Articles producció científica> Pedagogia

Sentiment analysis for formative assessment in higher education: a systematic literature review

  • Identification data

    Identifier: imarina:9296458
    Authors:
    Grimalt-Alvaro, CUsart, M
    Abstract:
    Sentiment Analysis (SA), a technique based on applying artificial intelligence to analyze textual data in natural language, can help to characterize interactions between students and teachers and improve learning through timely, personalized feedback, but its use in education is still scarce. This systematic literature review explores how SA has been applied for learning assessment in online and hybrid learning contexts in higher education. Findings from this review show that there is a growing field of research on SA, although most of the papers are written from a technical perspective and published in journals related to digital technologies. Even though there are solutions involving different SA techniques that can help predicting learning performance, enhancing feedback and giving teachers visual tools, its educational applications and usability are still limited. The analysis evidence that the inclusion of variables that can affect participants’ different sentiment expression, such as gender or cultural context, remains understudied and should need to be considered in future developments.
  • Others:

    Author, as appears in the article.: Grimalt-Alvaro, C; Usart, M
    Department: Pedagogia
    URV's Author/s: Grimalt Alvaro, Maria del Carme / Usart Rodríguez, Mireia
    Keywords: Technology Review of literature Online Higher education Gender Artificial intelligence technology students review of literature polarity higher education gender feedback emotions attitudes
    Abstract: Sentiment Analysis (SA), a technique based on applying artificial intelligence to analyze textual data in natural language, can help to characterize interactions between students and teachers and improve learning through timely, personalized feedback, but its use in education is still scarce. This systematic literature review explores how SA has been applied for learning assessment in online and hybrid learning contexts in higher education. Findings from this review show that there is a growing field of research on SA, although most of the papers are written from a technical perspective and published in journals related to digital technologies. Even though there are solutions involving different SA techniques that can help predicting learning performance, enhancing feedback and giving teachers visual tools, its educational applications and usability are still limited. The analysis evidence that the inclusion of variables that can affect participants’ different sentiment expression, such as gender or cultural context, remains understudied and should need to be considered in future developments.
    Thematic Areas: Pedagogical & educational research Education & educational research Education Educació Computer science (all) Ciencias sociales
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: mireia.usart@urv.cat carme.grimalt@urv.cat
    Author identifier: 0000-0003-4372-9312 0000-0002-5314-7706
    Record's date: 2024-08-03
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://link.springer.com/article/10.1007/s12528-023-09370-5
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Journal Of Computing In Higher Education.
    APA: Grimalt-Alvaro, C; Usart, M (2023). Sentiment analysis for formative assessment in higher education: a systematic literature review. Journal Of Computing In Higher Education, (), -. DOI: 10.1007/s12528-023-09370-5
    Article's DOI: 10.1007/s12528-023-09370-5
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2023
    Publication Type: Journal Publications
  • Keywords:

    Education,Education & Educational Research
    Technology
    Review of literature
    Online
    Higher education
    Gender
    Artificial intelligence
    technology
    students
    review of literature
    polarity
    higher education
    gender
    feedback
    emotions
    attitudes
    Pedagogical & educational research
    Education & educational research
    Education
    Educació
    Computer science (all)
    Ciencias sociales
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