This paper proposes a method based on the rough set theory and dedicated to the incremental supervised learning in a context of unbalanced data. This method consists of three phases: the construction of a decision table, the inference of a set of decision rules, and the classification of each potential action in one of the predefined decision classes. The MAI2P method is validated in the context of MOOC (Massive Open Online Course).