Background. Many learning environments are quickly deserted by learners, even if they are efficient. Gamification of learning environments is a recent approach used to enhance learners' motivation and participation. Aim. One issue with this approach is that people have various expectations and react differently faced with specific game mechanics. So, an important goal lies in automatically adapting game mechanics according to player types. In this paper, we study the gaming features that can be adapted in learning environments and the player model that can be used for the adaptation process. We propose an approach that aims to predict to which game mechanics a user is responsive, and to adapt the gaming features of the system according to this information. Methodology. An implementation was released, and evaluated through an exploratory study with 59 middle school students, each one using the learning environment during three 45-minutes sessions. Results. The results validate the implementation of the system and show that the users' activity can help to predict their profile. The adaptation process did not improve learners' engagement as expected, but it shows a path for future research toward an adaptive approach for learning environment gamification.