ABSTRACT The influence of (trait) emotional intelligence (TEI) on academic achievement has been documented in literature, while its influence in the specific domain of L2 learning remains underexplored. The link between EI and negative emotions especially anxiety has been studied in different contexts including applied linguistics. However, it remains unknown how EI is related to positive emotions in L2 learning. Underpinned by theories and assumptions of Positive Psychology, the present study examined the complex relationships between 1307 Chinese high school students’ TEI, Foreign Language Enjoyment (FLE), and English-as-a-foreign-language (EFL) learning achievement. The following findings were obtained: (1) Most Chinese high school EFL students reported moderate to high levels of TEI, while low to moderate levels of FLE; (2) Small to medium correlations were found among students’ TEI, FLE, self-perceived English achievement and actual English achievement; (3) TEI was partially mediated by FLE to influence perceived achievement and actual achievement indirectly. The results were discussed in accordance with previous relevant findings as well as their theoretical and practical implications for L2 teaching and learning.
L. M. Amugongo, Pietro Mascheroni, Steve Brooks
et al.
Large Language Models (LLMs) have demonstrated promising capabilities to solve complex tasks in critical sectors such as healthcare. However, LLMs are limited by their training data which is often outdated, the tendency to generate inaccurate (“hallucinated”) content and a lack of transparency in the content they generate. To address these limitations, retrieval augmented generation (RAG) grounds the responses of LLMs by exposing them to external knowledge sources. However, in the healthcare domain there is currently a lack of systematic understanding of which datasets, RAG methodologies and evaluation frameworks are available. This review aims to bridge this gap by assessing RAG-based approaches employed by LLMs in healthcare, focusing on the different steps of retrieval, augmentation and generation. Additionally, we identify the limitations, strengths and gaps in the existing literature. Our synthesis shows that 78.9% of studies used English datasets and 21.1% of the datasets are in Chinese. We find that a range of techniques are employed RAG-based LLMs in healthcare, including Naive RAG, Advanced RAG, and Modular RAG. Surprisingly, proprietary models such as GPT-3.5/4 are the most used for RAG applications in healthcare. We find that there is a lack of standardised evaluation frameworks for RAG-based applications. In addition, the majority of the studies do not assess or address ethical considerations related to RAG in healthcare. It is important to account for ethical challenges that are inherent when AI systems are implemented in the clinical setting. Lastly, we highlight the need for further research and development to ensure responsible and effective adoption of RAG in the medical domain.
Sentiment analysis has emerged as a prominent research domain within the realm of natural language processing, garnering increasing attention and a growing body of literature. While numerous literature reviews have examined sentiment analysis techniques, methods, topics and applications, there remains a gap in the literature concerning thematic trends and research methodologies in sentiment analysis, particularly in the context of Chinese text. This study addresses this gap by presenting a comprehensive survey dedicated to the progression of research subjects, methods and trends in sentiment analysis of Chinese text. Employing a framework that combines keyword co-occurrence analysis with a sophisticated community detection algorithm, this survey offers a novel perspective on the landscape of Chinese sentiment analysis research. By tracing the interplay between research methodologies and emerging topics over the past two decades, our study not only facilitates a comparative analysis of their correlations but also illuminates evolving patterns, identifying significant hotspots and trends over time for Chinese language text analysis. This invaluable insight provides a roadmap for researchers seeking to navigate the intricate terrain of sentiment analysis within the context of Chinese language. Moreover, this paper extends beyond the academic realm, offering practical insights into sentiment analysis methodologies and themes while pinpointing avenues for future exploration, technical limitations, and directions for sentiment analysis of Chinese text.
