Predicting prehospital care students' first-year academic performance.
OBJECTIVE
To answer two research questions: First, can previously identified factors relating to academic performance be used to predict first-year academic success for students undertaking a newly developed and vocationally oriented prehospital care course delivered in a rural setting? Second, can the study's findings be used to develop appropriate student selection criteria to assist in the admission of students into relevant tertiary studies or the prehospital care industry?


METHODS
A retrospective review of all first-year, on-campus prehospital care students enrolled in a vocational course at a rural Australian university from 1998 to 2001 was conducted. Six predictors of academic performance were examined, namely: University Admission Index (UAI), postsecondary educational qualifications, student entry type (traditional or mature-aged), previous health-related experience, gender, and background (rural or urban). Three dependent variables assessed academic performance: grade point average (GPA) of students who completed all required first-year subjects, GPA of students who completed at least one subject in the first year, and the student's ability to successfully complete the first year.


RESULTS
UAI > 50, previous health-related experience, postsecondary educational qualifications, background, student entry type, and gender were all found to be significant predictors of first-year academic performance in selective cohorts. In addition, a combination of predictors produced higher GPAs than did any single predictor.


CONCLUSIONS
Academic performance of first-year students in the prehospital care discipline can be predicted given the appropriate selection variables. Admission selection can be assisted with the generated Student Selection 001.
Madigan
Veronica
V
School of Public Health, Charles Sturt University, Bathurst, New South Wales, Australia. vmadigan@csu.edu.au
D000328:Adult; D017677:Age Distribution; D000488:Allied Health Personnel / Q000193:education* / Q000706:statistics & numerical data*; D004521:Educational Measurement / Q000706:statistics & numerical data*; D004522:Educational Status; D004632:Emergency Medical Services / Q000706:statistics & numerical data*; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D015999:Multivariate Analysis; D009517:New South Wales; D012189:Retrospective Studies; D012570:School Admission Criteria; D017678:Sex Distribution; D013336:Students, Health Occupations / Q000706:statistics & numerical data*