Artificial Intelligence Literacy and Students' Science Engagement: A Correlational Study Among Senior High School Students

Students today are increasingly exposed to artificial intelligence technologies that shape how they learn and engage with academic subjects. This study primarily aimed to examine the relationship between artificial intelligence literacy and science engagement among senior high school students in a public secondary school in the Philippines during the Academic Year 2025–2026. A descriptive-correlational research design was employed, utilizing simple random sampling to select 120 respondents. Data were collected using adapted and validated instruments: the Artificial Intelligence Literacy Scale for Chinese College Students and the Students' Science Engagement Scale. Descriptive statistics, Pearson correlation, and regression analysis were used to analyze the data. Findings revealed that students demonstrated a high level of AI literacy (M=3.54), with ethics as the highest dimension and awareness as the lowest. Students exhibited a very high level of science engagement (M=3.51), particularly in science effort and preparation. A significant positive correlation was found between AI literacy and science engagement (r=0.987, p<.001), though this strong association warrants caution regarding potential common method bias given the self-reported nature of both measures. Regression analysis further revealed that evaluation (β=0.6172, p<.001) and ethics (β=0.5374, p<.001) significantly predicted science engagement, while awareness and usage did not. The high explanatory power of the model (R²=0.977) suggests considerable conceptual overlap between the two constructs, indicating that AI literacy and science engagement may be closely intertwined rather than distinct. It was concluded that higher-order AI literacy competencies—critical evaluation and ethical reasoning—substantially influence students' engagement in science learning. It was recommended that science teachers integrate AI literacy into their instruction by designing activities that develop students' critical evaluation skills and ethical awareness when using AI tools, while future research should examine the distinctiveness of these constructs using objective measures.