IntroductionAgainst the backdrop of the Belt and Road Initiative, the demand for professionals proficient in Arabic and capable of cross-cultural communication has surged, yet the mechanism of how learners navigate the significant cultural distance remains underexplored. This study aims to investigate the relationship between learning motivation and cross-cultural adaptability among Chinese Arabic language learners, specifically examining the moderating role of social support.MethodsAdopting a quantitative survey design, data were collected from 315 undergraduate Arabic majors. The study employed Confirmatory Factor Analysis (CFA), hierarchical multiple regression, and Instrumental Variable Two-Stage Least Squares (IV-2SLS) analysis to test the hypotheses.ResultsFindings indicate that both learning motivation (B = 0.319, p < 0.001) and social support (B = 0.494, p < 0.001) significantly and positively predict cross-cultural adaptability. Crucially, social support functions as a significant moderator (B_interaction = 0.703, p < 0.001), with the final model explaining 74.2% of the variance. Simple slope analysis reveals that the positive association between motivation and adaptability is significant only under high levels of social support, acting as a necessary boundary condition. Further analysis based on Self-Determination Theory subtypes specifically highlights that this moderating effect is most pronounced for external regulation, suggesting that learners driven by instrumental goals are particularly dependent on external resources to translate motivation into adaptive outcomes. Robustness checks using IV-2SLS (B = 0.630) confirmed the stability of these associations.DiscussionTheoretically, this study extends the existing literature by identifying the boundary conditions under which motivation predicts adaptability, suggesting that internal drive and external support function together to facilitate adaptation. Practically, the findings indicate that higher education institutions should provide multi-dimensional support systems to assist students in translating their motivation into effective cross-cultural competence.
Xiaomi merupakan salah satu merek smartphone asal Tiongkok yang memiliki pasar di Indonesia dan menduduki peringkat ketiga dalam segi jumlah penjualan. Di Indonesia masih terlihat ada stereotip terhadap merek Tiongkok yang menimbulkan keraguan pembeli terhadap produk-produk dari Tiongkok. Oleh karena itu, penelitian ini akan membahas bagaimana persepsi merek dan harga mempengaruhi intensi pembelian smartphone Xiaomi pada masyarakat Tionghoa di Surabaya barat. Penulis menggunakan metode penelitian kualitatif dengan melakukan in-depth interview pada 12 narasumber, baik yang menggunakan smartphone Xiaomi maupun tidak. Hasil penelitian menunjukkan bahwa baik bagi pengguna smartphone Xiaomi maupun yang tidak, persepsi terhadap merek memiliki pengaruh yang lebih kecil dibandingkan dengan harga dalam mempengaruhi intensi pembelian mereka. Hasil penelitian menunjukkan bahwa orang Tionghoa di Surabaya barat memiliki kebiasaan berbelanja yang sangat berhati-hati dan penuh perhitungan. Melalui penelitian ini juga dapat terlihat bahwa pada sebagian orang Tionghoa Surabaya barat yang kurang memahami produk Tiongkok, stereotip terhadap merek Tiongkok masih ada.
