Core Technologies: Adaptive 2.0 Engine


Pedagogy

The core of Adaptive 2.0 Learning Technology is the Learning Cube, which is built around pedagogy, learning models, rich media, real-time feedback, and learner analytics. Adaptive Learning employs a pedagogical framework, containing multiple learning strategies, pathways, and educational content personalized for the individual. Individuals not only learn differently from others, but they also learn different kinds of content using different learning strategies. Each individual has a dominant learning strategy based on cognitive development and a unique pace to digest new learning content. Through continuous monitoring and statistical inference, a preferred learning strategy is determined for each individual by our sophisticated customization models. The 5 learning strategies included in Adaptive 2.0 courses are based on brain research and defined as Apprentice, Incidental, Inductive, Deductive and Discovery models. Each of the strategies includes a mix of content, media, cases, projects, exercises, and interaction to differentiate instruction to best meet each student’s learning preference.

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Big Data Analytics

With the ability to adapt to each student’s learning strategy you no longer have to worry. Our Adaptive 2.0 technology can assess, predict and assign a perfect learning strategy that is tailored to your students. With big data analytics we are able to figure out what will best help your students and take the stress out of using traditional methods that take much more time.


Remediation

The brain-based adaptive learning approach is extremely effective and has demonstrated very high learning outcome for students with individual learning needs. Although you are in a course and will have opportunity to interact with thousands of students online but you will still have a personalized learning experience with continuous feedback to improve your performance.

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