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ADAPTIVE LEARNING SYSTEM

THE CHALLENGE

Massive Open Online Courses (MOOCs) make education available at scales never seen before, however they often have a one-size-fits-all approach. Our client was an early developer in this space, and saw the opportunity for a disruptive platform that could focus on learnings of an individual learner.

OUR APPROACH

We decided to build a platform that can be used to a create course pathway with adaptive learning techniques through which people can learn the same course in different ways and achieve the same level of proficiency irrespective of their skills and comprehension levels.

METHODOLOGY

  • Our data scientist created a model that would generate alternative paths for students to complete the course, based on their individual competencies and content preferences.
  • We modelled dependencies
    • between skills, sub skills, misconceptions and learning objectives and,
    • between content and skills
  • The ML algorithm also collected evidence data of student engagement and its impact on skill proficiency, to continuously improve the learning outcome.

TECHNIQUES, TECHNOLOGIES, TOOLS

Bayesian Graphical Models

THE RESULT/IMPACT

Within 6 months we successfully created a platform that generates personalized content pathways for every learner leading to increased student engagement and learning outcomes.