The rise of large language models has profoundly reshaped translation production practices, presenting a significant challenge to traditional translation training systems. This paper, oriented towards the objectives of knowledge, skills, and critical thinking, proposes a pedagogical framework driven by large language models for human-machine collaborative translation. The framework comprises a four-stage teaching pathway of translation diagnosis, prompt design, multi-round interaction and project practice, and adopts a comprehensive evaluation method, aiming to promote the intelligent transformation of translation education and cultivate innovative translators in the AI era.

As an essential higher-order capacity for foreign language learners, meta discourse awareness provides vital support for fostering high-quality foreign language professionals. Drawing on the findings from the research on English-Chinese discourse contrastive analysis, this paper proposes a content framework and its implementation strategy for cultivating meta discourse awareness. The framework operates at the micro, meso and macro levels, and comprises five key factors, namely structural awareness, semantic awareness, genre awareness, critical awareness and intercultural awareness. To implement the framework, the metacognition driven input-output strategy is adopted. With metacognition in the central organizing position, the strategy emphasizes clear goal orientation and self-regulatory ability development through discourse input and output. Its core lies in the bidirectional adjustment by teachers and learners via continuous reflection and feedback, thereby facilitating the effective transfer from English-Chinese discourse knowledge to intercultural discourse processing competence.

This study adopted a systematic review approach and analyzed the research methods employed in empirical studies in the field of applied linguistics from the perspective of complex dynamic systems theory (CDST). It summarized and discussed the research designs, participants, timescales and data collection methods, as well as data analysis methods. The analysis showed that the domestic and foreign CDST studies were featured with trends toward interdisciplinarity, paradigm integration and methodological innovation, though they differed in participant selection and design implementation.Domestic studies were primarily based on small-scale quantitative designs, focusing mainly on second language development at the tertiary level, with relatively limited data collection and analytical methods; in contrast, international studies involved larger sample sizes, covered learners at different educational stages, and used more diverse methods of data collection and analysis. It is suggested that future research should enrich theoretical perspectives, adopt integrated designs, and employ interdisciplinary methods to further reveal the dynamics and complexities of complex systems.

Intelligent chatbots are emerging technological tools for second language acquisition, though their effects on language acquisition remain controversial. Using meta-analysis, this study examines the overall and moderating effects of 35 experimental and quasi-experimental studies on application of intelligent chatbots to second language acquisition in the past decade. The results show that: (1) the overall average effect value is 0.677, exhibiting a large effect on language learning; (2) the moderating variables such as learning stages, teaching cycles, intelligent chatbot features (including interfaces and interaction modes), and second language skills produce significant effects on language learning, while learning situations have no moderating effect. The study provides implications for applying intelligent chatbots to second language teaching.

Machine translation literacy has emerged as a frontier topic in translation studies in the human-machine collaboration era, but assessment tools for machine translation literacy remain underdeveloped. This study attempts to construct a machine translation literacy scale consisting of 5 dimensions and 18 indicators, and examines its reliability and validity. The dimensions include human-machine translating knowledge, human-machine translating strategies, pre-editing techniques, post-editing techniques and human-machine relationship understanding. The statistical results indicate that the scale demonstrates good convergent validity, discriminant validity, and internal consistency reliability. The machine translation literacy scale may provide reference for quantitative assessment in translation education and practice.

Construction of China's independent knowledge system for foreign language education would meet the present requirements of strengthening foreign language education's capacity in addressing national strategic priorities, while offering a crucial pathway to overcome the challenges of foreign language programmes. This study analyzes the rationale and core principles underpinning the independent knowledge system. It then proposes pathways for its construction from four key dimensions of diversifying disciplinary concentrations, innovating curriculum content, enhancing faculty expertise, and developing pedagogical resources. China's independent knowledge system for foreign language education would benefit its transformation of talent cultivation modes, and improve its ability in building China into an education powerhouse.

