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Published

2024-02-18

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Vol. 9 No. 5 (2024)

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Research Articles

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How to Cite

Inoferio, H. V., Espartero, M., Asiri, M., Damin, M., & Chavez, J. V. (2024). Coping with math anxiety and lack of confidence through AI-assisted Learning. Environment and Social Psychology, 9(5). https://doi.org/10.54517/esp.v9i5.2228

Coping with math anxiety and lack of confidence through AI-assisted Learning

Hermie V. Inoferio

College of Education, Jose Rizal Memorial State University-Katipunan Campus

Marcelino Espartero

College of Science and Mathematics, Western Mindanao State University

Masnona Asiri

School of Graduate Studies, Sulu State College

Michelle Damin

Integrated Laboratory School, Western Mindanao State University

Jason V. Chavez

Research Operations Office, Zamboanga Peninsula Polytechnic State University


DOI: https://doi.org/10.54517/esp.v9i5.2228


Keywords: artificial intelligence, coping mechanism, learning difficulties, lack of confidence, math anxiety

Abstract

Artificial intelligence (AI) in education transforms the instructional processes and learning competence of students. AI can adapt to the individual learning needs of students. By analyzing students’ progress, performance, and preferences, AI systems can deliver tailored content, recommend additional resources, and provide feedback. The purpose of this study was to develop initial understanding on how AI models help students cope with math anxiety and lack of confidence in engaging with mathematics learning. This exploratory research established the connections between what students feel when using AI and how it benefits them. College students (n = 20) enrolled in different math-related programs (i.e., engineering, statistics/mathematics, computer science, education) were purposively sampled for a one-on-one interview. Thematic analysis indicated that students are now turning to AI models as a coping mechanism to alleviate math anxiety and boost their self-assurance. These AI models function as “mentors” and “math companions” that offer step-by-step explanations and personalized support. Their adaptability and personalized approach make mathematics more accessible to students, with the potential to reduce anxiety and enhance the overall learning experience. Moreover, the use of AI models encourages a sense of independence, motivating students to actively engage in self-guided learning. The findings open new questions about using AI models in improving the self-efficacy and confidence of students in mathematics learning. There is also an opportunity to build an AI-assisted learning with a focus on psychological interventions and behavioral interconnections mediating students’ academic performance.

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