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oapen-20.500.12657-582202022-09-16T03:13:41Z Chapter A structural equation model to measure logical competences Bacci, Silvia Bertaccini, Bruno Bruni, Riccardo Crescenzi, Federico Donati, Beatrice SEM Logical abilities Training course effectiveness bic Book Industry Communication::J Society & social sciences::JH Sociology & anthropology::JHB Sociology::JHBC Social research & statistics 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. 2022-09-15T20:05:35Z 2022-09-15T20:05:35Z 2021 chapter ONIX_20220915_9788855184618_16 2704-5846 9788855184618 https://library.oapen.org/handle/20.500.12657/58220 eng Proceedings e report application/pdf Attribution 4.0 International 978-88-5518-461-8_8.pdf https://books.fupress.com/doi/capitoli/978-88-5518-461-8_8 Firenze University Press 10.36253/978-88-5518-461-8.08 10.36253/978-88-5518-461-8.08 bf65d21a-78e5-4ba2-983a-dbfa90962870 9788855184618 132 5 Florence open access
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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.
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