Jul 13, 2020
SAN FRANCISCO, July 15. 2020 /PRNewswire/ -- Amira, AI powered software for helping students become better readers, has received four new awards for effectiveness and innovation. These awards include:
Amira Delivers Interactive Tutoring As A Student Reads
Right now, schools are looking for new ways to deliver remote learning and to help students catch up and recover from the Covid slide. Amira's ability to help students accelerate reading mastery has resulted in significant recognition from independent evaluators as an important innovation.
During the 2019-20 school year, Amira's effectiveness was demonstrated in leading Districts across the country. As the school year concludes, Amira has received widespread recognition for effectiveness, including:
and, finally,
4. Amira is a 2020 Extreme Tech Challenge (XTC) Finalist. XTC is the world's largest startup competition focused on global challenges. Leading investors evaluated more than 2400 startups in 87 countries, selecting Amira as one of 4 finalists in the Education category.
"Amira is gaining increased recognition as the software helps thousands of students keep growing even when working at home," said Mark Angel, CEO of Amira Learning. "Amira is the perfect online solution for Reading Tutoring and is proven to mitigate the COVID gap."
Amira enables students to read appropriately challenging stories out loud, providing interactive tutoring as they stall, stumble and mispronounce. As the student reads, Amira uses AI to understand what's tripping up the young reader, and then delivers micro-interventions that best build the gapped reading skills. Amira is the product of more than 20 years of research and development, utilizing innovation created at and licensed from Carnegie Mellon's AI Lab and the University of Texas Health System. In peer-reviewed, independent research conducted by leading universities around the world, Amira has generated amazing growth in reading ability, equivalent to giving a student a certified human tutor.
SOURCE Amira Learning
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