The Effects of Basic Aid to the Student Grading and Progress Monitoring System for the Basic Education at St. Clare College of Caloocan
Authors
Computer Science Department, St. Clare College of Caloocan (Philippines)
Computer Science Department, St. Clare College of Caloocan (Philippines)
Computer Science Department, St. Clare College of Caloocan (Philippines)
Computer Science Department, St. Clare College of Caloocan (Philippines)
Computer Science Department, St. Clare College of Caloocan (Philippines)
Computer Science Department, St. Clare College of Caloocan (Philippines)
Computer Science Department, St. Clare College of Caloocan (Philippines)
Computer Science Department, St. Clare College of Caloocan (Philippines)
Article Information
DOI: 10.51584/IJRIAS.2026.11060156
Subject Category: Computer Science
Volume/Issue: 11/6 | Page No: 2075-2079
Publication Timeline
Submitted: 2026-05-30
Accepted: 2026-06-19
Published: 2026-07-04
Abstract
The rapid advancement of technology has transformed the way educational institutions manage academic information and monitor student performance. Traditional methods of recording grades and tracking student progress often involve manual processes that can be time-consuming, prone to errors, and difficult for stakeholders to access. To address these challenges, St. Clare College of Caloocan implemented the Basic Aid Digital System, a web-based platform designed to support grading, attendance monitoring, and academic progress tracking. This study aimed to determine the effectiveness of the system in improving the management of student records and enhancing communication among teachers, students, and parents.
A quantitative correlational research design was employed in the study. Data were collected from 80 student respondents, 10 teachers, and parents or guardians of elementary learners through pre-survey and post-survey questionnaires. Statistical tools such as weighted mean, standard deviation, and Pearson correlation coefficient were utilized to analyze the gathered data. The findings revealed that the implementation of the Basic Aid Digital System contributed to improved efficiency in grading, easier access to academic records, and greater transparency in monitoring student performance. Results also showed a high level of satisfaction among users, particularly in terms of convenience, accessibility, and reliability. Furthermore, the statistical analysis indicated a strong positive relationship between the use of the system and the effectiveness of student grading and progress monitoring.
Based on the findings, the study concludes that the Basic Aid Digital System serves as a practical and reliable tool for academic management. Its implementation supports more efficient monitoring of student performance and strengthens collaboration among teachers, students, and parents
Keywords
Basic Aid Digital System, Student Grading, Progress Monitoring, Educational Technology, Academic Management, Digital Records
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References
1. Alruwais, N., Wills, G., & Wald, M. (2020). Advantages and challenges of automated grading systems in education. International Journal of Advanced Computer Science and Applications, 11(2), 45–53. [Google Scholar] [Crossref]
2. Anderson, P., Williams, R., & Thomas, J. (2023). Data-driven decision-making in educational institutions through learning analytics. Educational Technology Research and Development, 71(1), 120–135. [Google Scholar] [Crossref]
3. Bai, X., Zhang, Y., & Li, H. (2021). Artificial intelligence-assisted grading systems and academic assessment. Computers and Education, 168, 104–118. [Google Scholar] [Crossref]
4. Johnson, M., Smith, A., & Brown, K. (2021). Digital grading platforms and academic efficiency in higher education. Journal of Educational Technology Systems, 49(3), 289–304. [Google Scholar] [Crossref]
5. Kim, S., Park, J., & Lee, H. (2020). Cloud-based student information systems for educational management. International Journal of Educational Management, 34(5), 802–817. [Google Scholar] [Crossref]
6. Martinez, L., Gomez, R., & Cruz, P. (2022). Web-based academic monitoring systems and student performance tracking. Journal of Learning Analytics, 9(2), 55–72. [Google Scholar] [Crossref]
7. Morales, A., Santos, M., & Reyes, J. (2023). Challenges in implementing educational technologies in developing countries. Philippine Journal of Information Technology, 15(1), 21–36. [Google Scholar] [Crossref]
8. Nguyen, T., Pham, D., & Tran, H. (2022). Learning analytics and early intervention systems for student success. Educational Data Science Review, 6(1), 33–49. [Google Scholar] [Crossref]
9. Torres, R., Dela Cruz, J., & Mendoza, P. (2021). Factors affecting the adoption of school information systems in Philippine educational institutions. Asia Pacific Journal of Education, 41(4), 612–628 [Google Scholar] [Crossref]
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