The Extension of Attachment Theory into School Contexts and Adolescent’s Social and Emotion Skills Development A Regional Comparative Study

Description

This dataset contains the analytical materials supporting the study titled “Predictors of Adolescents’ Social and Emotional Skills: A Cross-Cultural Analysis Using Machine Learning and SHAP Interpretation.” The study used data from the OECD 2023 Survey on Social and Emotional Skills (SSES) to examine the key predictors of social and emotional skills among adolescents from different cultural contexts. The materials include data processing procedures, machine learning analysis codes, model development scripts, and SHAP-based interpretation procedures used in the study. The analysis involved comparisons of five machine learning algorithms, including XGBoost, Random Forest, LightGBM, CatBoost, and Linear Regression, with CatBoost selected as the optimal predictive model. SHAP analysis was conducted to evaluate feature importance and explore nonlinear relationships between predictors and students’ social and emotional skills. The original OECD SSES 2023 student-level dataset is not included in this repository due to OECD data access and redistribution restrictions. Researchers interested in reproducing the analyses should obtain the original dataset directly from the OECD following the relevant data access procedures. The materials provided here facilitate transparency, reproducibility, and further research on adolescent social and emotional development using interpretable machine learning approaches.

Institutions

• Wuhan Sports University

  Hubei, Wuhan

Categories

Licence