Learning English Literacy through Video Games: A Multimodal Perspective

T. Silvana Sinar, T. Thyrhaya Zein, Balazs Huszka, Muhammad Yusuf, Puan Maharani, Dedi Sanjaya

Abstract


Multimodal analysis in learning English literacy is meant to be an eye-opener for future research related to video games as didactic tools as they are comparatively less studied, although there has been rapid growth in the multimedia industry in the past decades. The data in the present study were taken from three different video game genres: Role Playing Game (RPG), Multiplayer Online Battle Arena (MOBA), and FPS (First Person Shooter), with two different titles for each genre. The data examined in this study were elements of composition and ten student game players. The compositional features in the collected data from the respective footage of the video games were based on a visual grammar by Kress and Leeuwen (2006) This research utilized the interactive model of qualitative data analysis by Miles, Huberman, and Saldana (2014) in analyzing the compositional features. It consists of three parts: data condensation, data display, and drawing and verifying conclusion. After analyzing the composition, the players were interviewed to gather the vocabulary learned through the process of playing the games. This study found that in terms of composition features: 37 elements of information values, 37 saliences, and 36 framings. It can be concluded that these genres own more maximum disconnection framing than maximum connection. However, these students categorized fighting genre and shooting genre elements without centered information value. The implications of the study towards learning the English language are: in the first place, video games can be one the useful media to teach students reading and speaking literacy skills, especially vocabulary and historical knowledge. Secondly, these games help the players acquire the English language subconsciously and make them enjoy the learning process.

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DOI: https://doi.org/10.5430/jct.v13n1p102

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Copyright (c) 2024 T. Silvana Sinar, T. Thyrhaya Zein, Balazs Huszka, Muhammad Yusuf, Puan Maharani, Dedi Sanjaya

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