AbstractThe present study has been conducted in the framework of Systemic Functional Grammar and on the basis of systemic functional typology, specifically Matthiessen’s typological generalizations. Based on examples taken from various written documents in Azeri Turkic such as grammar books and a series of stories as well as constructed examples, this study aims to describe the typological behaviors of the MOOD TYPE system in the clause structure of Azeri Turkic in terms of Matthiessen’s typological generalizations regarding the MOOD system. Some results of the present study indicate that Azeri Turkic MOOD TYPE system (1) has all the three declarative, polar interrogative, and imperative moods, (2) uses negative polar interrogatives to indicate the speaker’s positive bias, (3) belongs to the ‘languages that have the Wh-interrogative category’ type, (4) queries just the participants and circumstantial adjuncts in the Wh-interrogatives, (5) belongs to the ‘Wh-in-situ languages’ type, and (6) differentiates the imperative mood from the other mood types.IntroductionThis study, conducted within the framework of Systemic Functional Grammar and based on Matthiessen’s (2004) typology of MOOD TYPE system, as a subsystem within the interpersonal metafunction, aims to investigate and describe the MOOD TYPE system in Azeri Turkic, which belongs to the Southwestern branch of Turkic languages, also known as the Western Oghuz group. Grounded in systemic functional typology, this research seeks empirical generalizations applicable across languages. Matthiessen (2004) has developed descriptive generalizations through comparative analysis of the experiential, logical, interpersonal, and textual systems of various languages, identifying typological universals and variations. Following Matthiessen’s claim that these generalizations can be applied to any language within a Systemic Functional Framework, this study explores the realization of the MOOD TYPE system in Azeri Turkic. Data was collected from diverse sources, including short story collections, academic articles, grammar books on Azeri Turkic, and original examples provided by the researcher. The paper is structured into five sections: introduction, review of related literature, theoretical framework, analysis of MOOD TYPE in Azeri Turkic, and concluding remarks presenting the findings.Literature ReviewThis section reviews several studies on the clause type system, including Mirahmadi’s (2004) Systemic Functional analysis of Persian mood types, Pahlavannajhad & Vazirnejad’s (2004) stylistic study of mood types in Zoya Pirzad’s novel, Najm’s (2008) cross-linguistic comparison of English and Arabic imperatives and exclamatives, Figuerdo’s (2010) description of Portuguese mood types, and traditional grammatical studies on Azerbaijani Turkish by Li (1996), Ahmadi Givi (2004), Dehqani (2000), and Zahedi & Bayan (2008).Unlike previous studies, this research contributes to Systemic Functional Typology by analyzing mood types in Azeri Turkic through a functional lens, aiming to determine whether Matthiessen’s descriptive generalizations can be effectively applied to this language.ResultsThe findings of the present study show that Azeri Turkic identifies four major mood types—declarative, polar interrogative, content interrogative (Wh-questions), and imperative. This confirms Matthiessen’s generalization that declarative, polar interrogative, and imperative clauses are universal, while the presence of content interrogatives places Azeri Turkic among languages that distinguish this category. Polar interrogatives in Azeri Turkic appear in both biased and unbiased forms, marked by particles such as ɒjɒ ‘whether’ for neutral questions and mæjær, mæjæ, bæjæ, or bæ ‘don't/doesn't, didn't’ for biased questions. These markers typically appear at the beginning of the clause, contradicting Matthiessen’s generalization that such particles occur at the end in SOV languages. Additionally, polar interrogatives may be unmarked but distinguished by falling intonation. Content interrogatives are used to inquire about specific elements and are marked by Wh-words such as cim ‘who’, hɒrɒ ‘where’, and nijæ ‘why’. These clauses are clearly differentiated from declaratives through question words and rising intonation, aligning Azeri Turkic with typologically similar languages like English and Japanese, where content and polar interrogatives form a distinct mood type separate from declaratives. In terms of word order, Azeri Turkic follows the canonical position of Wh-elements within the clause rather than fronting them, placing it in the typological category of "Wh-in-situ" languages alongside Persian, Chinese, and Japanese, as opposed to English, French, and German.In Azeri Turkic, as in Persian and English, the imperative mood is marked by the absence of an overt subject, which is usually implied. Unlike in languages such as Mandarin Chinese and Hebrew, where negation in imperatives differs morphologically from declaratives, Azeri Turkic —similar to Persian and English—uses the same negative form across both imperative and non-imperative clauses. This indicates a syntactic independence between the imperative mood and the system of polarity in Azeri Turkic. Another typological feature of imperative clauses is the realization of speech functions relative to the speaker-listener relationship. Azeri Turkic, like German, Persian, and English, offers more delicate choices within the imperative mood to express politeness. For instance, all three languages can use polar interrogatives to represent polite commands.ConclusionThis study was an effort to describe the MOOD TYPE system in Azeri Turkic within a Systemic Functional Typological Framework.Drawing on diverse sources—including short story collections, academic articles, grammar books on Azeri Turkic, and the researcher's linguistic intuition—the study demonstrates that the MOOD TYPE system in Azeri Turkic:includes the three universal mood types: declarative, polar interrogative, and imperative.uses negative polar interrogatives to express the speaker’s positive bias.allows polar interrogatives to be expressed in declarative structure, without any formal marking other than intonation.belongs to the typological category of languages that distinguish content interrogatives (Wh-questions).questions only about participants and peripheral adjuncts—not processes—as interrogative elements in Wh-questions.is classified typologically as a "Wh-in-situ" language, where question words remain in their canonical position rather than being fronted.clearly distinguishes the imperative mood from other mood types.typically omits the addressee (second person) as an unmarked feature in imperative clauses.treats the imperative mood and the system of polarity independently, with no morphological distinction between negative forms in imperatives and non-imperatives.can metaphorically express the speech function of command through polar interrogatives, depending on the social relationship between speaker and listener.Overall, Azeri Turkic exhibits a well-differentiated MOOD TYPE system that aligns with broader systemic functional typological generalizations regarding mood types and their typological variations across languages.
