THE INTEGRATION OF VISUAL GRAMMAR INTO GENRE-BASED APPROACH TO DEVELOP STUDENTS’ MULTIMODAL VIEWING SKILLS
DOI:
https://doi.org/10.21009/ishel.v2i1.69398Keywords:
EFL learning, genre-based approach, multimodal literacy, viewing skills, visual grammarAbstract
In contemporary EFL classrooms, students increasingly encounter multimodal texts that combine images, written language, layout, color, and digital visual resources. However, viewing skills are often insufficiently addressed because English instruction remains largely focused on verbal literacy. This study investigated the integration of visual grammar into genre-based approach to develop junior high school EFL students’ viewing skills. An embedded mixed-methods design with a quasi-experimental non-equivalent pre-test–post-test control group was employed. The participants were 72 Grade 9 students from a public junior high school in Bogor, Indonesia, divided into experimental and control groups. The experimental group received instruction through the teaching and learning cycle integrated with visual grammar and image-text relations, while the control group received regular EFL instruction. Data were collected through viewing skills tests, classroom observations, questionnaires, interviews, and students’ learning artifacts. The findings showed that the experimental group improved from 56.42 to 76.83, with a mean gain of 20.41 and a moderate N-Gain of 0.47, while the control group improved from 55.81 to 65.28, with a mean gain of 9.47 and a low N-Gain of 0.21. The experimental group also outperformed the control group across five dimensions of viewing skills, particularly image-text interpretation, visual grammar analysis, and visual recognition. Students perceived the model as clear, engaging, and useful, although abstract visual grammar concepts remained challenging. The study concludes that the integration provides a structured and pedagogically meaningful model for teaching, practicing, and assessing viewing skills in junior high school EFL classrooms.
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Copyright (c) 2026 Alan Jaelani, Liliana Muliastuti, Samsi Setiadi
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