Inventory management under imprecise input parameters have recently led to a substantial number of studies. Researchers have mostly preferred using fuzzy set theory to formulate the impreciseness associated with the input parameters. While they mostly assume that adjusting fuzzy parameters depends on inventory operator’s expertise, they neglect the influence of human characteristics in their models.  Since human characteristics influence inventory decision, they should be included in the inventory models. In this paper, we develop a mathematical model for a fuzzy EOQ model with backorders by incorporating inventory operator’s learning in imprecise/fuzzy parameters. The mathematical model presents a situation where the operator is able to learn over the planning cycles and thus is able to apply the acquired knowledge in setting the fuzzy parameters. In the developed model, the learning ability includes cognitive and motor capabilities of humans.  The results show that learning with cognitive and motor capabilities could reduce the total cost of the inventory system