Language and Literature, Language. Linguistic theory. Comparative grammar
Objectives This scoping review aimed to synthesise the currently available evidence and influencing factors on the occurrence of postoperative urinary retention (POUR) in older patients with hip fractures.Design This scoping review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guideline.Data sources PubMed, Cochrane Library, CINAHL, Web of Science, Chinese National Knowledge Infrastructure, Wanfang Data and Sinomed databases were systematically searched from database inception to 1 September 2024.Eligibility criteria We included observational studies reporting on POUR prevalence and risk factors among patients aged 60 years and older with hip fractures and excluded systematic and non-systematic reviews, conference proceedings, editorials, commentaries, qualitative studies and case studies. Duplicated articles and articles unable to access the full text were also excluded. We also excluded studies with populations with pathologic fractures, multiple fractures, treated for periprosthetic fracture, or if studies were published in a language other than English and Chinese.Data extraction and synthesis Two authors independently extracted and summarised the data. We summarised the prevalence and risk factors for POUR in older patients with hip fractures.Results A total of 106 studies were identified, and 12 studies (all from published literature sources) detailing POUR prevalence and risk factors were included. The studies showed that the incidence of POUR in older patients with hip fractures ranged from 11.10% to 51.33%, and the risk factors included impaired activities of daily living, use of anticholinergic medications, serological indicators (serum albumin and thyroid-stimulating hormone), complications (urinary infection and postoperative incontinence), prolonged indwelling urinary catheters and faecal impaction. In addition, male sex, cognitive impairment, use of opioid medications and coexisting diabetes may also be risk factors for POUR, which still needs to be further clarifiedConclusion The incidence of POUR in older patients with hip fractures varies widely. Most factors were reported in one study with no proposed underlying mechanism for their influence. Further high-quality studies are needed to validate these findings.
Usando dados de empresas listadas em ações A na Bolsa de Valores de Xangai e na Bolsa de Valores de Shenzhen de 2007 a 2018, este estudo investiga o impacto da liberalização do mercado de ações sobre o comportamento de “tunneling” dos grandes acionistas. Empregando o Programa de Conexão deBolsas da China Continental com a de Hong Kong como um experimento natural, construímos um modelo de diferença-em-diferenças escalonado e descobrimos que a liberalização do mercado de ações inibe significativamente o comportamento de tunneling dos grandes acionistas. Outros testes concluem que o aumento da pressão de venda de ações, o equilíbrio dos direitos dos acionistas e a melhoria do ambiente de informações são mecanismos potenciais. Os testes de heterogeneidade constatam que a relação negativa entre a liberalização do mercado de ações e o comportamento de tunneling dos grandes acionistas é mais acentuada nas empresas estatais e nas empresas que não contratam auditores das chamadas Big 4. Este estudo fornece evidências empíricas de que a liberalização do mercado de ações desempenha um papel disciplinador na mitigação dos custos de agência das empresas de uma economia emergente.
