Predicting student satisfaction in career choices using machine learning: a case study

Abstract Student satisfaction plays a crucial role in successful educational and career decision-making. This study investigates how artificial intelligence, specifically Support Vector Machine (SVM) models, can be used to predict student satisfaction with university choices by considering socio-eco...

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Autores principales:	Mohamed Oubraime, Ahmed M’Hamdi, Abderrahim Sabour
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Springer 2026-03-01
Colección:	Discover Education
Materias:	School and career guidance Career satisfaction Machine Learning (ML) Support Vector Machine (SVM)
Acceso en línea:	https://doi.org/10.1007/s44217-026-01337-9
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