Difference between revisions of "Socioeconomic Status"

Revision as of 10:23, 18 May 2022

Yudelson et al. (2014) pdf

Models discovering generalizable sub-populations of students across different schools to predict students' learning with Carnegie Learning’s Cognitive Tutor (CLCT)

Models trained on schools with a high proportion of low-SES student performed worse than those trained with medium or low proportion
Models trained on schools with low, medium proportion of SES students performed similarly well for schools with high proportions of low-SES students

Yu et al. (2020) pdf

Students from low-income households were inaccurately predicted to perform worse for both short-term (final course grade) and long-term (GPA)
Fairness of model improved if it included only clickstream and survey data

Yu et al. (2021) pdf

Models predicting college dropout for students in residential and fully online program
Whether the socio-demographic information was included or not, the model showed worse accuracy and true negative rates for students with greater financial needs if they are studying in person
The model showed better recall for students with greater financial needs, especially for those studying in person

@@ Line 13: / Line 13: @@
 * Students from low-income households were inaccurately predicted to perform worse for both short-term (final course grade) and long-term (GPA)
 * Fairness of model improved if it included only clickstream and survey data
+Yu et al. (2021) [https://dl.acm.org/doi/pdf/10.1145/3430895.3460139 pdf]
+*Models predicting college dropout for students in residential and fully online program
+*Whether the socio-demographic information was included or not, the model showed worse accuracy and true negative rates for students with greater financial needs if they are studying in person
+*The model showed better recall for students with greater financial needs, especially for those studying in person