Readability Experts Discuss their Collaborative Strategies to Create Better Readability for All

 

Adobe’s Tacy Trowbridge recently sat down with readability experts Zoya Bylinskii and Ben Sawyer for a lively and engaging conversation about the future of better reading.

Tacy leads Adobe’s Global Education Thought Leadership and Advocacy programs and hosts The Creative Educator podcast. Her latest episode, Reinventing How We Read, discusses the impact of literacy and reading and how tech, nonprofits, and academia together are taking a strategic approach to improving readability for all. This collaboration is producing incredible results.

In this episode, hear from Dr. Zoya Bylinskii, Research Scientist at Adobe, and Dr. Ben D. Sawyer, director of the Readability Consortium at the University of Central Flordia. They discuss personalized reading research progress, what tech companies are doing today and the implications for students and educators.

“What does it mean to personalize reading to the individual? That is what all of our research on readability is all about,” summarizes Zoya. “Our goals are to really open this up and make this a necessary part of [all] technologies… It is a societal good that we need to continue to offer.”

Ben notes, “Our goal is readability for all – information equity.” Excited about the possibilities for the future, Ben hopes that it may “change the way the world reads forever.”

Listen to the engaging and interesting podcast to hear more about how Zoya, Ben, and the entire readability ecosystem are building the future of personalized reading.

It’s a must-listen podcast!

Creative Educator PodcastThe Creative Educator: Reinventing How We Read

Imagine if you could read 20-35% faster, while maintaining or improving overall comprehension. Readability Consortium members Readability Matters, the University of Central Florida, Adobe and Google are working to make this a reality for everyone. Tacy is joined by lead researchers, Ben D. Sawyer, Ph.D., from the University of Central Florida, and Zoya Bylinskii, Ph.D., from Adobe’s Creative Intelligence Lab, to discuss how matching people with their most compatible reading format can greatly improve reading speed and comprehension.

 

About Tacy Trowbridge: Tacy leads Adobe’s Global Education Thought Leadership and Advocacy programs. Her team inspires and empowers educators and students around the world to become creators, not just consumers, of digital media. Prior to Adobe, Tacy was an educator and designed learning experiences, led global programs and organizations, and conducted research. She offers a unique insight into the ways students today use digital media to tell stories and to create. Tacy holds a Master’s Degree is Learning, Design and Technology from Stanford University. Connect at @tacytrow.

About Dr. Zoya Bylinskii: Zoya is a Research Scientist in the Creative Intelligence Lab at Adobe Research (in Cambridge, MA) and an Associate of the Institute of Applied Computational Science at Harvard University. Zoya received her Computer Science Ph.D. and M.Sc. from MIT in 2018 and 2015, respectively. Zoya works at the interface of human perception & cognition, computer vision, and human-computer interaction. She leads the readability research effort from within Adobe Research and is actively hiring interns in this space. More at www.zoyathinks.com. Connect at @zoyathinks.

About Dr. Ben D. Sawyer: Ben is Director of The Readability Consortium and The Virtual Readability Laboratory, where he leads teams rethinking how information flows from human to machine, and back. He is Faculty at UCF in the Department of Industrial Engineering and Management Systems within the College of Computer Engineering and Computer Science and The Institute for Simulation and Training. His previous positions include MIT’s Center for Transportation and Logistics and Air Force Research Laboratory 711th Human Performance Wing. More at bendsawyer.com. Connect at @bendsawyer.

 

Learn more:
The Readability Consortium Announcement
A Collaborative Interdisciplinary Readability Research Approach