Project: Analyzing mathematical learning abilities in children using re-description mining for hierarchical data
Description
In this project, we analyze learning behavior in young children. We work with data collected by the Turku Research Institute for Learning Analytics, where children perform a variety of computer assisted tasks such as comparing numbers and simple calculation tasks.
Re-description mining is a powerful local pattern mining technique to discover subgroups in the data with similar descriptions. We aim to use this technique to discover similarities between different learning tasks.
However, re-description mining is commonly applied to IID data, whereas our data has a hierarchical structure. That is, per child we have multiple measurements from the same task and hence, measurements are not independently distributed.
The goal of this project is to further develop re-description mining methods to be applicable for hierarchical data.
For more information or to see if this project is a match for you, please do not hesitate to reach out: r.m.schouten@tue.nl.
Details
- Supervisor
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Rianne Schouten
- Secondary supervisor
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Mykola Pechenizkiy
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