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A multimodal discourse analysis of in-text images of Nigerian literature texts for primary schools

Bibliographic Data

ID13032816
AuthorsBukola Alfred (Obafemi Awolowo University, corresponding author), Ifeoluwa Olayinka (Obafemi Awolowo University)
Year2025
Volume11
Issue2
Pages233-268
Publication date2025-04-22
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLanguage and Semiotic Studies (JOURNAL)
Journal identifiersISSN: 2096-031X • E-ISSN: 2751-7160
PublisherWalter de Gruyter GmbH (PUBLISHER • DE)
DOI10.1515/lass-2024-0040
OpenAlexW4409666313
LanguageEN
Citations received1
References cited5

This article examines the in-text images from literature textbooks of Nigerian primary schools and how these are succinctly used to positively enhance the learning process of pupils at that level. The data for the study comprises seventy-eight (78) in-text images from 5 literature books for pupils from grade 3–5. The data was analyzed using van Leeuwen’s Visual Grammar and a discussion of how various visual elements may impact on their understanding of the messages and key themes in the texts with a focus on the representative metafunction level of analysis. The findings of the study show that in-text images deployed in the literature texts effectively complement the written texts, and has valuable pedagogical implications, including providing more interactive and personalized learning experiences. Also, the finding show that visual elements help pupils to cultivate good attributes in relation to taking responsibility, cultural diversity, ethics, decision making, friendship and so on. The study concludes that incorporating visual elements in the literature textbooks for primary schools can create a more impactful learning engagement for the target audience

Discourse analysis · Linguistics · Natural language processing · Physics · Primary (astronomy · Sociology · Computer Science · Discourse Analysis in Language Studies · EFL/ESL Teaching and Learning · Literacy, Media, and Education · Philosophy

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

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