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Mining Educational Social Network Structures from FLOSS Repositories

Mukala, Patrick (2016) Mining Educational Social Network Structures from FLOSS Repositories. Technical Report del Dipartimento di Informatica, TR . Università di Pisa, Pisa, IT. (Submitted)

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    FLOSS environments have been proved to provide an interesting learning platform for software engineers. Research suggests that people partaking in both technical and non-technical activities in FLOSS prjects are more likely to positively improve their software engineering skills. To this end, there are propositions to involve computer science and software engineering students in formal higher institutions of learning, in participating in FLOSS projects in order to give them an opportunity to develop their programming capacity by working on real-life projects. While some empirical studies have been conducted to provide some lights on learning processes in FLOSS environments, there is limited or no work done pertaining to understanding social structures during this process of knowledge transfer and acquisition. In this paper, we make use of social network analysis techniques in order to provide insights related to the emerging of social structures from FLOSS repositories from an educational point of view. We hope that these educational structures will enhance both the understanding with regards to how learning occurs in these communities and especially, the frequency of participants' involvement that culminates into learning.

    Item Type: Book
    Uncontrolled Keywords: Social Network Analysis, Learning Models, Mining Data, Educational Data Mining, Learning in FLOSS, Online Learning, Op en-stack
    Subjects: Area01 - Scienze matematiche e informatiche > INF/01 - Informatica
    Divisions: Dipartimenti (from 2013) > DIPARTIMENTO DI INFORMATICA
    Depositing User: Prof. Franco Turini
    Date Deposited: 26 Sep 2016 08:56
    Last Modified: 26 Sep 2016 09:22
    URI: http://eprints.adm.unipi.it/id/eprint/2361

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