The Logistics Factors that Affect the Academic Achievement of Elementary School Students in the Kingdom of Saudi Arabia (Applied Statistical Study)
DOI:
https://doi.org/10.48165/gjs.2025.2107Keywords:
Exploratory factor, analysis, Discriminant analysis Logistical factors, Academic achievementAbstract
This study aimed to examine the impact of logistical services on the academic achievement of primary school students using Exploratory Factor Analysis (EFA) and Stepwise Discriminant Analysis (DA). The EFA revealed five factors that explained 64.1% of the total variance: School Environment, Distance Between School and Home, Logistics Factors 1, Level of Education According to School Location, and Logistics Factors 2. These factors were extracted based on eigenvalues greater than 1 and were rotated using the Varimax method. Subsequently, four of these components were sequentially entered into the discriminant model through stepwise analysis: Level of Education According to School Location, Logistics Factors 1, Logistics Factors 2, and School Environment. Results indicated that Level of Education by Location was the most significant discriminator (Wilks’ Lambda = .338, F = 3420.828, p < .001), followed by logistical and environmental factors. The final model achieved a Wilks’ Lambda of .203. The standardized canonical discriminant function coefficients showed that the Level of Education According to School Location had the most decisive influence on the first discriminant function (1.055). As results indicate: • School location significantly impacts academic achievement, whether a school is located in an urban or rural area. • Improving logistical services, such as school transportation and delivering the textbook early, as the delay of these factors affects student achievement negatively. • Attention to the school environment, including lighting, ventilation, and recreational facilities, positively affects students' academic achievement. • The study recommends conducting future studies to investigate the remaining variables using alternative statistical methods.
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