Speech perception is a cognitive process that integrates visual and auditory modalities. Observers process prominent information through visual (e.g. facial expressions) and auditory (e.g. prominence) cues. Based on the McGurk effect theory, this study investigates Chinese EFL learners' audiovisual perception of English and Chinese prominence by measuring reaction time and accuracy. The results reveal that the congruent audiovisual cues have the strongest effect on prominence perception. It is easier for EFL learners to judge Chinese prominence than English prominence, showing native language advantage. Under audiovisually congruent conditions, EFL learners' audiovisual perception patterns of English prominence closely approximate those of native speakers. It is faster and easier to detect prominent words in the non-final positions of a sentence than those in the final position. The study provides foundational data for human-computer interaction research, offering practical application value in fields such as intelligent education and medical rehabilitation.

This one year longitudinal study involves two cohorts of undergraduates at a Chinese university: 2 673 students from the 2022 cohort and 2 272 students from the 2023 cohort. It uses a self-developed GenAI-powered personalized adaptive learning system ZJU E-Lang, and examines its role in improving EFL listening and reading abilities from the perspectives of learning outcomes and students' perceived effectiveness. The findings indicate that the GenAI-powered system significantly enhanced students' English listening and reading abilities. However, a clear novelty effect was observed, with substantial progress during the first half of the year followed by a slowdown in the second half. Students' perceptions of the GenAI-powered system varied by discipline, but disciplinary backgrounds did not interact with GenAI-facilitated learning effects. The positive effects of the GenAI-powered system in supporting language learning provide enlightenment for the deep integration of human intelligence and artificial intelligence in foreign language teaching.

With the accelerating process of globalization, the demand for talents with international competence has become increasingly pressing, while college foreign language education plays a pivotal role in cultivating such talents. Adopting an educational design research approach, this study draws on relevant frameworks at home and abroad, and aligns with the disciplinary characteristics of college foreign language education in China. Through questionnaires, interviews, expert consultations and teaching practices, the study defines international competence in college foreign language education, constructs a competence framework encompassing three dimensions of values, knowledge, and skills, and outlines 15 key elements. Based on the framework, it proposes corresponding implementation pathways, aiming to provide theoretical foundations and practical insights for cultivation and assessment of international competence in college foreign language education.

This paper systematically reviews the empirical literature on language teacher identity from the CSSCI and SSCI databases (2014-2024), and provides a comprehensive analysis of the research methods employed, with particular emphasis on the techniques for enhancing the quality of qualitative research and the ways in which the quality is reported. The main findings are as follows: (1) both Chinese and English-language literature feature qualitative research, with a wide use of interviews, observations and written materials to gather data, but Chinese literature also presents a more diverse range of research paths, including quantitative and mixed-methods research. (2) Case studies dominate qualitative research in both Chinese and English literature, with a rising trend of narrative research focusing on exploring language teacher identity from open and exploratory perspectives. (3) Qualitative research in both Chinese and English literature employs various quality-enhancing methods, such as triangulation and member check to enhance research credibility, while the use of quality terminologies is insufficient and inconsistent, and English literature shows the tendency to develop quality assessment standards applicable to qualitative research. The paper reveals the similarities and differences between Chinese and English empirical research on language teacher identity in terms of research methods, quality strategies, and terminological reporting, providing reference and enlightenment for advancing methodological awareness and standardization in teacher identity research.

Fostering moral ethics through education and developing students' disciplinary and cross-disciplinary competencies is a key agenda for cultivating talents for the “Four New Disciplinary Initiatives” and a core component of curriculum reform. This paper focuses on the development of AI-enhanced College English courses. Taking a national excellent course as an example, it introduces an AI-enhanced College English course integrating AI technology with the course content. Through functions such as the construction of multi-dimensional knowledge and competency graphs, human-computer collaborative teaching and learning, full-cycle support from virtual teaching assistants and virtual teachers, and intelligent data feedback, the course promotes the cultivation of College English language and interdisciplinary competencies geared towards the “Four New Disciplinary Initiatives”, thereby realizing the transition from knowledge acquisition to intelligence growth in College English teaching.

