Knewton Enterprise
Platform Documentation

Design, Build and Integrate world class adaptive learning products with the Knewton Enterprise Platform

Knewton Enterprise Adaptive Learning Platform

Knewton provides a flexible and powerful adaptive learning platform on which partners can build digital products. Knewton personalizes learning paths so every learner is engaged and supported to reach their full potential.

Adaptive Recommendations

A recommendation is a piece of content that Knewton has determined to be most relevant for a student at a given time, considering what is known about what they have done.

Learner Analytics

Analytics are calculated from the learner’s performance, history and goals. They help the instructor predict how a student will perform if they continue along their current path without intervention.

Content Insights

Based upon how your learners have consumed recommended content, content insights help figure out how well your content is performing, and help priotise editor efforts.

How Knewton Works

The Knewton platform is accessed through the flexible Knewton API, and is built to power an array of features within existing or new digital education products. Partners can harness the Knewton API to create continuously adaptive learning experiences. A learner-facing product sends learner interaction and performance data to Knewton, then receives personalized recommendations and analytics via the Knewton API.

Learner

Partner Applications

Knewton API

Knewton
Platform

  • Knowledge Graph
  • Accounts and Profiles
  • Registrations and Learning Instances
  • Goals
  • Learner Events
  • Recommendations
  • Analytics
Learner

Learners interact with a partner-product by completing lessons, homework, and assessments. Read more

Partner Applications

A partner’s learning application sends learner interaction and performance data to Knewton via the Knewton API. Read more

Knewton API

The Knewton API returns personalized recommendations and analytics to the partner’s learning application. Read more

Knewton Platform - Knowledge Graph

The Knewton platform maps the pedagogical relationships between the concepts in a partner’s content (lessons, homework, and assessments) to form a “knowledge graph.” Knewton uses this knowledge graph to interpret incoming data and recommend appropriate activities to the the learner. Read more

Knewton Platform - Accounts and Profiles

The Knewton platform stores information about the users within the partner application to enable personalized and accelerated learning. Read more

Knewton Platform - Registrations & Learning Instances

The Knewton platform records the learning instances (classes, groups) and the registrations (learners, instructors) within those learning instances. Read more

Knewton Platform - Goals

The Knewton platform stores partner- or instructor-created learning goals (like assignments and quizzes) to define the scope and deadlines used to guide personalized recommendations. Read more

Knewton Platform - Learner Events

The Knewton platform stores a history of all learner events sent via the API. Read more

Knewton Platform - Learner Events

The Knewton platform returns personalized recommendations to the partner’s application. Read more

Knewton Platform - Learner Analytics

The Knewton platform returns inferred metrics to drive visualizations in partner applications. Read more

Knewton technology works across nearly any subject area or learner demographic. Partners connect the lessons, homework, and assessments in their applications to the Knewton platform in order to deliver uniquely personalized and accelerated learning experiences that continuously adapt to each learner. Knewton matches learners with the optimal lesson, question, explanation, or activity — exactly when they need it. Knewton’s data scientists, software engineers, product managers, adaptive instruction analysts, implementation architects, and other team members have devoted their careers to helping instructors differentiate instruction more effectively, making the underlying technology scalable, and ensuring the platform continues to serve learners, instructors, and publishers as the technological landscape around it improves and changes.

Thinking Adaptively

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