Traditionally in scheduling problems, the job processing time is considered constant. However, when tasks are performed by humans, processing times can decrease when the resource improves productivity, for example as a result of the learning effect. The aim of this work is to compare two approaches to modeling the learning effect proposed in the literature in order to evaluate their complexity and to assess the effect over the makespan in a flowshop scheduling problem (FSSP).