A Bayesian probabilistic analysis of the use of English modal verbs in L2 writing: Focusing on L1 influence and topic effects

Abstract

Modal verbs, with their multifaceted semantic nuances and varied grammatical configurations, present notable challenges for L2 learners and regularly intrigue L2 researchers. This study attempts to investigate and compare how English modal verbs are used by L2 learners from different L1 backgrounds. By exploring the Turkish and Chinese learners’ subcorpora of the International Corpus of Learner English (ICLE), this work scrutizes the overall frequencies of nine core English modal verbs as grouped into three major semantic classes along with the influential lexico-syntatic variables that are semantic classes of collocated verbs, grammatical patterns and subject pronominality. The results of a Bayesian probabilistic analysis show that both the Turkish and Chinese learners primed similar modal verbs and constructional preferences without topic as the normalizing factor. While the broader analysis reveals no statistically significant divergences between these two learner groups in English modal verb preferences, a pronounced contextual influence is evident when the dataset narrows to essays on a unified theme. This nuanced shift underscores the intricate relationship between essay topics and linguistic structures, thus emphasizing the pivotal role of context in modal verb usage.