Characteristics of and Causal Factors Related to Academically Resilient Students: A Study Based on PISA 2018 Data

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Abstract

This study utilizes PISA 2018 data to explore the factors that influence the academic resilience of our disadvantaged students. Key features were identified through the Boruta algorithm while XGBoost predicted students' resilience in reading, math, and science.The Shapley Additive Explanations framework explained the degree of influence of the important features. Results showed five common features among the top ten characteristics in the three disciplines, including meaning in life, classroom disciplinary climate, perception of cooperation at school, expected career status, and fear of failure. On other characteristics, the three disciplinary resilience domains differed in their performance. This study provides new insights into the field of academic resilience and emphasizes the importance of fostering academic resilience among Chinese students.

Author

• Wenbei Li, Beijing Normal University