Key determinants of education quality of secondary schools in Bangkok

Abstract

This study aims to investigate the key determinants of the quality of education of upper-secondary schools in Thailand focusing on the Bangkok Metropolitan area. Among the 219 the upper-secondary schools located in the studied territory, 149 schools under the supervision of the Office of the Basic Education Commission, Bangkok Metropolitan Administration, the Office of the Higher Education Commission, and the Office of the Private Education Commission were randomly selected. This sample size provided a 95 percent confidence level for all statistical tests when expanded to estimate the behaviors of the entire population. The dependent variable was education quality, while the examined independent variables, which were expected to have significant influence on education quality, included the transformational leadership of the school principal, teacher quality, and school facilities. A self-administered survey was conducted using the questionnaire, which was comprised of a demographic profile and information regarding all three independent variables. To accurately evaluate the education quality of the students in the selected schools, the Ordinary National Educational Test (O-NET) and the General Aptitude Test (GAT) scores were employed. Both examinations are organized by the National Testing Service (Public Organization) and are considered as the most reliable and standardized assessments in the nation to measure student academic proficiency. According to the respondents’ demographic profile, 59.7 percent were female and the age groups were fairly distributed from 25 to 60 years. All of the respondents were well educated, with 53.7, 44.3, and 2.0 percent receiving bachelor, master, and doctoral degrees, respectively. The average work experience was 19 years and most of the respondents had positive toward their career and planned to stay in their current job until retirement. This background information revealed that all of the respondents had sufficient qualifications and experience in their career so that the data obtained from their responses and opinions were precise and non-biased. The results from the factor analysis revealed that among the three independent variables tested, only teacher quality and school facilities had a significant impact on education quality in terms of the O-NET and GAT scores at a 95 percent confidence level. Teacher quality explained 50.0 and 71.2 percent of the total variances for the O-NET and GAT scores, respectively, while school facilities provided 42.9 and 27.5 percent accurate predictions for the O-NET and GAT scores, correspondingly. Hence, they can be judged as the key determinants for education quality at the upper-secondary school level. On the other hand, the transformational leadership of the school principal was unexpectedly found to have no statistically-significant relationship with education quality, in terms of both the O-NET and GAT scores. Nonetheless, the constructed multiple regression equations for the O-NET and GAT scores, which comprised all three independent variables, could sufficiently explain the O-NET and GAT scores up to a 61.8 and 75.0 percent accuracy, respectively. The remaining uncertainties might have been a result of other factors not included in this study; however, they were minor factors as compared to teacher quality and school facilities. Further analysis found that school facilities also had a significant impact on teacher quality, whereas transformational leadership did not. The teachers believed that 43 percent of their expertise and quality derived from the school facilities. Therefore, the consequent influence of the school facilities on the teacher’s quality was examined through path analysis. The results indicated that among the 50.0 percent of the total variance in O-NET scores under the influence of teacher quality, 21.5 percent could be considered as a consequence of the school facilities. As a result, the influence of school facilities on the regression variance of the O-NET score rose from 42.9 to 64.4 percent. Similarly, of the 71.2 percent of the regression variance for the GAT score which could be explained by teacher quality, 30.6 percent of this value could be considered as a consequence from school facilities through an indirect effect. Therefore, the total impact of school facilities on the GAT score increased from 27.5 percent (direct effect) to 58.1 percent. Nonetheless, this was still less than 71.2 percent of the direct effect of teacher quality. In conclusion, both teacher quality and school facilities can be considered as the key determinants of education quality in Thailand. Therefore, in order to raise the education quality of Thailand at this stage, education administrators and related parties should primarily focus on improving and developing teacher quality and school facilities.