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Cultivate Growth

A smarter solution for reading growth, powered by AI and rooted in the Science of Reading. 

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AI-driven dyslexia diagnostic screener for early detection and targeted support. 

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Meet diverse student needs and unify learning systems with AI.

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Predict, identify, and prioritize literacy needs for all students with AI.

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LIVE WEBINAR

Assessment Upgrades
for SY25-26 

Combining the best of Amira and Istation

Tuesday, Feb 25, 2:00pm ET

Duration: 60 minutes

Join us for an exclusive deep dive into the next generation of reading assessments, where innovation meets proven science. This webinar will unveil how we’re combining the best of Amira’s AI-powered assessment with Istation’s renowned ISIP assessment to create the most accurate reading assessment yet.

Register Now

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Discover how this groundbreaking assessment:

  • Delivers unmatched precision in measuring and analyzing reading skills along Scarborough's Reading Rope.
  • Generates a more accurate dyslexia screening by capturing over 10x more data points than traditional assessments.
  • Provides Science of Reading insights that pinpoint every student's specific needs connected to your core curriculum.
  • Eliminates the need for teachers to handle proctoring and scoring while creating a low-stress assessment experience for students.
  • Removes bias, ensuring every student receives a fair and precise assessment.

Whether you’re a district leader, teacher, or instructional coach, this webinar will showcase how our enhanced assessment will provide the most accurate view of reading performance and growth. 

Reserve your spot today!

Presenter

Dr. Ran Liu

Vice President and Chief AI Scientist, Amira Learning

Ran Liu leads both the AI and psychometrics teams at Amira Learning. A recognized pioneer working at the intersection of reading science, AI, and measurement, she combines a deep research background with extensive EdTech experience. She earned her Ph.D. in cognitive and computational neuroscience from Carnegie Mellon University, with a focus on modeling speech, language, and reading acquisition. Her post-doctoral research at Carnegie Mellon's School of Computer Science then focused on developing AI for educational applications that improve classroom learning outcomes. During that time, she also worked on groundbreaking extensions of psychometric models for educational measurement. Ran’s post-academic career spans several leadership roles at education technology companies. She has deep expertise and is a leading voice in developing AI systems that can understand, assess, and support student learning.

Ran Liu Headshot Circle