PLS-SEM Validation of a Game-Based Vocabulary Learning Model: Do Cinematic, Narrative, and Quest-Oriented Games Fit Iranian EFL Learners?
Keywords:
Bootstrapping, Cinematic, Narrative, Quest-Oriented Games, Partial Least Squares, Vocabulary Learning Performance, Structural Equation ModelingAbstract
This study aims to investigate a hypothesized model of vocabulary learning performance enhanced by three types of commercial game features: Cinematic, Narrative, and Quest-Oriented games, within Iran’s EFL context. Given the growing role of digital games in language education, this research investigates how these game types assist in enhancing vocabulary learning performance. Knowing words is the first step to mastering a language. However, many students in Iran focus mainly on passing tests and don't get enough practice with real-world English. Educators in Iran are interested in game-based learning, but they need a reliable framework to know which game genres best teach vocabulary. A variance-based structural equation modeling approach (PLS-SEM) was applied to test the measurement model (reliability and validity) and the structural model (predictive paths). Bootstrapping techniques were applied in PLS software to stabilize estimates. The analysis confirmed the model, and findings indicate that cinematic, narrative, and quest-oriented games are positively associated with vocabulary gains in the Iranian EFL context, with notable implications for teachers and curriculum developers aiming to adopt game-based methodologies in language instruction. Also, narrative and quest-oriented games showed comparatively larger effects than cinematic games. Findings recommend incorporating these specific genres of games into Iranian EFL curricula to enhance vocabulary learning.
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Copyright (c) 2025 Parvaneh Pedram (Author); Farhad Fahandezh Saadi; Shahram Afraz (Author)
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