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Friday, February 22 • 3:15pm - 3:35pm
KEYNOTE: A New Model of Knowledge Assessment and AI Adaptive Learning

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In this talk, Dr. Dan Bindman will describe a powerful new multi-dimensional model for knowledge assessment and learning that he is now working to implement with Yixue Squirrel AI Learning for their adaptive learning products. This new model gives extremely accurate and high resolution predictions at the highest granularity level: after a student has answered only 20 to 25 questions in a given product, the system can accurately predict the student’s probability of answering each question in the product at the current time. And unlike systems such as ALEKS, the model does not require Knowledge Structures linking the topics, saving a huge amount of costs compared to adaptive learning systems that require this step. It also can be used “out of the box” with any mix of question formats (free response or multiple choice) from any mix of subject areas without any content tweaking. Finally, all results so far indicate each student’s knowledge (as represented by the model) can be accurately updated as the student learns and works on questions in the product without the need of periodic reassessments, eliminating a big “pain point” for students that occur with many adaptive learning systems. The results from a real-world large-scale application of the model will be given to show the model’s unprecedented accuracy and predictive power.

Speakers
avatar for Dan Bindman

Dan Bindman

Chief Data Scientist, Squirrel AI Learning
Dan Bindman received his Ph.D. from the Institute For Math Behavioral Sciences at UCI in 2002. He then spent the next 12 years at ALEKS, a pioneer in online adaptive learning focussed on Math and Chemistry, where he eventually became Editorial Director and Chief Architect for the... Read More →


Friday February 22, 2019 3:15pm - 3:35pm
Main Stage

Attendees (134)