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Analysis of Factors Affecting Academic Performance of Mathematics Education Doctoral Students: A Structural Equation Modeling Approach.
Wijaya, Tommy Tanu; Yu, Boran; Xu, Fei; Yuan, Zhiqiang; Mailizar, Mailizar.
Afiliación
  • Wijaya TT; School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China.
  • Yu B; School of Mathematical Sciences, Beijing Normal University, Beijing 100875, China.
  • Xu F; Teachers College, Columbia University, New York, NY 10027, USA.
  • Yuan Z; School of Mathematics and Statistics, Hunan Normal University, Changsha 410081, China.
  • Mailizar M; Mathematics Education Department, Universitas Syiah Kuala, Banda Aceh 23111, Indonesia.
Article en En | MEDLINE | ID: mdl-36901528
ABSTRACT
Student academic performance is an important indicator of doctoral education quality, but limited research has focused on how multiple influential factors of doctoral students' academic performance work together. This study aims to explore the factors significantly affecting the academic performance of mathematics education doctoral students in Indonesia. Several factors were recognized from prior studies, such as the fear of delay, student engagement, parental support, teacher support, facilitating conditions, stress level, and well-being. An online questionnaire was designed and answered by a total of 147 mathematics education doctoral students. The partial least squares structural equation modeling (PLS-SEM) approach was adopted to analyze the questionnaire data. The results suggested that teacher support had the strongest positive effects on mathematics education doctoral students' academic performance in Indonesia. Student engagement was the most significant positive factor in improving doctoral students' well-being, while parental support could most significantly reduce their stress levels. Practically, these results are expected to provide implications to universities and supervisors regarding the improvement of doctoral students' well-being to promote their academic success and further the quality of doctoral programs in education. Theoretically, these results can also contribute to building an empirical model that can be used to explore and explain how multiple factors could affect doctoral students' academic performance in other contexts.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Rendimiento Académico / Éxito Académico Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Int J Environ Res Public Health Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Rendimiento Académico / Éxito Académico Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Int J Environ Res Public Health Año: 2023 Tipo del documento: Article País de afiliación: China