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    Chapter A structural equation model to measure logical competences

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    Author(s)
    BACCI, Silvia
    Bertaccini, Bruno
    Bruni, Riccardo
    Crescenzi, Federico
    Donati, Beatrice
    Language
    English
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    Abstract
    Logical abilities are a ubiquitous ingredient in all those contexts that take into account soft skills, argumentative skills or critical thinking. However, the relationship between logical models and the enhancement of these abilities is rarely explicitly considered. Two aspects of the issue are particularly critical in our opinion, namely: (i) the lack of statistically relevant data concerning these competences; (ii) the absence of reliable indices that might be used to detect and measure the possession of abilities underlying the aforementioned skills. This paper addresses both aspects of this topic by presenting the results of a research that we conducted between October and December 2020 on students enrolled in various degree courses at the University of Florence. The dataset has been collected by a three-stage initiative. We started from an entrance examination to assess the students' initial abilities. This test included ten questions, each regarding a specific aspect of logical reasoning. Then, students underwent a short training course to strengthen their knowledge of logic. At the end of the short course, students underwent a final examination to evaluate the effectiveness of the training. To verify the effectiveness of the training program we used students’ characteristics into a Structural Equation Model comparing the distribution of abilities before and after the training.
    URI
    https://library.oapen.org/handle/20.500.12657/56348
    Keywords
    SEM; Logical abilities; Training course effectiveness
    DOI
    10.36253/978-88-5518-461-8.08
    ISBN
    9788855184618, 9788855184618
    Publisher
    Firenze University Press
    Publisher website
    https://www.fupress.com/
    Publication date and place
    Florence, 2021
    Series
    Proceedings e report, 132
    Pages
    5
    Rights
    https://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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