This study examines the impact of English anxiety on learning outcomes in digital game-based learning (DGBL) for English pronunciation. While language anxiety is known to hinder learning, its effects in DGBL contexts remain underexplored. To address this, a DGBL system was developed, and an experiment involving 56 non-English major university students was conducted. Participants were categorized into a high anxiety group (HAG) and a low anxiety group (LAG) based on an English anxiety scale. Data were collected through pronunciation tests, motivation 3and flow state scales, and badge performance logs. Results showed significant pronunciation improvement in both groups, with no significant differences between them. Notably, the HAG outperformed the LAG in badge performance related to listening and pronunciation practice. Both groups reported comparable motivation and flow experience. These findings highlight the importance of considering anxiety levels in DGBL design and suggest the value of personalized systems to support diverse learner needs.

Despite a growing body of literature on performance goals and learning, limited studies have explored their influence on English translation education within the context of Digital Game-Based Learning (DGBL). To address this gap, this study developed a DGBL system to assist students in learning English translation techniques, and compared the effects of students’ different performance goal orientations (performance-approach versus performance-avoidance goals) on their learning performance, in-game performance, self-efficacy, fear of failure, and learning perceptions. The participants were 56 university students, who were divided into a performance-approach group (PAPG) and a performance-avoidance group (PAVG). The study used quantitative analysis with data from English translation technique tests, log data from gaming sessions, and three questionnaires. It was found that the PAPG exhibited significant improvements in relatively difficult translation techniques (i.e., conversion), while the PAVG showed notable improvements in relatively simple translation techniques (i.e., polysemy). Furthermore, the PAPG outperformed the PAVG in in-game performance related to polysemy. This study enhances our understanding of the impact of performance goal orientations on both learning and in-game performance in English translation education, particularly within the context of DGBL.

This study developed a digital game-based learning system featuring three different badge mechanisms: expected badges, unexpected badges, and mixed badges. An experiment was conducted to investigate how these badge mechanisms affected both English pronunciation learning performance and in-game behavior. Sixty students participated in the study and were randomly assigned to one of three groups: the expected badge group (EBG), the unexpected badge group (UBG), and the mixed badge group (MBG). The results showed that learners across all badge groups significantly improved their English pronunciation learning performance. Moreover, learners in the MBG and EBG outperformed those in the UBG. Additionally, MBG learners surpassed UBG learners in most in-game behavior metrics. These findings suggest that integrating unexpected badges with expected ones can produce more pronounced effects, leveraging the benefits of both types of badges. Conversely, relying solely on unexpected badges may not yield such significant results.