Towards Individuated Reading Experiences: Different Fonts Increase Reading Speed for Different Individuals
| Autor: | Shaun Wallace, Zoya Bylinskii, Jonathan Dobres, Bernard Kerr, Sam Berlow, Rick Treitman, Nirmal Kumawat, Kathleen Arpin, Dave B. Miller, Jeff Huang, Ben D. Sawyer |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | ACM Transactions on Computer-Human Interaction. 29:1-56 |
| ISSN: | 1557-7325 1073-0516 |
| DOI: | 10.1145/3502222 |
| Popis: | In our age of ubiquitous digital displays, adults often read in short, opportunistic interludes. In this context of Interlude Reading , we consider if manipulating font choice can improve adult readers’ reading outcomes. Our studies normalize font size by human perception and use hundreds of crowdsourced participants to provide a foundation for understanding, which fonts people prefer and which fonts make them more effective readers. Participants’ reading speeds (measured in words-per-minute (WPM)) increased by 35% when comparing fastest and slowest fonts without affecting reading comprehension. High WPM variability across fonts suggests that one font does not fit all. We provide font recommendations related to higher reading speed and discuss the need for individuation, allowing digital devices to match their readers’ needs in the moment. We provide recommendations from one of the most significant online reading efforts to date. To complement this, we release our materials and tools with this article. |
| Databáze: | OpenAIRE |
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