibility and educational outcomes

Personal Motivation

Having experienced educational inequality from both sides - under-resourced Louisiana classrooms where Edgenuity represented “future of education,” to cutting-edge London EdTech development - I understand how technology can either bridge or widen educational disparities. This drives my commitment to creating technology that serves learners rather than administrators.

Future Research Applications

This professional experience has informed my interest in pursuing graduate research in computational learning systems, particularly exploring how AI can amplify human teaching capabilities while avoiding the compliance-focused design that characterizes failed educational technology.

4. Cross-Cultural Implementation: How do accessibility needs vary across different educational contexts (UK vs. US vs. international)?

Technical Methodology

AI System Architecture

• Backend: Secure classroom systems with international deployment capability
• Frontend: React, Mantine UI for accessible interface design
• AI Components: Custom algorithms for cognitive load detection and content adaptation
• Accessibility Framework: WCAG 2.1 AA+ compliance with enhanced cognitive accessibility features

Research Validation

• Real-world Testing: Active deployment in UK high school environments
• Competitive Validation: 1st place pitch competition win
• International Scale: Remote leadership of international development team
• Iterative Development: Continuous feedback from students with learning difficulties

Philosophical Approach

Anti-Compliance Mindset: Rejecting systems that prioritize administrative convenience over genuine learning support. Every design decision tested against “does this genuinely help students with learning difficulties?”

Accessibility as Innovation: Treating accessibility not as an afterthought but as the primary design driver that leads to breakthrough innovations in educational technology.

Future Directions

1. Scalability Research: How to maintain personalized accessibility at scale across diverse educational contexts
2. Cognitive Science Integration: Incorporating latest research in learning differences and cognitive processing
3. Teacher Training Systems: Developing AI tools that help teachers understand and support diverse cognitive needs
4. Policy Impact: Translating research insights into educational technology policy recommendations

This research represents the intersection of rigorous AI research with real-world implementation, ensuring that advances in educational accessibility translate into measurable improvements for the students who need them most.