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Accelerating Adult Readers with Typeface: A Study of Individual Preferences and Effectiveness

ACM CHI Conference on Human Factors in Computing Systems Extended Abstracts (CHI'EA)

Published April 25, 2020

Shaun Wallace, Rick Treitman, Jeff Huang, Ben D. Sawyer, Zoya Bylinskii

Information overload is the challenge of the modern era and text the medium. Every adult reader would benefit from faster reading, provided they could retain comprehension. The present work explores the reading speed gains possible solely by manipulating typeface. We consider that optimal typeface might be a matter of an individual's preferred font, or that some fonts might be better for all users. Indeed, eight in ten of our participants believed their favorite font would be their best. Instead, our findings showed that the preferred font was seldom best, and one font did not fit all. Adult readers in our study read better with varying fonts. An average 117 word per minute difference between worst and best typeface, or around 10 additional pages an hour, means font choice is of real-world significance. Our discussion focuses on the challenges of rapidly identifying an individual's optimal font, and the exciting individuation technologies such an advance allows.

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