Research on the development of urban and rural basic education based on analytic hierarchy method

Abstract

Listen

Translate article

In order to analyze the factors affecting basic education, such as the number of schools, the condition of basic equipment, the number of teachers, and the proportion of school area in elementary, middle, and high schools, we derived the time difference between urban and rural basic education for this period by finding various types of data for rural and urban areas from 2010 to 2022 and then comparing and analyzing the various types of data for rural and urban areas. The analytical hierarchy was then used to determine the importance of these indicators. This shows that the gap between urban and rural basic education has widened over time in these areas discussed. From 2010 to 2022, the changes in the penetration of information technology, the number of multimedia devices, the promotion rate, and the students' and physical education; satisfaction with the use of multimedia devices and the problems that teachers encounter when using multimedia were analyzed for both urban and rural primary and secondary schools. The TOPSIS integrated analysis was used to determine the most important influencing factors and their impact on the level of basic education. Finally, it was concluded that multimedia technology has both favorable and unfavorable effects on the level of basic education, but the favorable effects far outweigh the unfavorable effects, and overall it still greatly promotes the development of the level of basic education and helps to promote the balanced development of education. Before the implementation of the double reduction policy, we looked for the extracurricular tuition of rural and urban primary, middle and high school students, the promotion rate of rural and urban primary and secondary schools, and the proportion of extracurricular activities. Then we looked for corresponding data after the implementation of the double reduction policy, analyzed the correlation of these data, determined the impact of these data on the level of basic education, and used the analytical hierarchy to rank the importance of these factors. This policy has reduced the pressure of involutional competition for urban students and enriched their after-school life. For rural children, transfer rates have increased.