We present data-driven log file analyses of an electronic text book for history, called the mBook, to support teachers in preparing lessons for their students. We represent user sessions as contextualised Markov processes of user sessions and
propose a probabilistic clustering using expectation maximisation to detect groups of similar (i) sessions and (ii) users.