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Analiza Dyskursu z Wykorzystaniem Wizualizacji×Analiza dyskursu multimodalnego×
DziedzinaMetody jakościoweJęzykoznawstwo
RodzinaProcess / pipelineProcess / pipeline
Rok powstaniaLate 1990s–2000s (consolidation as a combined approach)1996
TwórcaSynthesised from photo-elicitation (Clark, 1969; Harper, 2002) and discourse analysis (Foucault; Fairclough)Gunther Kress and Theo Van Leeuwen
TypQualitative combined methodEmpirical process pipeline
Źródło pierwotneHarper, D. (2002). Talking about pictures: A case for photo elicitation. Visual Studies, 17(1), 13–26. DOI ↗Kress, G., & Van Leeuwen, T. (2006). Reading Images: The Grammar of Visual Design (2nd ed.). London: Routledge. DOI ↗
Inne nazwyVEDA, photo-elicitation discourse analysis, image-elicitation discourse analysis, visual elicitation interview analysisMultimodal Analysis, Semiotic Analysis
Pokrewne52
PodsumowanieVisual Elicitation Discourse Analysis (VEDA) is a qualitative method that uses photographs or other images as interview stimuli to generate participant talk, which is then subjected to systematic discourse analysis. By anchoring conversation in concrete visual materials, VEDA accesses meanings, ideologies, and subject positions that purely verbal questioning often fails to surface. The approach combines the depth of elicitation interviewing with the critical, language-focused rigour of discourse analysis.Multimodal Discourse Analysis is a method for examining how meaning is created through the integration of multiple modes of communication: language, image, sound, gesture, and spatial arrangement. Developed by Gunther Kress, Theo Van Leeuwen, and others, this approach recognizes that in contemporary communication—from videos to websites to classrooms—meaning is rarely conveyed by language alone. By analyzing how text, visuals, sound, and other modes work together, multimodal analysis reveals how complex meanings are constructed.
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ScholarGatePorównaj metody: Visual Elicitation Discourse Analysis · Multimodal Discourse Analysis. Pobrano 2026-06-17 z https://scholargate.app/pl/compare