Predicting student attrition in a baccalaureate curriculum.

Area of Science:

• Nursing Education
• Educational Psychology
• Student Affairs

Background:

• Student attrition poses challenges for nursing schools.
• Accurate prediction of attrition is crucial for student support and curriculum planning.
• Previous methods for predicting attrition lacked precision.

Purpose of the Study:

• To develop and validate a predictive model for nursing student attrition.
• To improve measures of student retention and attrition for counseling and planning.
• To identify key variables differentiating continuing students from dropouts.

Main Methods:

• Longitudinal analysis of enrollment data from the University of Wisconsin--Madison School of Nursing.
• Discriminant analysis of achievement, learning style, and psychological variables.
• Development of a predictive function based on significant differentiating variables.

Main Results:

• A significant differentiation (p < .000) was found between continuing and dropout nursing students.
• A predictive function was successfully developed to estimate student success.
• The model demonstrated effectiveness in identifying students likely to succeed or not.

Conclusions:

• The developed model offers a precise method for predicting nursing student attrition.
• This tool can enhance counseling and planning within nursing education programs.
• Identifying at-risk students early allows for timely intervention and support.