Mark Angel

CEO Amira Learning

Mark Angel is the CEO and Co-founder of Amira Learning, a company
revolutionizing the way students learn to read through the use of artificial
intelligence. Amira has introduced the first AI reading assistant designed
specifically for K-5 classrooms. Prior to founding Amira Learning, Mark
served as the Chief Technology Officer at Renaissance Learning, where he led
the R&D organization and contributed to the success of two of the most widely
used reading apps in the United States – Accelerated Reader and STAR.
With over 30 years of experience in Silicon Valley, Mark has held roles as a
CEO, CTO, and General Manager for several pioneering companies in the
fields of Artificial Intelligence and Natural Language Processing, including
Ernst & Young, Nuance, and KANA Software. He has founded two successful
startups: Papyrus Technology, an early leader in Wall Street trading
technology acquired by Ernst & Young, and Knova, a company that pioneered
contact center technology, went public, and was eventually acquired by a
leading private equity firm.
Mark is a named inventor on more than 10 patents in the areas of natural
language processing. His extensive background and innovative contributions
have positioned him as a leading figure in the development of AI-driven
educational technology.

1:30 PM - 2:15 PM

Second Day Oct 29

Option 3: Amira Learning

Topic: Past the Hinge Point: What Classroom AI Must Prove Before It Reaches a Childanadian-Built MicroChat

Room: TBD

The Presenter:Mark Angel, CEO Amira Learning

Session description

Ask Canadian district leaders about their current position on student-facing AI and most will say, “Proceed with caution.” Part of the reason is that most AI in schools is built for adults. Amira CEO Mark Angel, a 30-year AI and speech-technology veteran, shows what changes when AI is purpose-built for how children learn to read. Amira listens to a child read aloud, catches the reading errors in real time, and gives teachers their next instructional move. Attendees will get an in-depth look under the hood of a working classroom AI model: Amira’s Reading Error Detection model, trained on children’s voices.

The discussion will put classroom AI to three tests: Is it grounded in the science, with evidence to back it? Does it advance equity, serving every learning fairly? Does it keep teachers in the driver’s seat of personalized learning? Together, these tests show what classroom AI must prove to earn a green light.