Artificial Intelligince Literacy and Research Competence of Senior High School Student in SDO Calaca City

Abstract

This study examined the relationship between artificial intelligence (AI) literacy and research competence among Senior High School students in the Schools Division of Calaca City during the school year 2025–2026. It assessed students’ AI literacy in terms of access, knowledge and understanding, usage and application, and evaluation, as well as their research competence in terms of problem identification and conceptualization, information literacy and synthesis, and research design and application. The study also identified teacher-reported challenges in promoting these competencies and proposed an instructional intervention based on the findings.

Using a descriptive-quantitative research design, data were gathered from 350 Senior High School students selected through stratified random sampling. Structured four-point Likert scale questionnaires were used to measure AI literacy, research competence, and teacher-related challenges, while selected teacher responses provided contextual support for the quantitative findings. Data were analyzed using descriptive statistics and Pearson product-moment correlation.

Results revealed that students were slightly literate in AI, with evaluation emerging as the weakest dimension, indicating limited ability to assess the accuracy, reliability, and ethical implications of AI-generated outputs. Students were also slightly competent in research, with citation and referencing identified as the weakest area. Pearson correlation analysis showed a strong, statistically significant positive relationship between AI literacy and research competence, r = .705, p < .001. Teacher-reported challenges included limited institutional policy support for AI use, technological constraints, reduced opportunities for meaningful teacher-student interaction, and heavy workloads that limited sustained research mentoring.

Based on these findings, the study proposed the AI-Augmented Research Toolkit (AART), a structured instructional material designed to support ethical and research-oriented AI integration. The toolkit adopts a Human–AI–Human workflow that emphasizes critical evaluation, source verification, synthesis, citation checking, and responsible use of AI-generated content. The study recommends the development of clear institutional AI policies and targeted professional development programs to strengthen students’ and teachers’ evaluative, ethical, and research-related competencies.