Siusin, Suharti and Shaharudin, Shazlyn Milleana and Mohamed, Nur Syarafina and Musirin, Ismail (2023) Classifying students’ academic performance using principal component analysis during pandemic COVID-19. In: 6th World Conference on Smart Trends in Systems, Security and Sustainability, WS4 2022, 24 August 2022 - 27 August 2022, London, England.
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Official URL: http://dx.doi.org/10.1007/978-981-19-7660-5_15
Abstract
As a result of the COVID-19 outbreak in Malaysia, educational institutions, including universities, were forced to conduct all academic activities online. If online learning continues in subsequent academic sessions, it may have a big impact on the academic performance of the student. Thus, the purpose of this study is to classify student’s academic performance by using principal component analysis (PCA) before and during pandemic COVID-19. The sample consisted of 234 undergraduates from the Department of Mathematics at the Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris (UPSI). Data collection is conducted using a questionnaire. Data were gathered from students’ grades for each subject in the first semester of the session 2019/2020, which is during face-to-face learning, and each subject’s grade in the second semester of the session 2019/2020, which is during online learning. The finding of the study was divided into two parts which are preliminary analysis and further analysis. According to the eigenvalues greater than one criteria (Kaisar, 1960), when using the correlation matrix in eigen analysis, only, values greater than one should be included in the analysis. As a result, the researcher decided to cut-off the dimension at the second dimension from the eigenvalues obtained by the R software because the eigenvalues for the second dimension were greater than one which is 1.111. For further analysis, the researcher will be using the principal component one in classifying students based on their overall academic achievement, and principal component two will be used in classifying in which semester they did best in. With regard to overall academic performance, the majority of students’ 51.4% were in the classification of good performance, while just 24.3% were considered excellent performance. Further, 15.7% of students are categorized as performing averagely in their academic performance, whereas 8.6% are categorized as performing below average. The results indicate that 65.7% of students performed similarly in both semesters, indicating that most students are performing in their academic performance either before or during the pandemic COVID-19, while only 14.3% of students performed in semester 1 session 2019/2020, which is during face-to-face learning, and only, 20% of students performed in semester 2 session 2019/2020, which is during online learning.
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | academic performance, classification, online learning, principal component analysis |
Subjects: | Q Science > QA Mathematics |
Divisions: | Science |
ID Code: | 108289 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 22 Oct 2024 07:52 |
Last Modified: | 22 Oct 2024 07:52 |
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