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An Approach for Thematic Relevance Analysis Applied to Textual Contributions in Discussion Forums

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Title: An Approach for Thematic Relevance Analysis Applied to Textual Contributions in Discussion Forums
Language: English
Authors: Machado, Crystiano José Richard, Maciel, Alexandre Magno Andrade, Rodrigues, Rodrigo Lins
Source: International Journal of Distance Education Technologies. 2019 17(3).
Availability: IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: journals@igi-global.com; Web site: https://www.igi-global.com/journals/
Peer Reviewed: Y
Page Count: 15
Publication Date: 2019
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Discussion Groups, Integrated Learning Systems, Learning Problems, Content Analysis, Natural Language Processing, Models, Computation, Information Retrieval, Concept Mapping, Foreign Countries, Knowledge Representation, Classification, Graduate Students, Disability Identification, Portuguese
Geographic Terms: Brazil
DOI: 10.4018/IJDET.2019070103
ISSN: 1539-3100
Abstract: Discussion forums in learning management systems (LMS) have been shown to promote student interaction and contribute to the collaborative practice in the teaching-learning process. By evaluating the postings, teachers can identify students with learning difficulties. However, due to the large volume of posts that are generated on a daily basis in these environments, manual analysis becomes impractical. This article proposes a mechanism to support teaching through the thematic relevance analysis of the posts made by students in discussion forums. For this, text mining and metrics from network science were used to process and extract characteristics of the texts. Then, the processed texts were classified through supervised learning algorithms. The results show that the use of these techniques may generate potentially useful indicators for teachers to help them improve their pedagogical practices.
Abstractor: As Provided
Entry Date: 2019
Accession Number: EJ1214725
Database: ERIC
FullText Text:
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  Data: An Approach for Thematic Relevance Analysis Applied to Textual Contributions in Discussion Forums
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  Data: IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: journals@igi-global.com; Web site: https://www.igi-global.com/journals/
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  Data: <searchLink fieldCode="DE" term="%22Brazil%22">Brazil</searchLink>
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  Data: 10.4018/IJDET.2019070103
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  Data: 1539-3100
– Name: Abstract
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  Data: Discussion forums in learning management systems (LMS) have been shown to promote student interaction and contribute to the collaborative practice in the teaching-learning process. By evaluating the postings, teachers can identify students with learning difficulties. However, due to the large volume of posts that are generated on a daily basis in these environments, manual analysis becomes impractical. This article proposes a mechanism to support teaching through the thematic relevance analysis of the posts made by students in discussion forums. For this, text mining and metrics from network science were used to process and extract characteristics of the texts. Then, the processed texts were classified through supervised learning algorithms. The results show that the use of these techniques may generate potentially useful indicators for teachers to help them improve their pedagogical practices.
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        Value: 10.4018/IJDET.2019070103
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
    Subjects:
      – SubjectFull: Discussion Groups
        Type: general
      – SubjectFull: Integrated Learning Systems
        Type: general
      – SubjectFull: Learning Problems
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      – SubjectFull: Content Analysis
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Knowledge Representation
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      – TitleFull: An Approach for Thematic Relevance Analysis Applied to Textual Contributions in Discussion Forums
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            NameFull: Rodrigues, Rodrigo Lins
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