중학생의 수학 교과역량에 영향을 미치는 언어 관련 개인, 가정, 수업 변인의 영향력 탐색

Abstract

Objectives In this study, the influence of various predictive factors was analyzed through artificial neural network model in order to explore the influence of language-related personal, family, and class variables on middle school students' mathematics competency. Structural relationships were analyzed by constructing a model with the selected major variables as predictors and mediator, and the mathematics competency as dependent variables. Methods For this purpose, the self-report questionnaire data of 2,235 middle school students in the 3rd year(2019) of the D-educational longitudinal study and the scores of the Korean language and mathematics competency tests were used for the analysis. An artificial neural network model was constructed that predicts mathematics competency based on language-related individual, family, and class variables that can predict mathematics subject competency and Korean competency. Structural equation model analysis was conducted by setting the structural relationship between language-related variables and mathematics competency as a research model. Results The purposes of this study were to specify variables related to convergence competency, and to analyze the structural relationships among them. The purposes of this study were to specify variables related to convergence competency, and to analyze the structural relationships among them. Conclusions As a result of checking the correlation coefficient between the training data and the predicted value in the process of building the artificial neural network model, the average of the error was 0.7, and the correlation coefficient was . 68, indicating adequate prediction performance. As a result of confirming the structural relationship between language-related variables and Korean competency and mathematics competency, individual, family, and class variables directly or indirectly had a significant positive effect on mathematics subject competency.