This study presents a novel technique for computing the division of intervals and fuzzy numbers under positive and negative scenarios, focusing on arithmetic operations involving complete correlation. By exploring the relationship between fuzzy numbers through complete correlation, we provide a framework for interactive division that differs from traditional methods. Our results are compared with outcomes derived from Zadeh’s extension principle and the generalized Hukuhara division. Additionally, we investigate the behavior of these operations using $\alpha$-cuts, offering a detailed analysis of their performance across different $\alpha$-cut levels.