Scientific research has progressed through experimental, theoretical, computational, and data-intensive paradigms, and is currently advancing toward the fifth paradigm: artificial intelligence-driven scientific discovery. AI is not only an auxiliary tool but also a collaborator and inspirer in knowledge production. Language research, due to the unique nature of its object, is at the forefront of this transformation. The fifth paradigm of language research is essentially a systematic reconstruction of language research “human-machine collaborative generation mechanism.” In knowledge production, this manifests in four fundamental shifts: the cognitive subject is reconstructed from human researchers to a human-AI composite cognitive system; the generation mechanism shifts from an interpretative model to a generative mechanism; the production structure shifts from a linear process to a cyclical system; and the presentation form shifts from rule-based to distributed, parameterized probabilistic representations. In research practice, this transformation manifests in five key areas: the research object has expanded from human language to human-machine hybrid language; in terms of methodology, AI is not only the object of analysis but also a methodological tool for generating data, conducting simulations, and assisting in analysis; the research goal is not only to understand human language but also to construct language intelligent agents capable of generating, understanding, and interacting; the research subject has upgraded from individual scholars to human-machine collaboration; and the disciplinary structure has shifted from a single discipline to a multidisciplinary integration. This transformation brings significant opportunities for language research, such as a leap in research capabilities and room for theoretical innovation. However, it also brings profound challenges, including an interpretive crisis, weakening of theories, concentration of knowledge power, risks to the language ecosystem, and ethical issues. Faced with the systemic reconstruction of the fifth paradigm, language researchers should not merely be followers of methodology, but rather critics of technological governance and builders of language ethics, maintaining human initiative and upholding ultimate human rights.
Bai Shuo (2025) recently proposed that we should delve deeper into the first principle of language to create “small yet efficient” low-resource language models and argued that whether language is “learned” is not the essence of Chomskyan linguistic theory. We hold that, in contrast, “linguistic innateness” is the first principle of Chomskyan linguistic theory, since it is essential for humans’ innate “linguistic faculty” to endow humans with recursive abilities, allowing “infinite use of finite means”. The language ability of large language models, however, is learned, and their success is based on “finite use of infinite data”. As far as language technology and language engineering are concerned, it is infeasible or unworkable at this stage to construct “small yet efficient” language models on the first principle of language. While the theory of humans’ innate linguistic faculties still lacks sufficient scientific evidence, the statistical learning theory currently strives to prove that the brains of human infants can perceive external objects, acquire knowledge, and learn language through a conceptual system. The criticism of large language models and the pursuit of “small yet efficient” language models from the linguistic perspective that “language is not learned but an innate ability” may reflect a weakness in scholarly thinking, namely, the “theory-induced blindness”. As surveys and experiments guided by the theory of constructed emotion reveal, what classical emotion theories refer to as emotional universality, often regarded as fact by researchers, is actually the effect of experimental designs. This serves as a wake-up call for the study of universal grammar.
Across its long intellectual history, from prescriptivism and descriptivism to structuralism and generative grammar, linguistics has the ultimate goal of modelling the internal language faculty of the human mind. Despite the accumulation of extensive body of micro-level findings, a substantial gap persists between such fragmented insights and the construction of a holistic model of human language as a cognitive system. Since the 1950s, the dominant paradigm trajectory in artificial intelligence has evolved from symbolism through empiricism to connectionism. Although contemporary large language models (LLMs), powered by leveraging massive computation and vast datasets, can model human language at unprecedented computational power, they remain limited in capturing the deep cognitive regularities that are not fully encoded in surface distributions and therefore still fall short of native-speaker competence in extracting and internalizing deeper cognitive and semantic regularities that are weakly expressed in surface distributions alone. In this context, it opens a critical space for collaboration. Linguists, drawing on their theoretical sensitivity to subtle semantic, pragmatic, and structural phenomena, can contribute by leveraging domain-specific insight to uncover the deep semantic issues embedded in micro-level linguistic phenomena and to transform linguistic knowledge into high-quality, structured data for improving AI’s linguistic capabilities. At the same time, AI offers linguistics the possibility of moving beyond observational, descriptive, and explanatory adequacy toward generative adequacy. Consequently, the automated transformation of theoretical research into interactive linguistic data—evolving from manual to fully autonomous processes—constitutes a central challenge for linguists in the AI era, and addressing this challenge is essential if linguistics is to play a constitutive role in the next stage of language modelling.
International Chinese Language Education (ICLE) is entering an era of diversity featuring the coexistence of three groups of learners, i.e., native speakers, heritage language speakers, and foreign language learners. According to surveys and estimates, Chinese-origin native and heritage language speakers account for approximately 70% of all learners, while non-Chinese-origin foreign language learners are split roughly equally between adults and young learners at around 15% for each. Previous research on ICLE has focused heavily on adult foreign language learners and failed to fully reflect its global landscape. There is an urgent need to adjust research directions to adapt to this new situation. Currently, research on native speakers remains extremely scarce and is in urgent need of comprehensive development. Studies on heritage language speakers are relatively more numerous, yet they focus primarily on heritage language maintenance, to the neglect of heritage language acquisition. In the past, research on foreign language learners has paid little attention to the growing number of young learners. Meanwhile, research on the needs for Chinese in professional and technical learning is also inadequate. Future research directions should be adjusted to focus on seven major areas: studies on the learning needs of the “three groups of learners”, studies on learning patterns, research on learning content, investigations into learning interaction, as well as the supporting research in language assessment, teacher development, and the coupling between the “symbiosis of three types of people” and the “three groups of learners”. It is necessary to proceed from reality and redefine ICLE in light of the diverse landscape of Chinese language learning. To support the adjustment of research directions, efforts should be made to promote the development of a global database of Chinese language learners for in-depth and refined research.
