SMART TeachLink: A Tutoring System for Primary School

Primary school students today are exposed to digital technologies at an early age, often leading to both opportunities for learning and risks of developing negative digital habits. Traditional classroom instruction struggles to balance engagement with discipline, while teachers face increasing workloads in monitoring student progress. This study introduces SMART TeachLink, a web-based tutoring system designed to guide young learners toward responsible and educational use of technology. The system integrates interactive lessons, automated assessments, and a reward mechanism to motivate learners across core subjects such as Math, English, Filipino, Science, Araling Panlipunan, and MAPEH. Using a developmental research design and Agile methodology, SMART TeachLink was developed with PHP, HTML, CSS, JavaScript, and MySQL to ensure accessibility across devices. Results show that the system effectively identifies learning difficulties, reduces teacher workload through automated tracking, and promotes positive study habits among students. SMART TeachLink demonstrates that technology can be harnessed not only as a tool for entertainment but as a structured platform for academic growth and responsible digital behavior.

Tutoring System; Primary Education; Interactive Learning; Digital Habits; Academic Performance; Web-Based Learning.

1. Abad, J. M., & Cruz, L. R. (2024). Gamification in Philippine Classrooms: Enhancing Student Engagement through Digital Platforms. Philippine Journal of Educational Technology, 18(1), 55–72. [Google Scholar] [Crossref]

2. Caballero, R. A., & Villanueva, P. S. (2023). AI-Driven Learning Management Systems: Opportunities and Challenges in Southeast Asia. Asian Journal of Education and Innovation, 12(3), 201–219. [Google Scholar] [Crossref]

3. Dela Peña, M., & Santos, K. (2025). Automated Scheduling and Academic Tracking in K-12 Education. International Journal of Smart Education Systems, 7(2), 89–104. [Google Scholar] [Crossref]

4. Garcia, A. J., & Lee, H. (2022). Interactive Dashboards for Student Performance Monitoring: A Comparative Study. Computers & Education, 185, 104–118. [Google Scholar] [Crossref]

5. UNESCO. (2023). Global Education Monitoring Report: Technology in Education – A Tool on Whose Terms? UNESCO Publishing. [Google Scholar] [Crossref]

6. Velasco, R. T., & Mendoza, C. F. (2025). Integrating AI-Assisted Quizzes in Mathematics Learning: Effects on Student Motivation. Journal of Digital Pedagogy, 9(4), 145–162. [Google Scholar] [Crossref]

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