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This paper presents a methodological proposal for automatic identification of emotions in educational environments using machine learning algorithms and physiological and behavioral signal acquisition technologies to identify relations between emotions and learning. Four of the main learningcentered emotions are considered [1]: engagement, boredom, confusion and frustration. It is proposed to make a fusion of data from two physiological and behavioral signal acquisition technologies with the objective of achieving the identification of emotions in the most precise manner. Therefore, considering the stages of the proposed methodology, the first of them is presented and the design of the experiment that will be executed for data collection. The development of an appropriate database with elements belonging to a learning environment for the study of emotions is an essential task.

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Collaborative spaces are widely used for diverse organizations and purposes. Despite the fact that technological solutions exist there is a lack of methodological support to develop such environments. In this paper we illustrate how FlowiXML methodology can be used to develop collaborative spaces using a real life case study. The benefits of the resulting system are evaluated and the results are discussed.