The Spatial Structure and Evolution Educational Anxiety—Research on Provincial Panel Based on Big Data Search

摘要

This research uses Python technology to obtain the daily Baidu index data of 175 groups of relevant vocabulary , such as “education and training” in 31 provinces and cities from 2011 to 2020. Using Baidu search index to construct a data model of “education anxiety” total index and macro variables, it explore s the temporal and spatial distribution and regional characteristics of education anxiety in various provinces in China. Research shows that at the regional level, the level of educational anxiety in East China, Central South, and North China is relatively high, and it has further increased over time, and the level of educational anxiety in Southeast, Northeast and Northwest regions is also gradually increasing. At the provincial level: by 2020, 15 provinces will enter the high level of education anxiety, and the level of education anxiety in other provinces will also increase significantly. The fixed effect model found that factors such as provincial GDP, urbanization rate, and education expenditure have statistically significant effects on “education anxiety”. Based on this, policy recommendations for alleviating education anxiety are put forward.