Constructing a predictive model of negative academic emotions in high school students based on machine learning methods

Negative academic emotions reflect the negative experiences that learners encounter during the learning process. This study aims to explore the effectiveness of machine learning algorithms in predicting high school students’ negative academic emotions and analyze the factors influencing these emotio...

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Veröffentlicht in:	Scientific reports Jg. 15; H. 1; S. 19183 - 11
Hauptverfasser:	Ma, Shumeng, Jia, Ning, Wei, Xiuchao, Zhang, Wanyi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 01.06.2025 Nature Publishing Group Nature Portfolio
Schlagworte:	631/477 631/477/2811 Academic Performance - psychology Adolescent Adolescents China Decision trees Emotions Female High school students Humanities and Social Sciences Humans Learning Learning algorithms Logistic Models Machine learning Machine learning algorithms Male multidisciplinary Negative academic emotions Negativism Prediction Prediction models Predictive Learning Models - standards Predictive Learning Models - statistics & numerical data Psychological Tests Random Forest Regression analysis Reproducibility of Results Resilience, Psychological Science Science (multidisciplinary) Secondary school students Secondary schools Self Efficacy Students Students - psychology System theory Systems Theory China Machine learning algorithms High school students Negative academic emotions Prediction
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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