Title of article
Learning patterns of university student retention
Author/Authors
B.C. Nandeshwar، نويسنده , , Ashutosh and Menzies، نويسنده , , Tim and Nelson، نويسنده , , Adam، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2011
Pages
13
From page
14984
To page
14996
Abstract
Learning predictors for student retention is very difficult. After reviewing the literature, it is evident that there is considerable room for improvement in the current state of the art. As shown in this paper, improvements are possible if we (a) explore a wide range of learning methods; (b) take care when selecting attributes; (c) assess the efficacy of the learned theory not just by its median performance, but also by the variance in that performance; (d) study the delta of student factors between those who stay and those who are retained. Using these techniques, for the goal of predicting if students will remain for the first three years of an undergraduate degree, the following factors were found to be informative: family background and family’s social-economic status, high school GPA and test scores.
Keywords
DATA MINING , student retention , Predictive modeling , Financial Aid
Journal title
Expert Systems with Applications
Serial Year
2011
Journal title
Expert Systems with Applications
Record number
2350670
Link To Document