Unraveling microbial signatures in the comorbidity of autoimmune diseases and depression.

The rise of artificial intelligence (AI) and generative AI technologies in second/foreign language (L2) education has received scholarly attention during recent years [, , , , –, ]. This growing interest stems from the transformative potential of AI and generative AI to reshape language learning and teaching practices across diverse contexts [, , , , ]. The inclusion of AI has brought about numerous changes in language education domains and has offered several implications for teaching and learning practices of L2 education [, , , , , , , ]. AI tools can provide immediate and individualized feedback and learning content tailoring to learners' needs and motivational desires [, ]. Building on such benefits, a growing body of research has investigated practical applications and impacts of AI systems. For instance, Derakhshan and Taghizadeh [] examined the effect of AI on L2 students’ higher-order thinking skills through a phenomenological approach. The results indicated that AI can both enhance and hamper the growth and development of higher-order thinking skills in L2 learners. In another study, Liu and Ma [] explored the extent to which L2 learners incorporate AI tools, namely ChatGPT and Bing Chat, into their digital language learning. The results revealed that perceived use and ease of use affected learners' adoption of AI. Additionally, three themes regarding the actual use of chatbots as tutors, the relationship between chatbot benefits and increased intention to use them, and chatbot ease of use were identified. While much of the research has focused on behavioral and cognitive aspects of AI use, AI technologies also play a role in influencing the psychological and affective factors of L2 learners []. In this sense, recent studies, drawing on positive psychology (PP) and control value theory (CVT), have illustrated that the integration of AI in language education brings about diverse positive and negative emotions in both teachers and learners [, , ]. Since AI entails novel teaching and learning approaches, it can cause diverse affective states in language learners [, ]. Early studies have shown that AI can influence emotions such as enjoyment, anxiety, and stress and affective-motivational states like engagement and motivation [, , , , ]. Within this direction, Seyri and Ghiasvand [] explored EFL teachers’ emotions and their regulatory strategies in AI-enhanced L2 instruction. The findings illustrated that both positive and negative emotions were experienced during AI inclusion. Moreover, teachers were found to use both up-regulating and down-regulating strategies to control their emotions. Focusing on learners, Yang and Zhao [] investigated the emotions of 498 EFL learners and their regulation strategies through open-ended questionnaires and semi-structured interviews. The results showed that an array of positive and negative emotions was experienced during AI-based learning. Additionally, learners utilized antecedent-focused and response-focused strategies to regulate their AI-induced emotions.