Difference between revisions of "Public or Private K-12 School"

Revision as of 15:07, 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) [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.

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 * 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) <nowiki>[https://doi.org/10.3390/info13090401 pdf]</nowiki>
+<nowiki>*</nowiki> Models predicting secondary school students at risk of failure or dropping out.
+<nowiki>*</nowiki> Models achieved high performances with an AUROC higher than 0.90 and F1-Macro higher than 0.88.
+<nowiki>*</nowiki> Models achieve better results when new data comes from the secondary education period (e.g., model M2G1-UTU achieved a performance of 95%).
+<nowiki>*</nowiki> First-year primary school zones (rural or urban) and sixth-year assessment-based grouping are two of the most important attributes of this model.