IMAGES MATTER: A SEMIOLOGICAL CONTENT ANALYSIS OF GENDER POSITIONING IN CONTEMPORARY ENGLISH-LEARNING SOFTWARE APPLICATIONS

A semiological content analysis of gender positioning in two English-learning software programs (Tell Me More and English at Home) demonstrates the usefulness of this approach for investigating semiotic resources which situate gender unfairly in visual discourse. Dimensions identified in Goffman’s Gender Advertisements (1979) were mapped onto the image categories developed by Kress and van Leeuwen in Reading Images (2006) to form the following resources: active participant, gaze direction, visual techniques, modality, and body display. The results showed that males appeared as active, competent, dominant, and powerful. Females appeared as reactive, objects of the male gaze, intimate, subordinate, and powerless even in modern technology-based media. Accordingly, this study discusses the translatability of Goffman’s content analysis.