The effects of part-time work on the students' academic performance during COVID-19 pandemic: a logistic regression analysis / Siti Nurhafizah Mohd Shafie ...[et al.]

• Main Authors: Mohd Shafie, Siti Nurhafizah (Author), Nafi, Mohd Noor Azam (Author), Ab. Aziz, Nasuhar (Author), Deen Bakry, Nur Deana Aqila (Author), Mohamad, Nurul Anis Hafiza (Author), Haslubis, Siti Nor Faqihah (Author), Amran, Azzah (Author)
• Format: Book
• Published: Unit Penerbitan UiTM Kelantan, 2021-12.
• Subjects: Article; PeerReviewed
• Online Access: Link Metadata
• Notes: https://ir.uitm.edu.my/id/eprint/56399/1/56399.pdf
• Keywords: Statistical data; Regression analysis. Correlation analysis. Spatial analysis (Statistics)

In early 2020, the COVID-19 pandemic has caused Malaysia to face serious challenges in various sectors, including the education sector. This pandemic has also caused major concerns among students in Higher Education (HE). They are facing problems in academic performance and financial stress regarding their university enrolment. It can be seen that in Malaysia, 76 percent of the students acquire financial resources from full-time jobs, part-time jobs, scholarships, and study loans. Therefore, this study emphasized the effects of part-time work on the academic performance among full-time students. This research mainly focuses on students in Universiti Teknologi MARA (UiTM), Kota Bharu, Kelantan. By using stratified random sampling technique, an online survey with self-administered questionnaire consisting of five sections was distributed to 113 undergraduate students as a sample. A logistic regression approach is used to investigate the relationship between gender, number of working hours, skills, learning time, social time, and social networking sites towards academic performance. Hence, social time and social networking sites are the only variables that significantly contribute to the predictive ability of the model.