Multimodal literacy and language testing: Visual and intersemiotic literacy indicators of reading comprehension texts. Issue 3 (1st October 2020)

• Record Type: Journal Article
• Authors: Karatza, Styliani
• Is Part Of: Journal of visual literacy. Volume 39:Issue 3/4(2020)
• Page Start: 220
• Page End: 255
• Publication Date: 2020-10-01
• Subjects: Multimodal literacy -- reading comprehension text -- visual literacy indicators -- intersemiotic literacy indicators -- image -- image-writing relations -- large-scales language examinations; Visual literacy -- United States -- Periodicals; Visual learning -- United States -- Periodicals; Visual communication -- United States -- Periodicals; Visual learning; Visual literacy; United States; Periodicals; 302.22605
• DOI: 10.1080/1051144X.2020.1826222
• Languages: English
• ISSNs: 1051-144X

Abstract

Abstract: This paper is concerned with multimodal literacy involving the different kinds of knowledge required to fully access texts with multiple semiotic resources used in reading comprehension test tasks. Such literacy requirements have not drawn researchers' attention to date, mainly because the foreign language teaching and testing project has primarily focussed on the verbal features of reading comprehension texts. Drawing on data from the Greek National Foreign Language Exams (known with the acronym KPG) – one of the few high-stakes examination systems which use multimodal reading comprehension texts – the paper approaches reading comprehension as a meaning-making process highly dependent on both image and language used in test tasks and the relations between them (i.e. intersemiosis ). Working mainly within the framework of Systemic Functional Linguistics (SFL), this study has attempted a systematic description of the visual and intersemiotic literacy indicators of 86 multimodal media texts used in KPG reading comprehension test tasks. For the SFL-oriented multimodal discourse analysis, Tan et al.'s categories of system choices suggested for the analysis of different types of multimodal media texts, and the Multimodal Analysis Image (MMA) interactive software program were used.