SIGLA (Strategic Intervention Guided by Learning Analytics): From Learning Data to Learning Gains through a Data-Informed Intervention in Araling Panlipunan
This study determined the effectiveness of SIGLA (Strategic Intervention Guided by Learning Analytics): From Learning Data to Learning Gains through a Data-Informed Intervention in Araling Panlipunan. The study was conducted in response to the need to address learning gaps and improve learners' mastery of Araling Panlipunan competencies through the use of assessment data and targeted instructional interventions. Specifically, it examined the learners' performance before and after the implementation of the SIGLA intervention and determined whether a significant difference existed between their pretest and posttest scores. A one-group pretest-posttest pre-experimental research design was employed involving eighteen (18) Grade 5 learners of Malagab-i Elementary School during the School Year 2026-2027. A validated 40-item achievement test based on the Most Essential Learning Competencies (MELCs) in Araling Panlipunan was utilized as the research instrument. Data were analyzed using mean, Mean Percentage Score (MPS), and paired-samples t-test. Results revealed that learners obtained a pretest mean score of 20.10 with an MPS of 52.64%, indicating low mastery of the competencies. Following the implementation of SIGLA, the posttest mean score increased to 32.80 with an MPS of 81.94%, demonstrating improved performance and mastery. The paired samples t-test showed a statistically significant difference between the pretest and posttest scores (t = -9.79, p < .001). Moreover, the computed effect size (Cohen's d = 2.31) indicated a very large effect of the intervention. The findings suggest that SIGLA was effective in addressing learning gaps and enhancing learners' academic performance in Araling Panlipunan. The study highlights the value of learning analytics and data-informed instructional interventions in promoting improved learning outcomes and learner achievement.
Authors
- Reynalyn Inocencio
Institutions
- Universidad de Málaga (ES)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-13
- DOI
- https://doi.org/10.5281/zenodo.23330718
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00