The Senegalese secondary school system is a critical component of the country's education infrastructure, aiming to provide quality learning outcomes for students. However, there remains uncertainty about the effectiveness and efficiency of this educational structure in achieving its goals. The research employs a multilevel regression model to analyse data collected from secondary schools across Senegal. The model will incorporate both school-level (e. g. , teacher qualifications, infrastructure) and student-level (e. g. , socioeconomic status, attendance patterns) variables. Robust standard errors will be used for inference. The analysis reveals a significant impact of teacher qualifications on academic performance, with teachers having higher levels of education leading to better outcomes among students. Dropout rates are also influenced by a lack of access to healthcare facilities and transportation issues. This study provides valuable insights into the effectiveness of Senegalese secondary schools in achieving educational goals. The multilevel regression model offers a nuanced understanding of factors affecting clinical outcomes, which can inform policy decisions aimed at system improvement. To enhance student health and academic performance, it is recommended that the government invests in improving school infrastructure, particularly healthcare facilities, and addresses transportation challenges to ensure students have access to educational resources. Senegal, secondary schools, multilevel regression analysis, clinical outcomes, education policy The empirical specification follows Y=₀+^ X+, and inference is reported with uncertainty-aware statistical criteria.
Gaye et al. (Fri,) studied this question.
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