Multiple Criteria Decision Aid (MCDA) aims at providing support to a decision maker (DM) involved in a decision process. This requires a decision aiding process in which the DM and an analyst interact to build a model grounded on several criteria. This decision aiding process is usually composed of various phases among which the identification of the stakeholders, the definition of set of alternatives, construction of evaluation criteria, the elicitation of the DM's preferences. The later task require to organize a preference elicitation process. In this paper, we aims at studying the nature of such elicitation process. We show that preference elicitation can be conceived so that the DM to elaborate his/her convictions along the elicitation process: constructive learning preference elicitation. We investigate the specificities of tools supporting such elicitation processes. We also provide a general framework to describe a large class of preference elicitation procedures.