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Student-centered Education

Rich Data Systems Support Anytime, Anywhere Learning


The global reach of the mobile Internet offers students convenient access to world-class learning resources. Still, many resist using online platforms outside class to boost academic achievement.

This reluctance is understandable.

Digital learning frameworks collect troves of information about one's struggles with subject materials. But to reach each student in more meaningful ways, these systems must also intelligently revise study tracks to continue challenging that student as subject proficiency improve, and without making tasks too frustrating. But the critical insights for tailoring instruction strategies to individual academic needs are just too complex to reliably hand-code by human programmers.

Consequently, many technology-based interventions can feel procedural — designed to steer each student to predefined learning paths rather than encouraging progress toward mastery of a subject by attending to how one learns best.


BrainiacTV

Helping Students Learn Better


Brainiac TV personalizes digital learning tracks to each student's subject competence and preferred learning style, and then coaches that student through trouble spots to more effectively use one's limited study time.

This framework applies machine learning algorithms, multi-layered logic called "deep learning," to churn through the trail of data each student leaves behind for early signs of difficulty with essential concepts; and uses clues about one's optimal "learning profile" to focus each student on what matters most — with instruction strategies inspired by award-winning teachers that drive continuous academic improvement, and the latest findings from brain science about how we tend to pick-up new information faster, and retain it longer.


 AI Engines
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Updated August 3, 2017.  All Rights Reserved.