ReaderBench: Building Comprehensive Sociograms of Online Communities

Sirbu, Dorinela; Panaite, Marilena; Secui, Ana; Dascălu, Mihai; Nistor, Nicolae; Trăușan-Matu, Ștefan

doi:10.1109/synasc.2017.00044

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…Mihai Dascalu, Professor at the Department of Computers, University Politehnica of Bucharest, is known for his work on ReaderBench, a tool that aims at supporting students' and teachers through cohesion-based analysis, identification of reading strategies identification and evaluation of textual complexity [65]. Stefan Trausan-Matu, Professor of Computer Science at University Politehnica of Bucharest, has published extensively about analysis of student discourse and collaborated with Dascalu on ReaderBench [66]. The two developed a technique for constructing networks where ties between students are based on cohesion metrics of the discourse they shared online.…”

Section: A Knowledge Creatorsmentioning

confidence: 99%

Networks in Education: A Travelogue Through Five Decades

2022

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For over five decades, researchers have used network analysis to understand educational contexts, spanning diverse disciplines and thematic areas. The wealth of traditions and insights accumulated through these interdisciplinary efforts is a challenge to synthesize with a traditional systematic review. To overcome this difficulty in reviewing 1791 articles researching the intersection of networks and education, this study combined a scientometric approach with a more qualitative analysis of metadata, such as keywords and authors. Our analysis shows rapidly growing research that employs network analysis in educational contexts. This research output is produced by researchers in a small number of developed countries. The field has grown more recently, through the surge in the popularity of data-driven methods, the adoption of social media, and themes as teacher professional development and the now-declining MOOC research. Our analysis suggests that research combining networks and educational phenomena continues to lack an academic home, as well as remains dominated by descriptive network methods that depict phenomena such as interpersonal friendship or patterns of discourse-based collaboration.

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Section: A Knowledge Creatorsmentioning

confidence: 99%

Networks in Education: A Travelogue Through Five Decades

2022

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“…Two types of views are used to model the interaction between participants, namely a Force-Clustered Graph and a Hierarchical Edge Bundling visualization [3]. The views are generated using the d3.js library (https://d3js.org).…”

Section: Performed Experimentsmentioning

confidence: 99%

“…The first experiment evaluated the involvement of participants in online blog communities, their interactions and evolution throughout the discussion threads [3]. The analysis was performed on a corpus of 85 conversations from 78 members, cumulating 250 contributions extracted from the online Math community http:// mathequalslove.blogspot.com.…”

Section: Performed Experimentsmentioning

confidence: 99%

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

Dascălu

Sirbu

Guțu-Robu

et al. 2018

Lifelong Technology-Enhanced Learning

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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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