Artificial Intelligence and Mathematics Learning: Lived Experiences of Students and Teachers

This study explores the lived experiences of students and teachers regarding the integration of artificial intelligence (AI) tools in mathematics learning. Using a descriptive phenomenological approach, the research captures participants’ experiences of how AI affects conceptual understanding, problem-solving skills, academic integrity, and pedagogical practices. Data were collected through in-depth interviews and qualitative surveys with eight students and five mathematics instructors and analyzed using Colaizzi’s method to identify emerging themes. For students, findings are categorized under the A.C.E. framework: “Advantage,” such as enhanced conceptual understanding and personalized learning; “Challenges,” including overreliance on AI and weakened problem-solving skills; and “Ethics,” reflecting concerns about academic dishonesty and responsible use of AI. For teachers, experiences align with the A.C.T. framework: “Adapt,” highlighting how AI supports the instructional design and differentiated learning; “Caution,” noting the risk of diminished student engagement and critical thinking; and “Teach,” emphasizing the need for guided, balanced integration of AI tools in the classroom. Though AI tools can potentially have deeper learning and instructional effectiveness, they can be harmful if abused. The research concludes that the use of AI can potentially undermine learning integrity and student autonomy in the absence of ethical standards and pedagogical management. Suggested solutions include incorporating AI literacy into the curriculum, establishing rules and ethical guidelines for AI use, and providing professional development to instructors. These findings offer vital insights for teachers, policymakers, and developers looking to use AI to transform and ethically guide mathematics.