<![CDATA[The purpose of this study was to present a novel approach to identify factors that influence student attrition in an undergraduate Sport and Exercise Science (SpES) degree. A non-linear statistical technique was used to analyze demographic indicators of students enrolled in the first year of the SpES bachelor's degree at an Australian university (n = 312). Student dropout was successfully predicted using Chi-Squared Automatic Interaction Detection (CHAID). Using only four variables (i.e., Region, ATAR, Admission, & VCEBus), the model achieved an 87.50% classification accuracy. The article concludes with an endorsement of the proposed analysis to predict student dropout. Administrative and teaching-focused university staff may adopt the novel approach to identify the relevant demographic indicators for their respective institutions or programs of study in the management of student attrition. The limitations of this study are also discussed.]]>
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