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In this paper, we propose a method for the real time evaluation of collaborative activities. The method aims to classify collaborative activities using a memory-based learning model and to evaluate them using a reference set of pre-evaluated activities. The proposed approach uses time series to represent activities and classifies them regarding their similarity. In order to evaluate the results, the method is used as an automatic rater of collaboration quality and the ratings are compared to ratings of human experts.