Smart eLearning: A framework development of a web portal for data-driven assessment and module recommendation for senior high school students using backtracking algorithm
Ma. Glaizel R. Gajardo & Francis F. Balahadia
Abstract
The study reviewed challenges in student performance in the Philippines, particularly in reading, mathematics, and science, as reflected in international assessments such as PISA and the 2024 National Achievement Test (NAT). Despite various efforts, Filipino students continue to underperform in these core subjects, highlighting the need for more targeted and personalized learning interventions. Existing assessment methods often fail to accurately identify specific learning gaps, making it difficult to provide timely and appropriate academic support. In response, the proponents introduced the SMART eLearning framework a conceptual web-based model designed to enhance instruction through data-driven assessments and customized learning materials. It integrates diagnostic and achievement tests with a backtracking algorithm a method that systematically traces a student’s incorrect answers to uncover underlying concepts they struggle with. Based on these results, the system recommends focused modules or exercises to help students improve in those specific areas. This approach aims to help senior high school students master essential competencies required for national standardized tests and college entrance exams. The framework promotes an adaptive learning environment using ICT tools such as automated quizzes, performance dashboards, and real-time progress tracking that provide immediate feedback to both learners and educators. It will guide system development through a developmental and descriptive research design, applying Agile principles to enable continuous refinement through classroom testing and user input. Ultimately, the SMART eLearning framework seeks to improve academic performance, reduce failure rates, and better prepare students for higher education and future careers, addressing persistent challenges in the Philippine education system.
Keywords
learning materials recommendation, backtracking algorithm, diagnostic analytics, data-driven assessment, educational quality
Author information & Contribution
Ma. Glaizel R. Gajardo. Corresponding author. Bachelor of Science in Computer Science, Student, State Polytechnic University (Siniloan) Host Campus. Email: maglaizel.gajardo@lspu.edu.ph
Francis F. Balahadia. Doctor in Information Technology. Faculty, Laguna State Polytechnic University (Siniloan) Host Campus. Email: francis.balahadia@lspu.edu.ph
"All authors contributed equally to the conception, design, preparation, data gathering and analysis, and manuscript writing. All authors read and approved the final manuscript."
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
This work was not supported by any funding.
Institutional Review Board Statement
Not Applicable
AI Declaration
The author declares the use of Artificial Intelligence (AI) in writing this paper. In particular, the author used ChatGpt in checking and refining the grammar. The author takes full responsibility in ensuring proper review and editing of content generated using AI.
Notes
Acknowledgement
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Cite this article:
Gajardo, M.R. & Balahadia, F.F. (2025). Smart eLearning: A framework development of a web portal for data-driven assessment and module recommendation for senior high school students using backtracking algorithm. International Journal of Science, Technology, Engineering and Mathematics, 5(3), 22-39. https://doi.org/10.53378/ijstem.353233
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