Open AccessEvaluation of Teacher Allocation in Regional Compulsory Education Industry Based on K-means clustering and GIS Spatial analysis: A Case Study of teacher-student ratio
Author(s) -
Yu Chen Limin Liu
Publication year - 2021
Publication title -
converter
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.104
H-Index - 1
ISSN - 0010-8189
DOI - 10.17762/converter.358
Subject(s) - cluster analysis , resource allocation , disequilibrium , resource (disambiguation) , compulsory education , computer science , common spatial pattern , hot spot (computer programming) , value (mathematics) , aggregate (composite) , environmental economics , mathematics education , geography , statistics , mathematics , economics , economic growth , artificial intelligence , machine learning , medicine , computer network , ophthalmology , materials science , composite material , operating system
The allocation of teacher resources can reflect the situation of regional education disequilibrium. It is an important research content to effectively evaluate the differences of regional teacher resource allocation and reveal the characteristics of spatial location. Take teacher-student ratio of compulsory education of five adjacent cities in China as an example, this paper focus on difference analysis and balanced evaluation of teacher resource allocation. Combined with geographical location, Differentiation coefficient, K-means clustering and GIS hot spot analysis methods are used to carry out the classification of teacher resource allocation and the spatial aggregation model of cold and hot spots. The results show that: there is an imbalance between different cities, as well as between districts and counties in same city.The results of K-means clustering and GIS hot spot analysis also show that regional teacher resource allocation has the characteristics of numerical classification and spatial aggregation. The k-means algorithm can aggregate the teacher-student ratio of 30 districts into three categories, revealing the category characteristics of teacher allocation. The results of GIS hotspots show that there are high value aggregation and low value aggregation in teacher configuration. The methods and research results of this paperprovide newresearch ideas for resource balance evaluation and spatial pattern analysis of education industry.