Exploring the interplay between AI and human logic in mathematical problem-solving

Shanzhen Gao(Virginia State University), Weizheng Gao(Virginia State University), Olumide Malomo(Virginia State University), Julian D. Allagan(Elizabeth City State University), Ephrem Eyob(Virginia State University), Chandrasheker Challa(Virginia State University), Jianning Su(Georgia State University)
Online Journal of Applied Knowledge Management
December 1, 2024
Cited by 7Open Access
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Abstract

This paper investigates the dynamic interplay between Artificial Intelligence (AI) and human logic in the domain of mathematical problem-solving. By critically examining a series of case studies, we compare the efficacy of AI-generated solutions, particularly those offered by ChatGPT, against traditional human problem-solving methods. The study employs various mathematical challenges, ranging from abstract logical puzzles to applied numerical problems, to evaluate AI's problem-solving approach and alignment with human cognitive processes. Our analysis highlights instances where AI's computational strategies complement or diverge from human reasoning, shedding light on AI's potential and limitations in deciphering mathematical problems. Furthermore, we explore the implications of integrating AI tools in educational contexts, specifically their role in enhancing students' mathematical problem-solving skills. The paper aims to contribute to the ongoing discourse on the optimal utilization of AI in education, proposing a balanced approach that leverages AI's computational power while fostering the depth and creativity of human logic. Through this comparative study, we advocate for a collaborative model where AI and human reasoning merge to enrich the educational landscape, particularly in the teaching and learning of mathematics.


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