Draft:The Readability Consortium
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|  |
| Formation | 2021 |
|---|---|
| Type | Non-profit |
| Headquarters | Orlando, Florida United States |
Parent organization | University of Central Florida Research Foundation |
| Website | thereadabilityconsortium |
The Readability Consortium (TRC) is a collaborative research initiative at the University of Central Florida founded in 2021 by the UCF Research Foundation, Readability Matters, and Adobe Inc. to support a scientifically based research community focused on enhancing digital reading efficiency and comprehension across devices for users of all levels. Google joined the initiative in 2022.[1][2] This founding group of non-profit and industry leaders serves as a member board to guide the joint effort of researchers and designers in advancing readability science and technology.
The Readability Consortium’s community is comprised of 18 members from the University of Central Florida’s Research Team as well as 13 research associates from institutions of higher education, non-profits, and industry. Associates include individuals affiliated with the University of Arizona, University of Northern Colorado, University of Toronto Mississauga, Tufts University, Royal Danish Academy, Berkeley University of California, ReadWorks, University of New Mexico, Chapman University, and New York University.[3] More than 110 community members across institutions provide subject matter research, population access, and specialized segments of readability research.
Studies show that variable typography creates optimal reading performance and can be personalized for the individual reader.[4] Character size, shape and line spacing affect reading ability.[5] Remote crowd workers were evaluated using online tests to determine personalized font recommendations across digital tools such as e-readers, web browsers and reading applications on phones. Using a machine learning model, reader characteristics were matched with recommended fonts, resulting in a “potential 35% increase in reading speed while maintaining comprehension.”[6][7]
TRC’s main areas of research with key findings from the scientific community include Psychophysics of Variable Typography, Information Design for the Individual, Readability in Education, and Readability Across Language and Culture.[8] The interdisciplinary consortium of academia, non-profits, and for-profit companies create datasets of digital reading behaviors, open source software based on psychophysics and machine intelligence with the goal of creating accessible tools that individualize the digital reading experience.
Further Reading[edit]
Best Font for Online Reading: No Single Answer
Introducing Variable Fonts – Fonts Knowledge - Google Fonts
Reading Skills: Individual Prescription
Prescriptions for reading? Using vision science to get you to read faster, better
What’s the best font? See how you and others perceive different types
External Links[edit]
References[edit]
- ^ Treitman, Rick. "Adobe Announces Readability Consortium with Google and University of Central Florida to Improve Reading for All Ages and Abilities | Adobe". blog.adobe.com. Retrieved 2024-01-30.
- ^ "Teaming Up to Improve Reading Research". Material Design. Retrieved 2024-01-30.
- ^ "Community - The Readability Consortium". 2022-10-26. Retrieved 2024-01-30.
- ^ Beier, Sofie; Berlow, Sam; Boucaud, Esat; Bylinskii, Zoya; Cai, Tianyuan; Cohn, Jenae; Crowley, Kathy; Day, Stephanie L.; Dingler, Tilman; Dobres, Jonathan; Healey, Jennifer; Jain, Rajiv; Jordan, Marjorie; Kerr, Bernard; Li, Qisheng (2022). "Readability Research: An Interdisciplinary Approach". Foundations and Trends® in Human–Computer Interaction. 16 (4): 214–324. doi:10.1561/1100000089. ISSN 1551-3955.
- ^ "Want to improve your reading skills? You might just need more space". 2021-11-29. Retrieved 2024-01-30.
- ^ Wallace, Shaun; Bylinskii, Zoya; Dobres, Jonathan; Kerr, Bernard; Berlow, Sam; Treitman, Rick; Kumawat, Nirmal; Arpin, Kathleen; Miller, Dave B.; Huang, Jeff; Sawyer, Ben D. (2022-08-31). "Towards Individuated Reading Experiences: Different Fonts Increase Reading Speed for Different Individuals". ACM Transactions on Computer-Human Interaction. 29 (4): 1–56. doi:10.1145/3502222. ISSN 1073-0516.
- ^ Hannon, Daniel; Rantanen, Esa; Sawyer, Ben; Ptucha, Raymond; Hughes, Ashley; Darveau, Katherine; Lee, John D. (November 2019). "A Human Factors Engineering Education Perspective on Data Science, Machine Learning and Automation". Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 63 (1): 488–492. doi:10.1177/1071181319631248. ISSN 2169-5067.
- ^ "Research - The Readability Consortium". 2022-11-01. Retrieved 2024-01-30.