Against the backdrop of rapid technological advancement in artificial intelligence (AI), the knowledge framework of university foreign language teachers is in urgent need of transformation. Based on in-depth interviews with eleven foreign language teachers from different types of universities, this study investigates the connotation elements of teachers' AI-integrated Pedagogical Content Knowledge (AI-PCK). Drawing on the ecological systems theory, it also analyzes influencing factors of teachers' AI-PCK. Findings indicate that AI-PCK consists of seven core knowledge elements, namely AI Knowledge (AI-K), AI-integrated Foreign Language Teacher Knowledge (AI-FLTK), AI-integrated Student Knowledge (AI-SK), AI-integrated Foreign Language Teaching Objective Knowledge (AI-FLTOK), AI-integrated Foreign Language Subject Content Knowledge (AI-FLSCK), AI-integrated Foreign Language Teaching Strategy Knowledge (AI-FLTSK), and AI-integrated Foreign Language Teaching Assessment Knowledge (AI-FLTAK). They are influenced interactively by ecological factors at macro, exo, meso, and micro levels. The study concludes by proposing development paths of teachers' AI-PCK, offering practical implications for university administrators and teacher educators to formulate evidence-based policies and promote foreign language teachers' professional development.

AI-enabled educational revolution has reshaped education models, and has shifted foreign language teachers' roles to “learning facilitators” and “human-machine collaborators”. This paper reviews policies, curricula, and research trends regarding AI in education in Asia, Europe and the Americas, and analyzes the applications and challenges of AI in education across different cultural contexts. Based on the analysis, it proposes a human-centered approach to enhancing foreign language teachers' AI competency, emphasizing ethics and digital inclusion. The stepwise pathway aims to support teachers' professional development and improve the quality of education in the AI era.

The development of China's higher foreign language education has always been closely aligned with national strategies. This paper begins with a concise review of the evolution of higher foreign language education since the reform and opening-up, revealing the historical logic behind its service to national strategies. On this basis, it argues that the new connotation of higher foreign language education has shifted toward playing a foundational and strategic supporting role in pursuing the cause of building China into a leading country in education. Against the backdrop of national rejuvenation and digital-intelligent technological transformation, the paper proposes for higher foreign language education a trinity of development coordinates, grounded in “Chinese perspective, mutual learning among civilizations, and AI integration”. Through systematic self-innovation and accelerated transformation, higher foreign language education should commit to cultivating new-type foreign language professionals capable of meeting the critical national needs, and proactively respond to the requirements of the times within the broader context of “advancing the rejuvenation of the Chinese nation on all fronts through a Chinese path to modernization”.

Based on a questionnaire survey among 237 Chinese non-English major undergraduates, this study employed structural equation modeling to investigate the predictive effects of controlvalue appraisals on second language (L2) academic achievement and the chained mediating roles of L2 grit and academic emotions (enjoyment, anxiety, and boredom) in between. The results are as follows: (1) within controlvalue appraisals, only value appraisals exerted a direct predictive effect on English academic achievement; (2) control appraisals fostered L2 enjoyment, which subsequently exerted a positive predictive effect on achievement, whereas value appraisals triggered L2 anxiety, negatively predicting achievement; (3) control appraisals had an indirect predictive effect on English academic achievement by the chained mediation of L2 grit and academic emotions. The study corroborates the hypothesized quadripartite relational chain comprising “appraisal-driven, trait-shaping, emotion-triggering, and achievement-enhancing” mechanisms, revealing the mediating roles of academic traits and emotions in linking “evaluation to academic performance”.

Based on the Complex Dynamic Systems Theory (CDST), this study investigates the emergence and dynamics of multi-dimensional features in L2 discourse development. Argumentative essays written by 83 Chinese English-as-a-foreign-language (EFL) learners over a semester were collected, and multi-dimensional analysis and longitudinal clustering methods were used. The results showed that two discourse types emerged from longitudinal cluster analysis, namely expositive persuasion and interactive persuasion. The former is more situation-explicit, abstract, informational, and less involved, while the latter shows the opposite features. A person-centered approach revealed three developmental profiles of L2 discourse, namely stable, fluctuating, and transitional profiles. They each exhibit distinct multi-dimensional interaction patterns, showing an overall tendency towards academicization. Implications regarding the pedagogy of argumentative discourses in the Chinese EFL context are discussed.

