# What Are Knewton’s Knowledge Graphs?

## A look into how Knewton represents content to power actionable insights and just-in-time remediation in alta

1. Solve the two-digit subtraction problem: 32–15
2. Solve one-digit subtraction problems (while performing the two-digit subtraction problem): 12–5, 2–1

# Extending the Example

The tiny Knowledge Graph above is a very simple example of how relationships between learning objectives can be represented. In many cases, a given learning objective can have multiple direct prerequisites. A simple example of a learning objective with two prerequisites can be found by looking at the learning objective requiring students to divide fractions. To divide fraction X by fraction Y, you multiply X times the reciprocal of Y. This means that in order to be able to divide fractions, you must already be able to (1) multiply fractions and (2) find reciprocals of fractions.

# Powering Just-In-Time Remediation

Knewton’s Knowledge Graphs allow us to generate adaptive recommendations based on pedagogical criteria, such as those reviewed by Graesser et al. (2012), including frontier learning, building on prerequisites, and providing remediation. For example, let’s go back to our struggling student. It is possible that our student may not have the prerequisite knowledge necessary to succeed in solving word problems with two-digit subtraction. If he struggles when solving these word problems in an alta adaptive assignment, Knewton’s recommendation engine can diagnose his prerequisite knowledge by using the information contained in the Knowledge Graph and provide just-in-time remediation in the form of targeted instructional content and formative assessment on the prerequisite learning objective(s) that he is struggling with. As the student masters the prerequisites, Knewton can move him forward towards his ultimate goal of learning how to solve word problems with two-digit subtraction.

# Sources

Doignon, J. P. and Falmagne, J. C. (1999). Knowledge Spaces. Springer.

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