Knowledge about emotional events is an important kind of knowledge which has been applied to improve the effectiveness of different applications. However, emotional events cannot be easily acquired, especially common or generalized emotional events that are context-independent. The goal of this paper is to obtain common emotional events in Chinese language such as "win a prize" and "be criticized". Our approach begins by collecting a comprehensive list of Chinese emotional event indicators. Then, we generate emotional events by prompting a Chinese large language model (LLM) using these indicators. To ensure the quality of these emotional events, we train a filter to discard invalid generated results. We also classify these emotional events as being positive events and negative events using different techniques. Finally, we harvest a total of 102,218 high-quality common emotional events with sentiment polarity labels, which is the only large-scale commonsense knowledge base of emotional events in Chinese language. Intrinsic evaluation results show that the proposed method in this paper can be effectively used to acquire common Chinese emotional events. An extrinsic use case also demonstrates the strong potential of common emotional events in the field of emotion cause extraction (ECE). Related resources including emotional event indicators and emotional events will be released after the publication of this paper.
Classifiers are an important and defining feature of the Chinese language, and their correct prediction is key to numerous educational applications. Yet, whether the most popular Large Language Models (LLMs) possess proper knowledge the Chinese classifiers is an issue that has largely remain unexplored in the Natural Language Processing (NLP) literature. To address such a question, we employ various masking strategies to evaluate the LLMs' intrinsic ability, the contribution of different sentence elements, and the working of the attention mechanisms during prediction. Besides, we explore fine-tuning for LLMs to enhance the classifier performance. Our findings reveal that LLMs perform worse than BERT, even with fine-tuning. The prediction, as expected, greatly benefits from the information about the following noun, which also explains the advantage of models with a bidirectional attention mechanism such as BERT.
Scientific literature serves as a high-quality corpus, supporting a lot of Natural Language Processing (NLP) research. However, existing datasets are centered around the English language, which restricts the development of Chinese scientific NLP. In this work, we present CSL, a large-scale Chinese Scientific Literature dataset, which contains the titles, abstracts, keywords and academic fields of 396k papers. To our knowledge, CSL is the first scientific document dataset in Chinese. The CSL can serve as a Chinese corpus. Also, this semi-structured data is a natural annotation that can constitute many supervised NLP tasks. Based on CSL, we present a benchmark to evaluate the performance of models across scientific domain tasks, i.e., summarization, keyword generation and text classification. We analyze the behavior of existing text-to-text models on the evaluation tasks and reveal the challenges for Chinese scientific NLP tasks, which provides a valuable reference for future research. Data and code will be publicly available.
This scholarly disquisition furnishes a comprehensive exploration of the burgeoning presence of Chinese private security companies (PSCs) across Latin America and the Caribbean (LAC), delving into the strategic repercussions for regional security architectures and national sovereignty imperatives. Employing a meticulous qualitative methodology encompassing a thorough literature review, policy document analysis, and an examination of Chinese-language sources, the research elucidates the salient drivers catalyzing this phenomenon. These precipitating factors span cultural affinities, economic motivations, geopolitical ambitions, and the exigent security challenges besetting Chinese commercial entities operating within the LAC region. The operational modes of Chinese PSCs are subjected to forensic scrutiny, illuminating their diverse service offerings, geographical permeation across the region, and the obstacles they confront. Furthermore, the inquiry contextualizes the issue within the broader geopolitical milieu, accentuating concerns regarding transparency lacunae, regulatory deficiencies, and potential avenues for Chinese intelligence and military machinations, thereby potentially destabilizing the regional equilibrium. Ultimately, the research culminates in a series of substantive policy prescriptions aimed at mitigating risks, fortifying regional stability, and safeguarding national sovereignty through capacity-building initiatives, constructive engagement with Beijing, enhanced transparency mechanisms, and robust regional cooperation frameworks.
