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Web-Based, Real-Time Data Monitoring

This post was written by Joy Zheng, a student at Harvard University who interned at Knewton this summer. THE PROBLEM How do you quickly visualize and validate data in a large-scale, distributed, and...

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Parameter Recovery

1. Introduction Providing students with good study recommendations begins with understanding what they already know. At Knewton, we’re combining existing work on psychometrics and large scale machine...

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Generative Models for Description and Prediction

This summer I worked on the Analytics team at Knewton. One of the goals of analytics is to condense the huge amount of information generated by students interacting with educational products and...

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Ku Pima: To Measure

Trivia: Ku Pima means To Measure in the Xitsonga Language An Analytics (Data Science) team is made up of engineers/scientists with a wide array of skills. This results from the nature of the goals the...

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Algorithmically Generating Questions

Developing assessment materials is a lot of work. Teachers spend countless hours scavenging textbooks and developing original exercises for practice worksheets, homework problems, remedial materials,...

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Deciding Who is Right: Using Item Response Theory Instead of Majority Rule to...

As the saying goes, it takes a village to build an adaptive learning technology provider. Even when you have an entire village at your disposal, however, the added help may contribute more headache...

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Student Latent State Estimation with the Kalman Filter

The Kalman filter is an algorithm that estimates the values of unknown, or latent, variables from a series of noisy measurements taken over time. The Kalman filter has numerous applications in finance...

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Online Cross-Validation to Predict Future Student Behavior

At Knewton we use various mathematical models to understand how students learn. When building such models we want to make sure they generalize, or perform well for a large population of students....

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Offline Parameter Estimation

As part of my summer internship at Knewton, I helped design and implement an offline parameter estimation batch. This blog post discusses some of the design considerations and challenges associated...

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How Well Can You Predict Student Responses?

NIPS 2014 and Human Propelled Machine Learning Last month Knewton gathered along with the global data science community at NIPS, which has become one of the top conferences for cutting-edge machine...

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Latent Skill Embedding

In this post, we explore a probabilistic model of student learning and assessment that can be used to recommend personalized lesson sequences. A student using Knewton-powered products currently...

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