Crowdsourcing platforms are changing the way how people work and earn money. The population of workers on crowdsourcing platforms is already counted in millions and keeps growing. Workers on these platforms face several challenges, and searching appropriate tasks to perform is one of them. Preliminary work (surveys) carried out in the last year in this line of research shows that workers spend about 27% of their time on searching tasks they want to perform. In this proposal we aim to decrease this searching time by improving both tasks searching and tasks selecting experience. Current state of the art is focused mainly on helping workers to discover new tasks using recommendation systems, while we propose to focus also on the tasks selecting problem, by investigating what information and how to display to workers about a task, in order to help them to decide which one to work on or discard.