Study of Factors Influencing Academic Achievement: a Case Study of Probability and Statistics for Cadet Engineering, Royal Thai Naval Academy

Abstract

The objectives of this research are as follows. 1.) To compare the opinions of cadets on factors influencing the course achievement in the subject of probability and statistics for cadet engineering by considering two factors. Firstly, the individual factors consisting of 3 variables: learning attitudes, achievement motivation, interest in studying and teaching. And secondly, learning factors consisted of 4 variables: course content, teachers, classmates, facilities 2.) Create a regression equation showing the relationship of the factor variables and academic achievement in the subject of probability and statistics for cadet engineering. The research population was second through fourth-year cadet classes of Royal Thai Naval Academy of 332 students. The research tool was a questionnaire, check list, which passed the quality examination of pilot study method. The confidence value, reliability, of the questionnaire using Cronbach's Alpha Coefficient shows high level of reliability for the whole questionnaire. The statistics used for data analysis were mean, standard deviation, inflation variance, Pearson Correlation Coefficient analysis of variance and multiple regression analysis. The findings were as follows: 1.) The cadets valued teaching and learning factors more than personal factors. The variables that the cadet gave the highest influence were teachers with values ​​of 4.454 and 2.) The result of multiple regression analysis finding the influence of all predictive variables – learning attitude, achievement motivation, interest in studying, course content, teachers, classmates and facilities showed all prediction variables are related and there also is a linear relationship with the academic achievement. At the significance level of 0.05, the most correlated predictive variables had a high level of positive correlation was learning attitude at 0.870. The result of the data analysis of VIF inflation variance of all predictive parameters found that there were no multiple linear syndromes in the analysis of data in this research. The analysis of the regression coefficient found that the magnitude of the attitude influence is the highest at 1.596 and the result of regression analysis showed that the seven predictive variables were able to be composed to predict the learning achievement equal to 79.70%.