Heatmaps Illustrating Relationships between Underlying Measures of Student Performance and Learning (IMAGE)

U.S. National Science Foundation

Heatmaps Illustrating Relationships between Underlying Measures of Student Performance and Learning

Caption

The LearnSphere project led by Carnegie Mellon University seeks to improve educational outcomes by upgrading the infrastructure for educational data mining. Summarizing data from 8,341 students doing online math problems involving 2,400 skills, these heatmaps illustrate relationships between four underlying measures of student performance and learning: prior knowledge, learning rate, guess rate and slip rate. These measures are used to identify student strengths and weaknesses so educators and educational technology can more efficiently personalize the learning experience for students.

Credit

Steven Ritter, Carnegie Learning

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