As the forerunners of education, teachers and their psycho-affective variables have been the focus of numerous studies in the past decades. To add to this line of inquiry, the present study aimed to scrutinize the correlation among English as a foreign language (EFL) teachers' self-efficacy, work engagement, and reflection in the context of China. To do so, three previously validated questionnaires related to each of the variables were distributed among Chinese EFL teachers with various experiences and academic degrees, and a sample of 614 completed the questionnaires. The results of Pearson's Product-moment correlation revealed that the participants' self-efficacy, work engagement, and reflection were positively correlated. Moreover, the results of regression analysis and ANOVA demonstrated that Chinese EFL teachers' self-efficacy and work engagement significantly predicted their reflection. The findings have viable takeaways for EFL teachers and teacher education programs in that they can invest more time and energy in promoting psychological factors in teaching the English language along with pedagogical issues.

Artificial intelligence (AI) offers new possibilities for English as a foreign language (EFL) learners to enhance their learning outcomes, provided that they have access to AI applications. However, little is written about the factors that influence their intention to use AI in distributed EFL learning contexts. This mixed-methods study, based on the technology acceptance model (TAM), examined the determinants of behavioral intention to use AI among 464 Chinese EFL college learners. As to quantitative data, a structural equation modelling (SEM) approach using IBM SPSS Amos (Version 24) produced some important findings. First, it was revealed that perceived ease of use significantly and positively predicts perceived usefulness and attitude toward AI. Second, attitude toward AI significantly and positively predicts behavioral intention to use AI. However, contrary to the TAM assumptions, perceived usefulness does not significantly predict either attitude toward AI or behavioral intention to use AI. Third, mediation analyses suggest that perceived ease of use has a significant and positive impact on students’ behavioral intention to use AI through their attitude toward AI, rather than through perceived usefulness. As to qualitative data, semi-structured interviews with 15 learners, analyzed by the software MAXQDA 2022, provide a nuanced understanding of the statistical patterns. This study also discusses the theoretical and pedagogical implications and suggests directions for future research.

The adequacy of language education largely depends on the favorable and unfavorable emotions that teachers and students experience throughout the education process. Simply said, emotional factors play a key role in improving the quality of language teaching and learning. Furthermore, these emotional factors also promote the well-being of language teachers and learners and place them in a suitable mental condition. In view of the favorable impact of emotional factors on the mental health of language teachers and learners, many educational scholars around the world have studied these factors, their background, and their pedagogical consequences. Nonetheless, the majority of previous studies have employed traditional research methods in assessing these variables and their influences on language teachers’ and learners’ mental health. Because of the complex and dynamic quality of emotional factors, traditional research approaches often fail to evaluate these factors and their dynamic, non-linear connections with teachers’ and learners’ mental health and well-being. Accordingly, some novel research approaches are required to measure the dynamicity and complexity of emotional factors in language education settings. To address this call, the current state-of-the-art conceptual article seeks to provide new insights for investigating emotional factors and their potential impact on language teachers’ and learners’ mental states. This study also intends to offer a comprehensive list of emerging methods that take into account the complex and dynamic nature of emotional variables. Finally, the study outlines the potential implications of this review for educational researchers.