Given the importance of ancient Chinese in capturing the essence of rich historical and cultural heritage, the rapid advancements in Large Language Models (LLMs) necessitate benchmarks that can effectively evaluate their understanding of ancient contexts. To meet this need, we present AC-EVAL, an innovative benchmark designed to assess the advanced knowledge and reasoning capabilities of LLMs within the context of ancient Chinese. AC-EVAL is structured across three levels of difficulty reflecting different facets of language comprehension: general historical knowledge, short text understanding, and long text comprehension. The benchmark comprises 13 tasks, spanning historical facts, geography, social customs, art, philosophy, classical poetry and prose, providing a comprehensive assessment framework. Our extensive evaluation of top-performing LLMs, tailored for both English and Chinese, reveals a substantial potential for enhancing ancient text comprehension. By highlighting the strengths and weaknesses of LLMs, AC-EVAL aims to promote their development and application forward in the realms of ancient Chinese language education and scholarly research. The AC-EVAL data and evaluation code are available at https://github.com/yuting-wei/AC-EVAL.
The advancement of large language models (LLMs) has enhanced the ability to generalize across a wide range of unseen natural language processing (NLP) tasks through instruction-following. Yet, their effectiveness often diminishes in low-resource languages like Chinese, exacerbated by biased evaluations from data leakage, casting doubt on their true generalizability to new linguistic territories. In response, we introduce the Chinese Instruction-Following Benchmark (CIF-Bench), designed to evaluate the zero-shot generalizability of LLMs to the Chinese language. CIF-Bench comprises 150 tasks and 15,000 input-output pairs, developed by native speakers to test complex reasoning and Chinese cultural nuances across 20 categories. To mitigate data contamination, we release only half of the dataset publicly, with the remainder kept private, and introduce diversified instructions to minimize score variance, totaling 45,000 data instances. Our evaluation of 28 selected LLMs reveals a noticeable performance gap, with the best model scoring only 52.9%, highlighting the limitations of LLMs in less familiar language and task contexts. This work not only uncovers the current limitations of LLMs in handling Chinese language tasks but also sets a new standard for future LLM generalizability research, pushing towards the development of more adaptable, culturally informed, and linguistically diverse models.
With the rapid advancement of Large Language Models (LLMs), significant safety concerns have emerged. Fundamentally, the safety of large language models is closely linked to the accuracy, comprehensiveness, and clarity of their understanding of safety knowledge, particularly in domains such as law, policy and ethics. This factuality ability is crucial in determining whether these models can be deployed and applied safely and compliantly within specific regions. To address these challenges and better evaluate the factuality ability of LLMs to answer short questions, we introduce the Chinese SafetyQA benchmark. Chinese SafetyQA has several properties (i.e., Chinese, Diverse, High-quality, Static, Easy-to-evaluate, Safety-related, Harmless). Based on Chinese SafetyQA, we perform a comprehensive evaluation on the factuality abilities of existing LLMs and analyze how these capabilities relate to LLM abilities, e.g., RAG ability and robustness against attacks.
What a large language model (LLM) would respond in ethically relevant context? In this paper, we curate a large benchmark CMoralEval for morality evaluation of Chinese LLMs. The data sources of CMoralEval are two-fold: 1) a Chinese TV program discussing Chinese moral norms with stories from the society and 2) a collection of Chinese moral anomies from various newspapers and academic papers on morality. With these sources, we aim to create a moral evaluation dataset characterized by diversity and authenticity. We develop a morality taxonomy and a set of fundamental moral principles that are not only rooted in traditional Chinese culture but also consistent with contemporary societal norms. To facilitate efficient construction and annotation of instances in CMoralEval, we establish a platform with AI-assisted instance generation to streamline the annotation process. These help us curate CMoralEval that encompasses both explicit moral scenarios (14,964 instances) and moral dilemma scenarios (15,424 instances), each with instances from different data sources. We conduct extensive experiments with CMoralEval to examine a variety of Chinese LLMs. Experiment results demonstrate that CMoralEval is a challenging benchmark for Chinese LLMs. The dataset is publicly available at \url{https://github.com/tjunlp-lab/CMoralEval}.
