Difference between revisions of "Public or Private K-12 School"
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* Several algorithms achieved better AUC and F1 for students who attended public high schools than for students who attended private high schools. | * Several algorithms achieved better AUC and F1 for students who attended public high schools than for students who attended private high schools. | ||
Queiroga et al. (2022) [https://doi.org/10.3390/info13090401 pdf] | |||
* Models predicting secondary school students at risk of failure or dropping out. | |||
* Models achieved high performances with an AUROC higher than 0.90 and F1-Macro higher than 0.88. | |||
* Models achieve better results when new data comes from the secondary education period (e.g., model M2G1-UTU achieved a performance of 95%). | |||
* First-year primary school zones (rural or urban) and sixth-year assessment-based grouping are two of the most important attributes of this model. | |||
Revision as of 15:08, 29 May 2023
Verdugo et al. (2022) pdf
- An algorithm predicting dropout from university after the first year
- Several algorithms achieved better AUC and F1 for students who attended public high schools than for students who attended private high schools.
Queiroga et al. (2022) pdf
- Models predicting secondary school students at risk of failure or dropping out.
- Models achieved high performances with an AUROC higher than 0.90 and F1-Macro higher than 0.88.
- Models achieve better results when new data comes from the secondary education period (e.g., model M2G1-UTU achieved a performance of 95%).
- First-year primary school zones (rural or urban) and sixth-year assessment-based grouping are two of the most important attributes of this model.