DOI: 10.1177/21582440261493235 ISSN: 2158-2440

Exploring the Emotional Effects of Background Music on EFL Learners’ Lexical Access: A Quantitative–Qualitative Approach

Yu Guo, Zilong Zhong

Background music is commonly present in technology-enhanced learning environments, yet its effects on second language (L2) processing remain inconclusive, particularly with respect to the emotional qualities of music. The present study investigated the influence of background music with different emotional valences (positive, none, and negative) on L2 lexical access among Chinese learners of English as a foreign language (EFL). Using a one-way, three-level within-subjects design, forty Chinese EFL undergraduates completed a semantic categorization task under three background music conditions. Reaction time and accuracy served as dependent measures and were analyzed using linear mixed-effects models. The results revealed a significant effect of background music emotional valence on L2 lexical access. Negative emotional background music significantly reduced categorization accuracy and slowed reaction times compared with the no-music condition, indicating a clear inhibitory effect within the present task context. In contrast, positive emotional background music facilitated faster semantic categorization responses relative to silence, although accuracy did not significantly differ from the no-music condition. Participants’ post-task reflections further suggested that positive music was associated with engagement and mood, whereas negative music was associated with perceived distraction and cognitive burden. These findings suggest that background music may not function as a neutral contextual factor in L2 lexical access; rather, its emotional characteristics may influence cognitive processing during short-term semantic tasks. The study contributes to research on music-language interaction by highlighting the potential importance of emotional valence in background music and offers preliminary, task-specific implications for the design of technology-enhanced language learning (TELL) systems, particularly with regard to adaptive and learner-controlled auditory environments.