Aldrin G. Donasco and Regina P. Galigao (Authors)
This study explores the impact of sleep quality on student academic performance through a cross-cultural lens, employing data mining techniques to analyze the complex relationships between sleep patterns and academic success. Previous research has demonstrated the negative effects of poor sleep on cognitive function, memory, and academic. However, the role of cultural norms, lifestyle factors such as stress, diet, and screen time in shaping sleep behaviors remains underexplored. Using data mining methods, this research analyzes large datasets collected from students across diverse cultural backgrounds to identify key factors influencing sleep quality and their subsequent impact on academic performance. The findings reveal those cultural attitudes toward sleep, stress levels, and lifestyle factors such as high screen time and poor diet significantly affect sleep quality, which in turn impacts academic outcomes. This study highlights the necessity of culturally tailored interventions to improve sleep hygiene and promote healthier habits. By applying data mining techniques to uncover patterns and correlations, this research contributes to a deeper understanding of how sleep quality varies across cultures and its implications for student success, providing a foundation for more effective, data-driven interventions to enhance student well-being globally.
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Keywords: Sleep quality, Academic performance, Data mining, Stress, Cultural context, Student well-being