Students’ Engagement with Artificial Intelligence, Metacognitive Reading Strategies, and Academic Achievement: A Correlational Study of Grade 12 STEM Learners in Valencia, Bukidnon

The rapid adoption of artificial intelligence (AI) in education raises questions about how AI use interacts with students’ metacognitive reading strategies and academic performance. This descriptive-correlational study examined relationships among engagement with AI tools (EAIT), metacognitive awareness of reading strategies (MARS), and academic achievement (AA) for 155 Grade 12 STEM students at Valencia National High School, Valencia, Bukidnon. Respondents completed validated survey instruments; data were analyzed using descriptive statistics, Pearson correlation, and multiple regression. Results indicated high EAIT (M = 3.65) and MARS (M = 4.24) levels, with outstanding AA (M = 94, SD = 1.77). Correlational analysis showed a significant positive relationship between EAIT and MARS (r = .322, p = .001) and between MARS and AA (r = .233, p = .003), whereas EAIT and AA were not significantly correlated (r = −.115, p = .152). Regression results revealed that behavioral engagement with AI negatively predicted academic achievement (B = –0.494, p = 0.017), whereas awareness of global reading strategies positively predicted achievement (B = 0.782, p = 0.002); the model accounted for 8.0% of the variance (R² = 0.080, F = 6.616, p = 0.002). These findings highlight the predictive relevance of how students engage with AI and apply metacognitive reading strategies to academic achievement, with higher behavioral AI engagement associated with lower predicted achievement and higher global reading-strategy awareness with higher predicted achievement. Educators should scaffold strategic, self-regulated use of AI in reading instruction to promote goal-setting, monitoring, and evaluation to support comprehension and academic outcomes.