Artificial Intelligence in Undergraduate Mathematics Education: Student Perspectives on Learning, Academic Achievement, and Math Anxiety

Abstract

Artificial intelligence (AI) has become increasingly integrated into education, particularly through generative AI tools that provide academic support, personalized feedback, and problem-solving assistance. While prior research has examined AI’s impact on student performance, motivation, and engagement, researchers have given less attention to students’ perceptions of AI and how these perceptions relate to learning experiences, academic success, and math-related anxiety. This study aims to investigate undergraduate students’ perceptions of AI use in mathematics courses and explores relationships between perceived impact, academic success, and anxiety. Data will be collected using an anonymous online questionnaire distributed to Carroll College students who have completed a mathematics course. The survey includes structured and open-ended items to assess students’ AI usage patterns and perceived effects on learning, achievement, and anxiety. Quantitative data will be analyzed using descriptive and correlational methods, while open-ended responses will undergo thematic analysis to identify recurring themes and patterns. Findings aim to provide insight into how students experience and interact with AI in mathematics education. Understanding these dynamics may inform ethical, responsible implementation practices that support independent thinking and long-term academic development.