Show Me what You Mean: Inclusive Augmented Typography for Students with Dyslexia

Augmenting the visual appearance of continuous text may contribute to more inclusive learning opportunities for university Students with Dyslexia (SwD). This neurodiverse population remains largely reliant on reading tools developed for ‘typical’ readers. Although SwD find reading slower, more tiring, and more difficult, they are also known to use deep learning approaches, which may be assisted by inclusive, custom typographic and layout systems. While printed texts offer only one typographic presentation and make limited use of visual cues, the affordances of digital reading tools could result in multiple visual adaptations to suit individual needs, preferences, and reading. This can be achieved with networked devices using Artificial Intelligence (AI) to read the content in texts, and applying real-time typography and layout modifications. A human-centred design approach is required if we aim to develop inclusive reading experiences to better serve the educational requirements of SwD. This application of our understanding of the diversity of human abilities may also open new possibilities for other marginalised readers and the wider academic reading population.

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Publication Details

Journal
Visible Language
Published
2025-05-28
DOI
https://doi.org/10.34314/91m10w95
Citations
1
Primary Topic
Subtitles and Audiovisual Media
Type
article
Field-Weighted Citation Impact
10.42
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article

Show Me what You Mean: Inclusive Augmented Typography for Students with Dyslexia

Myra Thiessen, Darren Taljaard
1 citations
Visible Language
Subtitles and Audiovisual Media
10.42
article

Show Me what You Mean: Inclusive Augmented Typography for Students with Dyslexia

Myra Thiessen, Darren Taljaard
article en
1 citations

Abstract

Augmenting the visual appearance of continuous text may contribute to more inclusive learning opportunities for university Students with Dyslexia (SwD). This neurodiverse population remains largely reliant on reading tools developed for ‘typical’ readers. Although SwD find reading slower, more tiring, and more difficult, they are also known to use deep learning approaches, which may be assisted by inclusive, custom typographic and layout systems. While printed texts offer only one typographic presentation and make limited use of visual cues, the affordances of digital reading tools could result in multiple visual adaptations to suit individual needs, preferences, and reading. This can be achieved with networked devices using Artificial Intelligence (AI) to read the content in texts, and applying real-time typography and layout modifications. A human-centred design approach is required if we aim to develop inclusive reading experiences to better serve the educational requirements of SwD. This application of our understanding of the diversity of human abilities may also open new possibilities for other marginalised readers and the wider academic reading population.

Visible LanguageVol. 57(1)
Australian Regenerative Medicine Institute (AU), Monash University (AU), The University of Adelaide (AU)
Openalex Percentile: Top 4%
Subtitles and Audiovisual Media
10.42
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Show Me what You Mean: Inclusive Augmented Typography for Students with Dyslexia — Myra Thiessen, Darren Taljaard · Visible Language (2025) | TGRS Research Map | TGRS