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Using Machine Learning to Predict UK and Japanese Secondary Students' Life Satisfaction in PISA 2018
Peer reviewed
Direct linkZexuan Pan; Maria Cutumisu – British Journal of Educational Psychology, 2024
Background: Life satisfaction is a key component of students' subjective well-being due to its impact on academic achievement and lifelong health. Although previous studies have investigated life satisfaction through different lenses, few of them employed machine learning (ML) approaches. Objective: Using ML algorithms, the current study predicts…
Descriptors: Artificial Intelligence, Secondary School Students, Life Satisfaction, Foreign Countries
Download full textChung Hyewon; Kim, Jung-In; Jung, Eunjin; Park, Soyoung – International Journal of Educational Psychology, 2022
The Program for International Student Assessment (PISA) aims to provide comparative data on 15-year-olds' academic performance and well-being. The purpose of the current study is to explore and compare the variables that predict the reading literacy and life satisfaction of U.S. and South Korean students. The random forest algorithm, which is a…
Descriptors: Comparative Education, Predictor Variables, Literacy, Life Satisfaction
