Tianyuan Cai
Aleena Gertrudes Niklaus
ABSTRACT
Digital reading applications give readers the ability to customize fonts, sizes, and spacings, all of which have been shown to improve the reading experience for readers from different demographics. However, tweaking these text features can be challenging, especially given their interactions on the final look and feel of the text. Our solution is to offer readers preset combinations of font, character, word and line spacing, which we bundle together into reading themes. To arrive at a recommended set of reading themes, we combine crowdsourced text adjustments, ML-driven clustering of the resulting text formats, and design sessions. After four iterations of these steps, we converge on a set of three COR (Compact, Open, and Relaxed) themes that are designed for different readers.
Footnotes
1 In the full paper available at https://arxiv.org/abs/2303.04221, we demonstrate the study design and results in greater detail.
Footnote2 All designers were recruited from the same large U.S. corporation. Only full-time work experience was reported. Designers were similar to the population they design for [53, 82]. Based on their responses to the dyslexia questionnaire [25], two designers had above-average chances of having dyslexia.
Footnote3 In the pilot study, we started all participants with the default setting of Arial font at 16px, 1.2 line spacing, and default values of character and word spacing (0em), and we asked them to explore the text settings to arrive at a preferred format.
Footnote4 The larger number of participants in R0 was to allow the presets to deviate from the reading themes initialized from the pilot study, thus increasing the diversity of the formats in future iterations.
Footnote5 Readers with symptoms of dyslexia account for about 15-20% of the world population [4]. We maintained equal representation to ensure that their reading preferences were also adequately considered.
Footnote6 The very first iteration (R0) is initialized with a single theme for each participant, randomly selected from 6 representative combinations of (character, word, line spacings) from the pilot study (§3), randomly paired with one of our 8 study fonts to offer diverse starting points.
Footnote7 Eleven validation themes were selected from the pilot study by designers asked to spot poor reading formats created by crowdworkers.
Footnote
Supplemental Material
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Index Terms
- THERIF: Themes for Readability from Iterative Feedback
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