Engineering Adaptation: A User Modelling Proof-of-Concept

The Vision: Beyond the Static Interface

Our User Modelling coursework taught us about adaptive systems. For this project, we were tasked to implement Adaptive Interfaces. This is a Proof-of-Concept (PoC) designed to investigate how software can perceive a user's cognitive load and modify its entire UI to prevent burnout.

The Core: The User Model

The heart of this application is a dynamic user model that categorizes users based on two primary dimensions to deliver a personalized experience:

• Experience Level: The system tracks interactions to distinguish between Beginners (who receive onboarding and simplified layouts) and Experienced users (who gain access to "Quick Add" features and high-density views).
• Cognitive Load State: By monitoring real-time metrics—specifically task volume and deadlines—the system determines if a user is in a state of LOW, HIGH, or PANIC cognitive load.

The Feature: Intelligent "Focus Mode"

The standout achievement of this PoC is the behavior-based Focus Mode (formerly Catch Up Mode). Rather than being a static toggle, it acts as an intelligent "digital intervention":

• Predictive Triggering: If the system detects a workload of 4 or more incomplete tasks or identifies overdue items (calculated from the start of the current day), it automatically proposes a low-cognitive-load view.
• Reducing Friction: Focus Mode strips away visual clutter and highlights a single "Next Step" to help the user regain momentum without feeling overwhelmed.

Technical Architecture & Implementation

To ensure the app felt production-grade despite being an academic PoC, I leveraged a modern, type-safe stack:

• Framework: Built with Next.js and TypeScript to handle complex state transitions and ensure a robust codebase.
• State Management: Centralized via UserContext, which serves as the "brain" of the application—calculating overdue logic and user metrics on every render.
• Infrastructure: While the project is currently deployed on Vercel for ease of access, the architecture follows the same container-ready principles I apply to my self-hosted Proxmox projects, ensuring the system is ready for automated CI/CD pipelines.

The Academic Alignment

This project directly satisfies the requirements for my laboratory activity. It specifically focuses on:

• User Model Variations: Supporting Beginner, Experienced, and Behavior-based states.
• Ethical Reflection: Respecting user autonomy by prompting for changes rather than forcing them.
• Heuristic Evaluation: Utilizing a built-in Simulation Panel that allows testers to artificially "stress" the user model to observe the adaptive logic in real-time.

Photos

Onboarding for New Users

Beginner Mode

Intermediate Mode

Expert Mode

Focus Mode