Accessible data visualization for ASRS-positive university students: A multi-criteria analysis of performance efficiency and user engagement

Abstract

Attention-Deficit Hyperactivity Disorder (ADHD) creates substantial educational and economic challenges, but digital information architecture often overlooks neurodiverse cognitive profiles, which results in overcrowded designs that cause cognitive overload. The study focuses on the effectiveness of the various data visualization formats on the processing efficiency and physiological stress among University students classified by the Adult ADHD Self-Report Scale (ASRS v1.1). The methodology employed a multi-criteria experimental study with 70 participants (40 ASRSnegative, 30 ASRS-positive) evaluating eight different visualization formats: Plain Text, Highlighted Text, Bar Charts, Bar Charts with Images, Pictographs, Simplified Infographics, Detailed Infographics, and Text modified by Artificial Intelligence. Inverse Efficiency Score (IES) was used to measure performance, and medical-grade pulse oximeters recorded real-time physiological stress measurements. Statistical rigour was ensured using Two-Way Mixed ANOVA, Linear Mixed-Effects Models (LMM), MANOVA, Bonferroni correction and Bayes Factors. Results revealed a very strong level of interaction (p < 0.001) that visualization formats have different effects on individuals with ADHD or ADHD likelihood. Plain Text, Bar Charts, and Bar Charts with Images maintained almost similar cognitive equity between both groups. Contrarily, Detailed Infographics and AI-Modified Text caused severe performance impairment (Hedges’ g = -1.775 and -1.162, respectively). Paradoxically, traditional attentional aids like text highlighting acted as visual noise, impairing ASRS-positive performance. Moreover, a critical finding revealed preferenceperformance dissociation: ADHD and ADHD-likelihood (ASRS-positive) individuals favoured visually complex designs that objectively hindered their accuracy and processing speed, underscoring the necessity for empirical metrics over subjective feedback. The practical design suggestions presented in the findings are based on concrete, empirically grounded results to establish digital learning environment settings that accommodate ADHD and ADHD-likelihood population.