Based on the experimental data from 137 Vietnamese-Chinese bilinguals, this study investigates how the foreign language effect manifests under different types of moral norms and levels of social distance. The results show that: (1) the moral foreign language effect is widespread, but its intensity may be influenced by linguistic features and cultural perceptions; (2) the effect remains consistent across different types of moral norms, and foreign language use leads to more lenient moral judgments on behaviors with varying normative attributes; (3) foreign language use weakens the influence of social distance on moral judgments, and the farther the social distance, the stronger the effect. The study verifies the general presence of the moral foreign language effect, and deepens the understanding of its manifestations and underlying mechanisms.

This paper proposes a new model of translation revision competence by integrating key elements of translation competence and translation revision competence. The specific components of the model include cognitive competence, strategic competence, assessment competence, the spirit of truth-seeking, the spirit of utility-attaining, common elements of translation competence and unique elements of translation revision competence. It incorporates the translator's self-revision, which is often excluded by Western scholars, and can explain various types of translation revision, such as monolingual revision and literary translation revision. Its distinctive feature lies in the openness of components, so that each type of translation revision can activate corresponding sub-competences. The model has both theoretical and practical value, offering insights for understanding relevant theoretical translation concepts and cultivating translation talents.

This study employs a self-paced reading experiment to examine how context types and foreign language proficiency affect the processing of metaphors in a foreign language. The results show that for positive metaphors, both the metaphorical and literal meanings are accessed simultaneously, whereas for ironic metaphors, the metaphorical meaning is accessed after the literal meaning, indicating a staged processing characteristic. Although both positive and ironic metaphors are non-literal, their cognitive mechanisms differ in that ironic metaphors require more cognitive resources from EFL learners. Regardless of metaphor types, advanced learners process metaphors faster than low proficiency learners, while the relationship between language proficiency and metaphor processing is dynamically mediated by cognitive abilities.

Over the past decades, Chinese linguistics has undergone a process of “integration” and “contestation” with Western linguistic theories, and has made remarkable advancements, yet with limited recognition in the international academic community. This paper briefly reviews the status quo of construction of Chinese linguistic discourse system, and highlights the existing major issues. It then proposes a theoretical framework for establishing Chinese linguistic discourse system in the new era from three dimensions, namely system concepts and structures, comparative approaches and paths, and strategies and guarantees, and explores effective paths for breaking free from Western discourse dependency. It is hoped that the paper would shed some light on constructing Chinese linguistic discourse system and a linguistic academic community, and ultimately enhancing China's international discourse power in linguistics.

Guided by the activity theory, this study employs a qualitative case study approach to conduct a three-year longitudinal tracking of three MA students majoring in foreign languages, exploring the characteristics of agency in academic research activities during their MA studies. The findings reveal that the academic research agency practices of the MA students are carried out via their growth will, goal-oriented approaches, and practice objectives. These practices are realized by means of marginal observation and centripetal perception, and iteratively influence future activities under the mediating effects of various elements within the activity system. Investigating students' academic research agency helps extend the collaborative dialogic space between teachers and students in the academic research field, stimulating new educational capabilities of university MA programmes.

This paper introduces cases of China's theoretical innovations in interpreting competence (a critical issue of interpreting professionals education), with special emphasis on the Interpreting Competence Scales and Attentional Control in Interpreting. The former illustrates the construct of interpreting competence from the perspectives of teaching and evaluation, while the latter exemplifies the underlying mechanism of interpreting competence. The paper then summarizes China's innovations in the practice of interpreting professionals education, including professional standardization, teaching modes and methods, evaluation systems, and industry standards. These innovations, prompted by the unique local issues, serve to enhance the understanding of an independent knowledge system for foreign language education in China, and have implications for interpreting professionals education in the AI age.

Oral accuracy is a key index of second language (L2) acquisition research and pedagogy. This paper reviews the cutting-edge developments and core issues in international L2 oral accuracy research in the past three decades. It identifies three major research strands: (1) the interactive mechanisms among accuracy, complexity, and fluency, (2) internal and external factors influencing oral accuracy, and (3) methodological approaches to measurement of oral accuracy. The paper concludes by calling for future research grounded in theoretical integration, oriented toward the standardization of measurement practices, and leveraging artificial intelligence to advance the field toward greater theoretical depth and empirical breadth.