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Decision Point Analysis on Learning Process Models in FLOSS mailing Archives

Mukala, Patrick (2016) Decision Point Analysis on Learning Process Models in FLOSS mailing Archives. Technical Report del Dipartimento di Informatica, TR . Università di Pisa, Pisa, IT. (Submitted)

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    Abstract. Numerous studies continue to explore the potential of social interactions between people in Free/Libre Open Source Software (FLOSS) environments. While the dynamics of interactions in these environments can be understood from different perspectives, we put a particular focus on any interactions resulting in knowledge transfer and acquisition. As learning platforms, FLOSS communities provide immense opportunities for improving software engineering skills. People who engage in FLOSS activities both acquire and improve their software development skills. For this reason, it is very helpful to understand how these learning interactions occur. In this paper, we make use of the decision miner in process mining to conduct our analysis. The purpose of such an endeavour is twofold. Firstly, we provide empirical insights into how people learn while exchanging emails in FLOSS mailing archives. Lastly, we go a step further by providing insights behind the motivation into learning participants' decisions on their learning paths.

    Item Type: Book
    Uncontrolled Keywords: Pro cess-Flow Analysis, FLOSSData, Educational Data Mining, Learning in FLOSS, Decision Mining, Learning Analytics
    Subjects: Area01 - Scienze matematiche e informatiche > INF/01 - Informatica
    Divisions: Dipartimenti (from 2013) > DIPARTIMENTO DI INFORMATICA
    Depositing User: Prof. Franco Turini
    Date Deposited: 28 Feb 2017 15:07
    Last Modified: 28 Feb 2017 15:07
    URI: http://eprints.adm.unipi.it/id/eprint/2365

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