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Training Prospective Primary and Kindergarten Teachers on Electric Circuits Using Conceptual Metaphors

Bibliographic Data

ID22045673
AuthorsFederico Corni (0000-0003-1226-1585, Free University of Bozen-Bolzano, corresponding author), Marisa Michelini (0000-0003-4764-9774, University of Udine), Leonardo Colletti (0000-0001-5689-6203, Free University of Bozen-Bolzano)
Year2022
Volume12
Issue7
Pages457
Publication date2022-06-30
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEducation Sciences (JOURNAL)
Journal identifiersISSN: 2227-7102 • E-ISSN: 2227-7102
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/educsci12070457
OpenAlexW4283746742
LanguageEN
Citations received3
References cited29

The awareness and use of conceptual metaphors available in ordinary language should be a relevant part of teaching strategies, yet it is still rather neglected in teacher education. With a specific activity, we integrated a class of prospective kindergarten and primary school teachers on electric circuits with a reflection on the cognitive and linguistic aspects of metaphor. To understand how effective this integration proved to be, both in terms of learning and in terms of developing teaching skills, we conducted a single case study with a mixed qualitative–quantitative methodology. Student teachers were invited to analyze and discuss expressions on electric circuits selected from those they themselves had formulated at an earlier time. Here, we present some relevant results from the analysis of the students’ elaborations, highlighting how they worked with metaphors. They demonstrated a better understanding of the subject matter and greater awareness of teaching as well, in particular for what concerns the use of language and identifying and overcoming implicit ideas

Cognition · Linguistics · Mathematics education · Metaphor · Pedagogy · Qualitative research · Sociology · Teaching method · Computer Science · Education Practices and Challenges · Language, Metaphor, and Cognition · Psychology · Science Education and Pedagogy · Artificial Intelligence

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Unique citing works3
Citations per year1
Citation span2023 - 2026 (4)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 3

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