Predicting Academic Achievement of Male High School Students Using Different Statistical Methods and Path Analysis

The main objective of present study was to model the relationship between academicachievement and its related variables, including self-efficacy, family income, age, familydimensions, birth order and parents’ education. A sample of 100 male high school studentswas selected by random sampling technique to collect the data in 2010-2011. The results ofpresent study showed that academic achievement had positive and significant correlation withself-efficacy (r = 0.637**) and parents’ education (r = 0.446*), and negative significantcorrelation with family dimensions (r = – 0.364*) and birth order (r = – 0.329*). Thestatistical model developed by regressing academic achievement on measured items indicatedthat about 45.6% of the variability in academic achievement could be collectively accountedfor by all the predictor variables. The residual plots analysis showed no problem in the modelwith selected variables. On the other hand, t-test and tolerance index revealed that some ofthe variables are not important to be present in this model. Further, the model was optimizedusing stepwise multiple linear regression analysis and the results of the final modeldemonstrated that about 45.5% of the variability in academic achievement could be attributedto self-efficacy (R2 = 40.5%), parents’ education (R2 = 3.5%) and family income (R2 = 1.5%)only. Path analysis revealed that self-efficacy (0.578**), and birth order (– 0.395) had thehighest direct and indirect effects on academic achievement, respectively. The findings ofdifferent statistical methods suggested self-efficacy and parents’ education as the bestpredictors for modeling academic achievement.

کلیدواژه ها:

Academic achievement ، Statistical methods ، Male high school students