A methodological framework for analyzing the language in digital games

Abstract

Digital game-based language learning (DGBLL) researchers have often touted the substantial amount of contextualized second language (L2) input that games can provide L2 learners. Yet, little research has analyzed this input or, more generally, described the linguistic environments within digital games. To this end, this chapter details a framework for identifying, describing, and analyzing these digital linguistic environments using corpus linguistics tools and methods. The framework follows Biber and Conrad's (2019) register analysis, which identifies unique situations of language use (i.e., registers) through a series of situational analyses. This study targets the language in the fictional worlds of four popular commercial digital games: Fallout 4, Divinity 2, Skyrim, and the Witcher III. The situational analyses revealed two spoken language registers, Interactive Speech and Immersive Speech, and four written language registers, Character Text, Quest Text, Tutorial Text, and Lore. To quantify the extent to which the games' spoken language may be transferable to real-world contexts, a large corpus was compiled from the digital language files of the games containing 4.8 million words across 30,000 texts. Texts are compared to real-world speech on the frequencies of 15 linguistic features common in real-world spoken conversations. Results find Immersive Speech to be more similar to real-world speech (Cohen's d = 0.25) than Interactive Speech (d = 0.67). Findings suggest that game mechanics that use Immersive Speech in their design may expose L2 learners to input that may be more transferable to the real world. The framework presented can inform future research in targeting, giving direction for future research targeting specific game mechanics and designs rather than focusing on game genres or specific titles.