Allen Jie Ein Chee

University of Nottingham Malaysia, Malaysia

Csaba Zoltan Szabo

University of Edinburgh, UK

Sharimila Ambrose

University of Nottingham Malaysia, Malaysia

Abstract

Teachers are expected to model emotional literacy and manage classroom affect (Teng, 2017), yet little is known about their ability to produce nuanced emotion vocabulary. In an online survey of 101 ESL/EFL pre- and in-service teachers, we administered a 25-item vignette-based productive emotion vocabulary task (PEVST; two responses per item) alongside LexTALE (proficiency) and the TEIQue-SF (trait EI). Teachers produced high-frequency emotion vocabulary accurately (≈78–81% in the 1k–3k bands), but performance declined for mid-/lower-frequency items (≈45% at 4k/6k, 26% at 9k), indicating strong frequency constraints. LexTALE showed a moderate positive association with PEVST accuracy (about r ≈ .41–.43, depending on the scoring method). In OLS regression (R² = .24), LexTALE emerged as the strongest predictor, while Emotionality contributed a smaller positive effect; the LexTALE × Emotionality interaction did not improve model fit, supporting additive rather than moderating effects. The results suggest that even largely advanced teachers may have limited productive access to lower-frequency emotion vocabulary, motivating more explicit teachereducation and curricular attention to nuanced affective labelling.

Keywords

Emotion vocabulary, language teaching, language assessment, emotion recognition, emotional intelligence