System and Method for Selecting Predictors for a Student Risk Model

摘要

Systems and methods may automatically generate institution-specific, program-specific or course-specific student risk assessment models from an arbitrary set of potential risk predictors. Student data from previously completed courses are collected and used to create a design matrix of predictor values and an outcome vector. The system determines the coefficients for the model using an automated predictor selection method, such as lasso logistic regression. The system uses the model with current student data to assess an outcome probability, such as the risk of a current student from failing or dropping a course. In addition to an overall risk assessment model, component models focused on particular components of risk, such as performance, participation, attendance, timeliness, or student profile, can be generated. The component models may be used along with the overall risk assessment model to help explain the reasons behind the risk assessment.

主权项

1. A method for creating a model to assess student risk, comprising:
collecting historical student data for a plurality of students wherein the historical student data includes historical student data associated with a plurality of courses directed to a same subject and associated with a plurality of predictors of student risk; creating a design matrix by:
organizing the historical student data on an enrollment day basis so that historical student data associated with the predictors is associated with one of the courses, one of the students, and one of the days within the one of the courses; andtransforming the historical student data associated with at least one predictor; creating an outcome vector so that outcomes are associated with the historical student data organized on an enrollment day basis; determining coefficient values for the plurality of predictors using logistic regression, the design matrix, and the outcome vector; and using the coefficient values to create a model to assess student risk, wherein the model is configured to generate an outcome probability for a student in an on-going course using current student data.