Machine Learning That Serves The Students, Not The Curricula

Technology innovation impacts nearly every industry and enables customers to get a personalized experience.  However, for some reason education still lags, with children still largely being taught in the same manner as 100 years ago.  Select implementations of technology in education like smart boards don’t really solve the core problem.  Instead, what we need is an educational approach that is student-centered, rather than curriculum-centered (Student-Centered Learning Environments: Foundations, Assumptions, and Design, Theoretical Foundations of Learning Environments (pp.3-25) Edition: 2ndChapter; Publisher: Taylor & Francis; Editors: David Jonassen, Susan Land).  True dynamic adaptive learning empowers the student by enabling him/her to be taught according to his/her needs.  Existing solutions feature adaptivity limited to student assessment and simple branching protocols rather than using the power of machine learning and cognitive analytics to make education customized for each and every student.

Instead, what we need is an educational approach that is student-centered, rather than curriculum-centered

Learnatric proposes to blend innovative pedagogy with true machine learning to deliver value to students by utilizing cognitive analytics that interfaces with the learning science built into the back end of our system – an approach that will result in an online learning system that offers true adaptive learning that responds to the student’s need on a fully dynamic basis.  The pedagogy is based on the concept of Threshold Concepts and Troublesome Knowledge (Threshold Concepts and Troublesome Knowledge: Epistemological Considerations and a Conceptual Framework for Teaching and Learning, Jan Meyer and Ray Land, 2005.).  Using this blend, we now have the ability to identify the specific source of difficulty and opportunity for each child in a truly dynamic way.

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