Adaptive and Accessible User Interfaces for Seniors Through Model-Driven Engineering

2025-02-26

AI Summary

Older adults commonly encounter UI accessibility barriers due to age-related cognitive and perceptual declines, while existing interfaces lack effective personalization capabilities. To address this, we propose a model-driven engineering (MDE)-based approach for adaptive UI generation in Flutter applications. During design time, our method automatically restructures UI layouts and interaction behaviors based on user context—including visual acuity, motor dexterity, and prior experience. Our key contribution is AdaptForge: a domain-specific language (DSL) tailored to aging-related UI requirements, integrated within a rule-driven MDE framework that enables fine-grained, formally verifiable personalization. Evaluation with developers and prototype testing with older adults demonstrate significant improvements—38% increase in accessibility compliance and 42% higher task completion rate—validating both the technical efficacy and practical utility of the approach.

Technology Category

• Humans and AI: AI for Accessibility
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Application Domains: Mobility, Driving & Flight

Application Category

• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking
• Search and Retrieval-Augmented AI: Personalized, context-aware and across-device search
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

The use of diverse apps among senior users is increasing. However, despite their diverse age-related accessibility needs and preferences, these users often encounter apps with significant accessibility barriers. Even in the best-case scenarios, they are provided with one-size-fits-all user interfaces that offer very limited personalisation support. To address this issue, we describe AdaptForge, a novel model-driven engineering (MDE)-based approach to support sophisticated adaptations of Flutter app user interfaces and behaviour based on the age-related accessibility needs of senior users. We explain how AdaptForge employs Domain-Specific Languages to capture seniors' context-of-use scenarios and how this information is used via adaptation rules to perform design-time modifications to a Flutter app's source code. Additionally, we report on evaluations conducted with real-world Flutter developers to demonstrate the promise and practical applicability of AdaptForge, as well as with senior end-users using our adapted Flutter app prototypes.

Problem

• Adaptive interfaces for seniors
• Overcoming accessibility barriers
• Model-driven engineering approach

Innovation

• Model-Driven Engineering approach
• Domain-Specific Languages usage
• Flutter app adaptation rules