The relationship between study-life balance and academic performance in higher education - Cheoh, Wen Hui; Kasturi, Manikam; Ng, Siao Wei; Yew, Fang Yan (2024)
This study delves into the complex interplay between study-life balance factors and academic performance among higher education students. The primary objective is to investigate the impact of study hours, workload, and social support on academic achievement within the context of higher education. By examining these variables, the study aims to contribute to the existing knowledge regarding the factors that influence students' academic success. A quantitative research approach was employed to achieve this objective. The study utilized statistical tools such as Pearson Correlation Coefficient and Multiple Regression Analysis to analyse the relationships between study hours, social support, workloads, and academic performance. The research involved a sample of higher education students, and data collection was conducted through structured questionnaires. The collected data were then analysed using SPSS software, allowing for a comprehensive examination of the variables under study. The findings of this study revealed significant correlations between study hours, workload, social support, and academic performance among higher education students. Notably, study hours emerged as a significant predictor of academic success, followed by social support and workloads. These results shed light on the critical role of effective time management, workload management strategies, and social support systems in enhancing student performance in higher education settings. In conclusion, this study contributes valuable insights into the factors influencing academic performance among higher education students. The findings underscore the importance of promoting study-life balance through strategies that optimize study hours, manage workloads effectively, and provide adequate social support to students. Furthermore, future research directions may include exploring additional variables and employing mixed methods approaches to gain a more nuanced understanding of study-life balance dynamics and their implications for academic outcomes