Nowadays, digital scenes, like games, tend to mostly use model animation, like facial expressions, and spoken dialogue, to convey emotion. However, those approaches are not always possible. This work explores the current approaches to text animation patterns, speech bubbles and background shapes and color, in order to convey emotion. It also aims to create a module that can control these aspects, and integrate it within a Virtual Tutoring application, which also utilizes model animation. We also present experiments, both comparing the existing base version, and final version of the application, and testing the emotional perception of each version, in order to understand if our approaches were correctly implemented. It was possible to observe that the addition of such details led the system to be recognized as better animated, when compared with the earlier version, however it when tested alone, some emotions ended up being less recognized, while others had a better impact on the application. In the end, we observe that such details can help improve the emotional recognition of a scene, however the additional information on one channel can create noise and bias on the other emotional channels, leading to worse results in certain occasions. Nonetheless, they can and should be used in order to reinforce emotional recognition, without creating contrast with the leading emotional channel.