Guideline-Based Evaluation of Web Readability

Explainable AI (XAI)Recommender System UXCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Special Education TeachersUI/UX DesignersAssistive Technology Specialists

Effortless reading remains an issue for many Web users, despite a large number of readability guidelines available to designers. This paper presents a study of manual and automatic use of 39 readability guidelines in webpage evaluation. The study collected the ground-truth readability for a set of 50 webpages using eye-tracking with average and dyslexic readers (n = 79). It then matched the ground truth against human-based (n = 35) and automatic evaluations. The results validated 22 guidelines as being connected to readability. The comparison between human-based and automatic results also revealed a complex framework: algorithms were better or as good as human experts at evaluating webpages on specific guidelines – particularly those about low-level features of webpage legibility and text formatting. However, multiple guidelines still required a human judgment related to understanding and interpreting webpage content. These results contribute a guideline categorization laying the ground for future design evaluation methods.

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https://hci.top/en/papers/chi/4891/2019

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CHI
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Year
2019
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4 authors
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Subtopics
Explainable AI (XAI), Recommender System UX, Cognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)
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Special Education Teachers, UI/UX Designers, Assistive Technology Specialists
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Abstract only
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