SYNAPSE: A Multi-LLM Orchestrated AI Tutor for Secure Software Development Education with Neurodivergent-First Design
This work addresses the lack of accessible, practical training for secure software development, particularly for neurodivergent learners, but the pilot is small and preliminary.
SYNAPSE is an adaptive tutoring platform for secure software development that coordinates multiple LLMs and includes neurodivergent-first design. In a pilot with 19 participants, it achieved a System Usability Scale score of 76.4 and engagement of 4.2/5, with comparable cognitive load across neurodivergent and neurotypical cohorts.
Developers who maintain real systems must continually recognise and remediate vulnerabilities in existing code, yet this skill is rarely trained directly: secure software development is commonly taught only after programming fluency is acquired, and accessibility support is treated as a secondary concern, disadvantaging learners with ADHD and related executive-function differences. This paper presents SYNAPSE, a publicly deployed adaptive tutoring platform for Java, Python for cybersecurity, and secure software development. SYNAPSE coordinates Claude, GPT-4o, and Gemini through the Model Context Protocol, routing interactions by pedagogical intent under a three-stage Socratic hint policy. It exposes eighteen always-visible accessibility features and anchors practice in ShopSecure, a deliberately vulnerable web application mapped to six OWASP Top 10 (2021) categories, on which learners practise the detect-understand-remediate loop characteristic of software maintenance. A feasibility pilot with nineteen participants across neurodivergent and neurotypical cohorts returned a System Usability Scale score of 76.4 and engagement of 4.2/5, with comparable cognitive-load levels across cohorts. SYNAPSE is available at https://synapse-course.com; a screencast is available at https://youtu.be/9R17KC47qQI.