Exploring the Role of Motivation in Self‐Regulated Digital Game‐Based Vocabulary Learning Among Saudi <scp>EFL</scp> Learners: A Structural Equation Modelling Approach to Attention, Relevance, Confidence and Satisfaction

ABSTRACT This study investigated the relationship between attention, relevance, confidence and satisfaction within the ARCS motivational framework in self‐regulated digital game‐based vocabulary learning among Saudi EFL learners. Employing structural equation modelling, this study examined how these motivational factors interact and influence learner engagement in digital game‐based vocabulary learning. A sample of 794 Saudi EFL learners enrolled in university‐level English courses participated in the study. Data were collected using a 24‐item motivation questionnaire adapted from the ARCS model. Exploratory and confirmatory factor analyses were conducted to validate the instrument's factor structure and measurement model. Structural equation modelling revealed significant positive relationships among the motivational constructs, with attention positively influencing relevance ( β = 0.71) and satisfaction ( β = 0.34), relevance positively affecting confidence ( β = 0.72), and confidence positively influencing satisfaction ( β = 0.52). Moreover, confidence mediated the relationship between relevance and satisfaction. Gender significantly predicted attention ( β = 0.22) and confidence ( β = 0.07), whereas academic‐level predicted attention ( β = 0.10). Age had no significant effect on motivational constructs. The findings confirm the importance of designing self‐regulated digital game‐based vocabulary‐learning environments that capture learners' attention, align with their goals, foster self‐efficacy and promote satisfaction to enhance vocabulary learning. This study contributes to growing research on game‐based language learning and offers implications for instructional design and digital learning strategies in EFL contexts.