improve the effectiveness of the tutoring services, as it would be complementary to dividing the problem into problem states. For example, if a learner performed a pattern p, an association rule could indicate that the learner has a higher probability of applying another pattern q later during the exercise than another pattern r that is available for the same problem state. 

Acknowledgment. Our thanks go to the FQRNT and NSERC for their logistic and financial support. The authors would like to thank Severin Vigot and Mikael Watrelot for integrating the framework in RomanTutor, and Khaled Belghith, Daniel Dubois, Usef Faghihi, Mohamed Gaha and the other members of the GDAC/PLANIART 
teams who participated in the development of RomanTutor. 

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