Identification of the factors predicting students' academic failure in Ahvaz Jundishapur University of medical sciences in 2019

Academic failure is one of the problems of higher education, which leads to the loss of a large amount of facilities, resources and potential human talents every year, and leaves irreparable effects on individual, organizational and social dimensions. Predicting academic failure can be a useful step in preventing its negative consequences and the resulting damage. The aim of this study was to identify and predict the factors affecting the academic failure of the students at Ahvaz Jundishapur University of Medical Sciences. The present study is a predictive correlational study that was designed using Logistics regression analysis method with the aim of predicting group membership (students on academic probation) and achieving a Logit equation. The study sample consisted of 82 students on academic probation and 82 otherwise-matched students as a control group. Step-by-step logistics regression test showed that the effect of diploma grade point average (0.646), spiritual health (.065), academic fatigue (0.156), divergent learning style (-0.048), study condition stressors (0.079) and academic disinterest (-0.178) on academic failure, and in total, these 6 variables predict 76.2% of being put on academic probation.  A logistic regression model for predicting academic failure and identifying students at risk of academic failure is an effective tool for making informed decisions in universities. By identifying the factors influencing students' academic failure, it is possible to prevent academic failure in these students.