This paper describes a collaborative educational data mining tool based on association rule mining for the continuous improvement of e-learning courses allowing teachers with similar course's profile sharing and scoring the discovered information. This mining tool is oriented to be used by instructors non experts in data mining such that, its internal operation is transparent to the user and the instructor can be focused in to the analysis of the results and make decisions about how to improve e-learning courses. (Contains 5 figures.) [Funding was provided by the Spanish Department of Research. For the complete proceedings, "Proceedings of the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, July 1-3, 2009)," see ED539041.]