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Code for "Generalisable Methods for Early Prediction in Interactive Simulations for Education" published at EDM 2022.

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Pipeline Lab

This repository helps implementing the whole pipeline used to process simulation logs and classify students into different groups according to their conceptual understanding.

It uses k-fold nested cross validation, and can do online and offline predictions on full and partial sequences.

Current state

This is the implementation of the general pipeline-lab. There is a branch for the beerslaw-lab and one for the capacitor lab. https://phet.colorado.edu/sims/html/beers-law-lab/latest/beers-law-lab_en.html

Structure

├── data
|	├── experiment keys
|	├── raw
|	├── parsed simulations
|	├── sequenced simulations
└── experiments
└── reports
└── src
|   ├── batches
|	├── configs
|	├── extractors
|	|	├── aggregator
|	|	├── cleaners
|	|	├── concatenator
|	|	├── encoding
|	|	├── lengths
|	|	├── parser
|	|	├── sequencer
|	├── logs
|	├── ml
|	|	├── gridsearches
|	|	├── models
|	|	├── samplers
|	|	├── scorers
|	|	├── splitters
|	|	├── xvalidators
|	├── notebooks
|	├── utils
|	├── visualisers
└── wikis

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Code for "Generalisable Methods for Early Prediction in Interactive Simulations for Education" published at EDM 2022.

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