Each year, roughly 30% of first-year students at US baccalaureate
institutions do not return for their second year and over 9billionisspenteducatingthesestudents.Yet,littlequantitativeresearchhasanalyzedthecausesandpossibleremediesforstudentattrition.Here,wedescribeinitialeffortstomodelstudentdropoutusingthelargestknowndatasetonhighereducationattrition,whichtracksover32,500students′demographicsandtranscriptrecordsatoneofthenation′slargestpublicuniversities.Ourresultshighlightseveralearlyindicatorsofstudentattritionandshowthatdropoutcanbeaccuratelypredictedevenwhenpredictionsarebasedonasingletermofacademictranscriptdata.Theseresultshighlightthepotentialformachinelearningtohaveanimpactonstudentretentionandsuccesswhilepointingtoseveralpromisingdirectionsforfuturework.