Cohesion-Centered Analysis of Sociograms for Online Communities and Courses Using ReaderBench

Mihai Dascalu, Maria-Dorinela Sirbu, Stefan Ruseti, Scott A. Crossley, Stefan Trausan-Matu, Gabriel Gutu-Robu

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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    Abstract

    Computer Supported Collaborative Learning (CSCL) environments facilitated by technology have become a viable learning alternative from which valuable data can be extracted and used for advanced analyses centered on evaluating participants’ involvement and their interactions. Such automated assessments are implemented within the ReaderBench framework, a Natural Language Processing platform that contains multiple advanced text analysis functionalities. The ReaderBench framework is based on Cohesion Network Analysis from which different sociograms, relying on semantic similarity, are generated in order to reflect interactions between participants. In this paper, we briefly describe the enforced mechanisms used to compare two Math communities, namely an online knowledge building community and an online course.
    Original languageEnglish
    Title of host publication13th European Conference on Technology Enhanced Learning (EC-TEL 2018)
    PublisherSpringer UK
    Pages622-626
    ISBN (Electronic)978-3-319-98572-5
    ISBN (Print)978-3-319-98571-8
    DOIs
    Publication statusPublished - 2018
    EventEuropean Conference on Technology Enhanced Learning: Lifelong Technology-Enhanced Learning (EC-TEL 2018) - Leeds, United Kingdom
    Duration: 3 Sep 20186 Sep 2018
    https://link.springer.com/conference/ectel

    Conference

    ConferenceEuropean Conference on Technology Enhanced Learning
    Abbreviated titleEC-TEL 2018
    CountryUnited Kingdom
    CityLeeds
    Period3/09/186/09/18
    Internet address

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    Electric network analysis
    Semantics
    Processing

    Keywords

    • Cohesion Network Analysis
    • Sociograms
    • Text cohesion
    • Natural Language Processing
    • ReaderBench framework

    Cite this

    Dascalu, M., Sirbu, M-D., Ruseti, S., Crossley, S. A., Trausan-Matu, S., & Gutu-Robu, G. (2018). Cohesion-Centered Analysis of Sociograms for Online Communities and Courses Using ReaderBench. In 13th European Conference on Technology Enhanced Learning (EC-TEL 2018) (pp. 622-626). Springer UK. https://doi.org/10.1007/978-3-319-98572-5_59
    Dascalu, Mihai ; Sirbu, Maria-Dorinela ; Ruseti, Stefan ; Crossley, Scott A. ; Trausan-Matu, Stefan ; Gutu-Robu, Gabriel. / Cohesion-Centered Analysis of Sociograms for Online Communities and Courses Using ReaderBench. 13th European Conference on Technology Enhanced Learning (EC-TEL 2018). Springer UK, 2018. pp. 622-626
    @inproceedings{1b59757d3e874b9bb062e4d74b358ba2,
    title = "Cohesion-Centered Analysis of Sociograms for Online Communities and Courses Using ReaderBench",
    abstract = "Computer Supported Collaborative Learning (CSCL) environments facilitated by technology have become a viable learning alternative from which valuable data can be extracted and used for advanced analyses centered on evaluating participants’ involvement and their interactions. Such automated assessments are implemented within the ReaderBench framework, a Natural Language Processing platform that contains multiple advanced text analysis functionalities. The ReaderBench framework is based on Cohesion Network Analysis from which different sociograms, relying on semantic similarity, are generated in order to reflect interactions between participants. In this paper, we briefly describe the enforced mechanisms used to compare two Math communities, namely an online knowledge building community and an online course.",
    keywords = "Cohesion Network Analysis, Sociograms, Text cohesion, Natural Language Processing, ReaderBench framework",
    author = "Mihai Dascalu and Maria-Dorinela Sirbu and Stefan Ruseti and Crossley, {Scott A.} and Stefan Trausan-Matu and Gabriel Gutu-Robu",
    note = "This publication reflects only the author's view and the European Commission is not responsible for any use that may be made of the information it contains.",
    year = "2018",
    doi = "10.1007/978-3-319-98572-5_59",
    language = "English",
    isbn = "978-3-319-98571-8",
    pages = "622--626",
    booktitle = "13th European Conference on Technology Enhanced Learning (EC-TEL 2018)",
    publisher = "Springer UK",
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    Dascalu, M, Sirbu, M-D, Ruseti, S, Crossley, SA, Trausan-Matu, S & Gutu-Robu, G 2018, Cohesion-Centered Analysis of Sociograms for Online Communities and Courses Using ReaderBench. in 13th European Conference on Technology Enhanced Learning (EC-TEL 2018). Springer UK, pp. 622-626, European Conference on Technology Enhanced Learning, Leeds, United Kingdom, 3/09/18. https://doi.org/10.1007/978-3-319-98572-5_59

    Cohesion-Centered Analysis of Sociograms for Online Communities and Courses Using ReaderBench. / Dascalu, Mihai; Sirbu, Maria-Dorinela; Ruseti, Stefan; Crossley, Scott A. ; Trausan-Matu, Stefan; Gutu-Robu, Gabriel.

    13th European Conference on Technology Enhanced Learning (EC-TEL 2018). Springer UK, 2018. p. 622-626.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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    T1 - Cohesion-Centered Analysis of Sociograms for Online Communities and Courses Using ReaderBench

    AU - Dascalu, Mihai

    AU - Sirbu, Maria-Dorinela

    AU - Ruseti, Stefan

    AU - Crossley, Scott A.

    AU - Trausan-Matu, Stefan

    AU - Gutu-Robu, Gabriel

    N1 - This publication reflects only the author's view and the European Commission is not responsible for any use that may be made of the information it contains.

    PY - 2018

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    N2 - Computer Supported Collaborative Learning (CSCL) environments facilitated by technology have become a viable learning alternative from which valuable data can be extracted and used for advanced analyses centered on evaluating participants’ involvement and their interactions. Such automated assessments are implemented within the ReaderBench framework, a Natural Language Processing platform that contains multiple advanced text analysis functionalities. The ReaderBench framework is based on Cohesion Network Analysis from which different sociograms, relying on semantic similarity, are generated in order to reflect interactions between participants. In this paper, we briefly describe the enforced mechanisms used to compare two Math communities, namely an online knowledge building community and an online course.

    AB - Computer Supported Collaborative Learning (CSCL) environments facilitated by technology have become a viable learning alternative from which valuable data can be extracted and used for advanced analyses centered on evaluating participants’ involvement and their interactions. Such automated assessments are implemented within the ReaderBench framework, a Natural Language Processing platform that contains multiple advanced text analysis functionalities. The ReaderBench framework is based on Cohesion Network Analysis from which different sociograms, relying on semantic similarity, are generated in order to reflect interactions between participants. In this paper, we briefly describe the enforced mechanisms used to compare two Math communities, namely an online knowledge building community and an online course.

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    KW - Text cohesion

    KW - Natural Language Processing

    KW - ReaderBench framework

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    Dascalu M, Sirbu M-D, Ruseti S, Crossley SA, Trausan-Matu S, Gutu-Robu G. Cohesion-Centered Analysis of Sociograms for Online Communities and Courses Using ReaderBench. In 13th European Conference on Technology Enhanced Learning (EC-TEL 2018). Springer UK. 2018. p. 622-626 https://doi.org/10.1007/978-3-319-98572-5_59