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Exploring Factors Contributing to Student Sociability in Canada: A Machine Learning Approach
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DOI：10.1177/08295735261447107.png)
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Abstract
En 中文
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Sociability plays a critical role in students’ social interaction, collaboration, and emotional well-being. This study examines factors associated with student sociability using data from the 2021 OECD Survey on Social and Emotional Skills, focusing on Canadian students aged 10 and 15 (
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= 5,440). A machine learning approach was employed to model sociability as a continuous outcome using multiple regression-based algorithms. Results indicate that cooperation, optimism, sense of belonging, and students’ energy levels are significant predictors of sociability. Among the models evaluated, Support Vector Regression and Lasso Regression demonstrated the strongest predictive performance, exhibiting the lowest error rates and highest explained variance. These findings highlight the close relationship between social and emotional skills and student sociability and underscore the importance of educational policies that support students’ social engagement and emotional development. Future research may extend this work by examining how social and emotional skills relate to academic outcomes.
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