In an era of breakneck change and tech innovation, evaluating dyslexia in young students looks much the same today as it has in the past: A struggling reader’s parents and teachers might sit down, gather information and assess the child on their strengths and weaknesses to determine a diagnosis and appropriate interventions.
Often this is done via paper tests—despite the growing usage of predictive analytics in schools, where there are seemingly as many data dashboards as students in a classroom. All that’s to say, it seems like an industry almost too tempting for deep-pocketed tech investors and an ambitious startup with an eye on using machine learning to trim the fat.
“Today’s methods are quite cumbersome,” explains Frederik Wetterhall, the CEO and co-founder of Lexplore, a company that has devised a dyslexia screening tool that pairs eye tracking cameras with AI and algorithms. “With paper- and pen-based tests, it’s quite hard to read the results and takes a lot of time. [Educators] ask, ‘Who are the kids we think have difficulties?’ and they miss a lot of kids.”
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Abel Vaquera's curator insight,
January 19, 2019 3:01 PM
Student can be screen and diagnosis and can seek appropriate help to succeed in school.
Stephanie Elise Gonzalez's curator insight,
February 2, 2020 1:42 AM
Though this goes more into the field of diagnosticians, I believe that the use of AI in detecting dyslexia is a phenomenal tool that can speed up the process of diagnosing.
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