Research On The Current Situation Of Children's Family Mathematics Learning Environment

Home math environment,as the first math learning environment children was exposed to,lots of projects study on this in other countries,which prove that it has great influence on the early math competence development of children.However,at present,there are still lack of related research in C hina.Therefore,on the basis of existing research,this study explores the current situation of the home math environment.This study assesses 291 parental mathematics expectation,parental mathematics anxiety,parental mathematics attitude,and home mathematics activities through parental questionnaires.The data were analyzed by SPSS19.0,such as descriptive statistics,variance analysis,correlation analysis and regression analysis,and the following conclusions were obtained: 1.Parents have different mathematics expectation level in different type of mathematics ability.Parental mathematics expectation effected by the impact of economic income and children' age.The higher the economic income,the higher the parental numeracy expectation level.The higher the child's age,the higher the parental numeracy expectation and spatial expectation.2.Different type of home mathematics activities have different frequency.Home mathematics activities frequency effected by the impact of children' age and gender.The higher the child's age,the higher the home numeracy activities and technology-related mathematics activities frequency.Compared with girl,the home spatial activities frequency was reported in a relatively a high level.3.Parental numeracy expectation is positively correlated with numeracy activities,and parental numeracy expectation can significantly predict the numeracy activities.Parental mathematics anxiety is negatively correlated with numeracy activities,and parental mathematics anxiety can significantly predict the numeracy activities.4.Parental mathematics anxiety is negatively correlated with spatial activities,and parental mathematics anxiety can significantly predict the spatial activities.