Prediction of Academic Motivation Based on Variables of Personality Traits, Academic Self-Efficacy, Academic Alienation and Social Support in Paramedical Students.

BACKGROUND Academic motivation is one of the indices of success in scientific activities. Therefore, the goal of the present research is to predict academic motivation based on variables of personality traits, academic self-efficacy, academic alienation, and social support in students studying in different fields of paramedicine. METHOD The research was correlation-descriptive in which 183 paramedical university students in the academic year of 2019-2020 were selected by a two-stage cluster random sampling method, studying in the Kermanshah University of Medical Sciences. The data were collected through the Vallerand Academic Motivation questionnaire, NEO Personality Inventory Test, Sherer Self-Efficacy questionnaire, Fleming Social Support questionnaire, and Johnson Academic Alienation, and the collected data were analyzed (Pearson correlation coefficient and multiple regression) using SPSS V.22 software. FINDINGS The results showed that personality traits of extroversion (β=0.255,p<0.01), openness to experience (β=0.185,p<0.01), conscientiousness (β=0.136,p<0.01), and self-efficacy could predict academic motivation, significantly; but neuroticism (β=-0.188,p<0.05), and academic alienation (β=-0.111,p<0.05) reversely related to academic motivation. Self-efficacy (β=0.121,p<0.05) could significantly predict academic motivation. There was also a significant relationship between social support and academic motivation. CONCLUSION The results of the research illustrated that some of the personality traits and self-efficacy had a positive role in predicting academic motivation among paramedical students, and neuroticism and alienation had a reverse negative role in academic motivation. Therefore, in order to promote the academic level of students, it is necessary to improve the harmful effects of self-efficacy and some personality traits that improve better learning performance and quality.