A clear and accurate professional positioning is crucial for improving both the quality of academic program development and talent cultivation in higher education. Focusing on the positioning of undergraduate programs in Teaching Chinese to Speakers of Other Languages within the framework of the “Double Ten-Thousand Plan”, this study investigates 24 national-level program construction sites through their official program information forms, as well as interviews with program directors or department heads from 13 of these institutions. A thematic analysis of the texts and interview data reveals that program positioning should be based on the needs of three main stakeholders: society, universities, and students, and include five key themes—talent cultivation, professional development planning, professional roles, serving regional and national needs, and strengths and unique features—each corresponding to one of five guiding orientations for program development. Based on the combinations of these themes, ten types of professional positioning can be identified. The characteristics of these positionings include: talent cultivation as the core element, a focus on the program’s practical and international dimensions, and increased attention to development planning goals. However, the study finds that most construction sites still face key challenges: their positioning is not well aligned with the requirements of the “Double Ten-Thousand Plan”; their understanding of professional positioning remains unclear; they lack a strong sense of their own advantages and unique features; and their approach to talent cultivation is not keeping up with contemporary trends. In the future, it is necessary to clarify the foundational role of undergraduate education within the overall talent cultivation system of international Chinese language education, specify the key elements of professional positioning, place emphasis on “social” and “distinctive” orientations, and address both graduate career pathways and societal needs.
Compared with second-generation immigrants born in the host country, the so-called 1.5 generation immigrants—those who migrate during childhood or early adolescence with their parents—generally face the dual challenges of heritage language attrition and the reconstruction cultural identities. This study focuses on 1.5-generation Chinese immigrants who moved to Australia between the ages of 4 and 13. Drawing on the critical period hypothesis and a “time–space–identity” model, it examines how age at migration shapes distinct language trajectories and identity formations through spatiotemporal interaction. Based on data collected from 25 adolescents and their parents through family questionnaires, interviews, ethnographic observations, and voluntarily provided written materials, the study reveals: (1) Children who migrated between ages 4 and 7 typically undergo systematic attrition of Chinese and tend toward an Australian dominant, unidirectional identity orientation;
(2) Those who migrated between ages 8 and 10 generally retain basic oral Chinese proficiency but experience a precipitous decline in literacy, accompanied by instrumental orientation of cultural identification; and (3) Adolescents who migrated between ages 11 and 13 demonstrate fluent spoken Chinese but limited academic literacy, resulting in a functional division between “everyday Chinese” and “academic English”, alongside a pronounced ethnic identity and ongoing processes of identity reconstruction. Overall, the findings reveal a clear “age gradient effect” and propose a tiered intervention model—remedial, transitional, and integrative—to support heritage language retention and identity development. This research offers theoretical grounding and policy insights for international Chinese language education in overseas Chinese communities.
In Chinese dictionaries, it is necessary, feasible, dynamic, and complex to generalize the meanings found in single character entries so that they fully cover the morphemic meanings involved in multi character entries. This mechanism is essential for constructing a lexicographical knowledge network and helping readers understand the motivations behind word formation in commonly used words. Decades of compilation and revision experience with the Modern Chinese Dictionary has shown that this goal can be effectively achieved by adding new sense items or refining definitions. Whenever a dictionary adds multi character entries, it must take into account whether the single character entries adequately cover the corresponding senses. Given the complexity and ambiguity of semantic relations, certain associations may be temporarily omitted if unclear; otherwise, it is necessary to summarize and establish such connections. There are five main methods to achieve this: defining and summarizing shared semantic components; providing definitions combined with related multi character words; explaining meanings using synonymous multi character words; co-interpreting with two related multi character words; and illustrating associations with examples of multi character words formed from shared morphemic meanings. To further improve quality, authoritative dictionaries need to supplement or fine tune new words whose senses exist in multi character entries but are absent in single character entries, continue to add and enhance well-accepted new words and meanings, and maintain consistency between the characters in the main word forms of multi character entries and the standardized head characters of single character entries. To enhance the efficiency and scientific rigor of compilation and revision, it is urgent to optimize computer aided lexicographical database platforms. Authoritative dictionaries should innovate their compilation and revision paradigms, accelerate the improvement of high quality content, and better meet social needs.
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Directed by: The National Language Committee of China Supported by: China Association for Language Policy and Planning Administered by: China Publishing and Media Holdings Co.,Ltd. Sponsored by: The Commercial Press, Ltd. ISSN 2096-1014 CN 10-1361/H Edited by: Board of Chinese Journal of Language Policy and Plarming(36,WangfujingSt.,Beijing 100710, China) Tel: 86-10-65219060/65219062