Difference between revisions of "Military-Connected Status"
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(Created page with "Baker at al. (2020) https://www.upenn.edu/learninganalytics/ryanbaker/BakerBerningGowda.pdf pdf * Model predicting student graduation and SAT scores for military-connected students * For prediction of graduation, algorithms applying across population resulted an AUC of 0.60, degrading from their original performance of 70% or 71% to chance. * For prediction of SAT scores, algorithms applying across population resulted in a Spearman's ρ of 0.42 and 0.44, degrading a...") |
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Baker | Baker et al. (2020) [[https://www.upenn.edu/learninganalytics/ryanbaker/BakerBerningGowda.pdf pdf]] | ||
* Model predicting student graduation and SAT scores for military-connected students | * Model predicting student graduation and SAT scores for military-connected students | ||
* For prediction of graduation, algorithms applying across population resulted an AUC of 0.60, degrading from their original performance of 70% or 71% to chance. | * For prediction of graduation, algorithms applying across population resulted an AUC of 0.60, degrading from their original performance of 70% or 71% to chance. | ||
* For prediction of SAT scores, algorithms applying across population resulted in a Spearman's ρ of 0.42 and 0.44, degrading a third from their original performance to chance. | * For prediction of SAT scores, algorithms applying across population resulted in a Spearman's ρ of 0.42 and 0.44, degrading a third from their original performance to chance. | ||
Revision as of 05:24, 3 February 2022
Baker et al. (2020) [pdf]
- Model predicting student graduation and SAT scores for military-connected students
- For prediction of graduation, algorithms applying across population resulted an AUC of 0.60, degrading from their original performance of 70% or 71% to chance.
- For prediction of SAT scores, algorithms applying across population resulted in a Spearman's ρ of 0.42 and 0.44, degrading a third from their original performance to chance.