Abstract
This study examined the extent of the impact of artificial intelligence (AI) applications on mathematics learning among STEM students of Grade 11 Senior High School at Mindanao State University-Sulu. A descriptive-correlational research design was employed, involving 100 student-respondents selected through purposive sampling. The study assessed the impact of AI applications in four dimensions: accessibility and usage, conceptual understanding, problem-solving skills, and motivation and engagement. It also considered demographic factors such as gender, age, parents’ educational attainment, and parents’ average monthly income. Findings revealed that the majority of respondents were female, aged 17 years old and below, and had parents who were college graduates or held post-graduate degrees. Additionally, half of the students belonged to low-income families. Students generally agreed that AI tools were accessible and useful for mathematics learning. However, they only partially agreed with AI’s impact on conceptual understanding, problem-solving skills, and motivation and engagement, indicating that while AI-supported learning, it was not fully relied upon as a primary educational tool. No significant differences were found in the impact of AI applications on mathematics learning when data were grouped by gender, age, and parents’ average monthly income. However, a significant difference was found in accessibility and usage based on parents’ educational attainment, suggesting that students with more educated parents had better access to AI tools for learning. Furthermore, significant positive correlations were found among all subcategories of AI’s impact, particularly between problem-solving skills and motivation and engagement. The study recommends that school administrators, curriculum developers, and policymakers implement structured AI integration in mathematics education, ensuring equitable access to AI-powered tools. Teachers may incorporate AI-enhanced strategies to improve problem-solving and motivation, while students are encouraged to use AI as a supplementary resource alongside traditional learning methods. Future researcher may explore the effectiveness of AI-driven interventions in improving mathematical learning outcomes.