| Summary: | 碩士 === 稻江科技暨管理學院 === 網路系統學系碩士班 === 99 === This study aims to analyze the various course scores of pupils based on association rules of data mining technology, and the students with poor scores in all learning course will be screened to proceed with remedial teaching. Five scores of Chinese, English, Mathematics, Society, and Nature for various pupils were selected as analysis variables, and applied method of regression analysis to study the deviation in learning achievements caused by difference between town and country. The results will be as a reference for resources allocating in country elementary schools.An overall case association analysis, which set a condition of the minimum support with value of 0.1 and minimum reliability with value of 0.9, reveals a significant correlation among variables. In case of lower academic record by setting the condition shown above the association rules statement: The scores of English (ENG=E) and Society (SOC=D) for male pupils (SEX=M) were poor in country area (CITY=A), and required for remedial learning. According to the results of statistical analysis, that showed the correlation within learning scores of courses was significantly positive, and the same as results of association analysis. For the study of learning achievements based on difference between town and country, the scores in urban were significantly better than scores in village, and the female pupils were significantly better than male pupils in average scores for the T-test analysis.
|
|---|
