AI-Related Language Learning Practice and Second Language Investment: Quantitative Evidence from Yemeni Postgraduate Students in India

Second language (L2) investment is shaped by multifaceted interaction of identity, capital, and ideology. Despite the growing use of artificial intelligence (AI) in language learning, little quantitative research has examined whether AI-related language learning practices are associated with perceived second language (L2) investment among international students. This study bridges this gap by investigating the perceived usefulness of AI-related tools for language learning, learners’ perceived L2 investment, the relationship between these two constructs, and whether English-major and non-English-major Yemeni postgraduate students (YPSs) differ in their perceptions towards L2 investment. A closed-ended questionnaire was administrated to a convenience sample of 78 YPSs studying in India. The results revealed a high level of AI usefulness for English language learning (M = 4.02), and a high level of perceived L2 investment (M = 4.14) among YPSs in India. Across the three dimensions of L2 investment, L2 Capital received the highest mean score (M = 4.27), followed by L2 Ideology (M = 4.14), and L2 identity (M = 4.02). The results further revealed the existence of a strong, positive, and statistically significant correlation between the self-reported AI-related language learning practices and perceived L2 investment (r = .669, p < .001). Notably, the Mann-Whitney U test indicated no statistically significant difference in perceived L2 investment between the perceptions of English-major and non-English-major YPSs (U = 634.00, p = .880). The findings provide quantitative evidence that AI-related language learning practices are positively associated with postgraduate L2 investment, showing greater emphasis placed on the instrumental and socio-economic value of English than on identity-related aspects.