The problem of propagating disinformation (a.k.a. "fake news") on social media has increased significantly in the last few years. There are several initiatives around the world to combat this serious problem. Maybe the most promising ones involve training people to identify "fake news." The use of digital educational games (DEG) to implement such initiatives has presented significant results. Nevertheless, to the best of our knowledge, most of the existing DEG applied to this purpose are designed for English-written News articles, leaving an important gap for news written in other languages, such as Portuguese, for example. Faced with this scenario, this article presents JEDi, a DEG that trains students to identify "fake news" written in Portuguese. JEDi is a version of the known "Trail Game" where the players must traverse the board by correctly distinguishing real from false news. We raise the hypothesis that as the students play JEDi, they develop the ability to recognize disinformation. It is also important to highlight that JEDi collects detailed data from every match in order to provide longitudinal analyses of each player's performance. This paper reports the application of JEDi in three case studies. While the first study involved 43 students from high school, the second and the third were developed with 29 undergraduate and 33 graduate students, respectively. Quantitative and qualitative results obtained in the three studies point to JEDi's effectiveness as a "fake news" detection training instrument. Mining techniques such as association rule mining were employed in data analysis and revealed frequent information that occurred simultaneously in JEDi's database (e.g. some mined association rules showed that even students who considered themselves experts in identifying "fake news" could improve their skills by playing successive rounds of the game).