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Mining Learning Processes from FLOSS Mailing Archives

Abstract : Evidence suggests that Free/Libre Open Source Software (FLOSS) environments provide unlimited learning opportunities. Community members engage in a number of activities both during their interaction with their peers and while making use of these environments. As FLOSS repositories store data about participants’ interaction and activities, we analyze participants’ interaction and knowledge exchange in emails to trace learning activities that occur in distinct phases of the learning process. We make use of semantic search in SQL to retrieve data and build corresponding event logs which are then fed to a process mining tool in order to produce visual workflow nets. We view these nets as representative of the traces of learning activities in FLOSS as well as their relevant flow of occurrence. Additional statistical details are provided to contextualize and describe these models.
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Patrick Mukala, Antonio Cerone, Franco Turini. Mining Learning Processes from FLOSS Mailing Archives. 14th Conference on e-Business, e-Services and e-Society (I3E), Oct 2015, Delft, Netherlands. pp.287-298, ⟨10.1007/978-3-319-25013-7_23⟩. ⟨hal-01448047⟩



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