Indiana student sets her sights on speeding dyslexia diagnostics: BTN LiveBIG
If dyslexia is caught early, there are a whole host of measures that can be taken to help a child improve their educational plan. The problem is, dyslexia can be tough to detect. It takes the eagle-eyes of parents and teacher to notice the subtle signs of the language and reading disability.
But what if dyslexia diagnostics took mere moments instead of months or years? What if AI could be used to rapidly assess a child and render a verdict in minutes?
Indiana University senior Katie Spoon is creating a revolutionary neural network system that evaluates a child’s handwriting for possible symptoms of dyslexia with staggering accuracy. Her initial work was guided by Katie Siek, an associate professor at the IU School of Informatics, Computing and Engineering.
In an interview with News at IU Bloomington, Spoon outlined why it is so critical to properly identify dyslexia and begin working on an intervention plan in a timely fashion.
“An estimated 20 percent of kids have dyslexia or some other language-based learning disability,” said Spoon, who is enrolled in the accelerated master’s degree program at the IU School of Informatics, Computing and Engineering. “Those students need to be detected by second grade because, if you struggle to read in third grade, you’re more than four times more likely to drop out before finishing high school, and only 2 percent are detected by second grade.”
Across Bloomington, at elementary schools and child-focused service organizations, such as the Boys and Girls Club, Spoon has collected handwriting samples from a cross-section of children in order to build a comparison database. It is her hope that one day parents will be able to upload a writing sample from their child online in order to quickly get an initial diagnosis.
While still in the development stage, Spoon’s work has already garnered her awards. Recently, she accepted the Indiana University Provost’s Award for Undergraduate Research and Creative Activity in the category of Natural and Mathematical Sciences. She also earned the 2019 NCWIT Collegiate Award.
To learn more about Spoon’s research and how you can help grow her important database, visit her study website here.