This study explores the relationship between speaking anxiety and self-efficacy among Chinese students preparing for language proficiency tests, such as IELTS and TOEFL, in the context of increasing globalization and the widespread use of English. Drawing from the literature on second language acquisition and Banduras self-efficacy theory, we investigate how Chinese students beliefs in their ability to speak a second language influence their anxiety levels. A questionnaire comprising self-efficacy and anxiety scales was administered to 51 English language students in an intermediate IELTS or TOEFL program in China. The findings reveal a weak negative correlation between self-efficacy and speaking anxiety, indicating that as speaking anxiety decreases, students self-efficacy in learning to speak a second language increases. Conversely, heightened anxiety levels tend to deter students from engaging in spoken language learning. These results align with previous research highlighting the detrimental impact of anxiety on language performance and learners willingness to engage in language learning. This study underscores the importance of addressing speaking anxiety among Chinese students and its implications for their second language proficiency. It also offers valuable insights for educators, enabling them to better understand and address the root causes and consequences of speaking anxiety, thereby fostering a more conducive learning environment. Ultimately, this research contributes to the broader conversation on language learning strategies and provides practical guidance for both students and educators aiming to enhance the effectiveness of second language acquisition.
: Language learning strategies (LLS) are deliberate behaviours adopted by language learners to facilitate the acquisition, storage, and application of new knowledge. This study investigated the overall and individual LLS used by Chinese who are English majors from all grades. A review of selected different literature briefly shows the background and basic information of LLS with several influencing factors. The data came from the questionnaire based on Oxford’s (1990) Strategy Inventory of Language Learning (SILL) by quantitative research. The findings showed that the respondents used almost all strategies in a high level. The results showed that social strategy was used most frequently by the group of students followed by metacogntive strategy. While the rest of the strategies followed by are cognitive, compensation, affective strategy, except for the memory strategy which was used with medium range. The results seem to indicate that respondents tend to use their preferred LLS in improving their language skills and would benefit greatly from the use of LLS to improve their language proficiency. Additional qualitative research could be required to comprehend the exact strategies chosen by students. These findings would have significant pedagogical and theoretical consequences.
Chinese parents fail to maintain use of their heritage languages for family communication because their children seem to wield their own power in deciding the home language. Little is known about how micro-language decisions at family level are influenced by macro-societal language use patterns and sociopolitical contexts. This study examined the influence of children’s family language policy on use of heritage languages by Chinese families in multiethnic Malaysia. Data on the language practices, language ideologies, and management strategies of two families were obtained using semi-structured interviews with the mother/father. The findings show that heritage languages prevailed when the children were young. The switch to dominant languages, particularly Mandarin and English, was triggered by the medium of instruction in school. Interestingly, it was the younger children in the family who actively exerted their agency to influence their family language practice in favour of the dominant languages as the means of family communication. The findings indicated that exposure to the heritage language through the media, having grandparents as carers, and parents’ frequent assertions on the value of the heritage language are not sustainable for heritage language maintenance.
There is an urgent need to address the critical demand for qualified Chinese language teachers against the background of China’s seeking greater Sino–foreign cultural and educational cooperation. The literature on integrating technological pedagogical content knowledge (TPACK) in language teaching has been increasing in the last few years. However, most of these studies focus on English language teachers. The objective of this study was to examine pre-service teachers’ understanding of TPACK for teaching Chinese as a second language (TCSL). This study investigated the TPACK factor structure of 286 pre-service TCSL teachers via exploratory factor analysis, which yielded a six-factor structure. The results revealed that the teachers could not distinguish the boundaries between technological pedagogical knowledge (TPK) and technological content knowledge (TCK); and TPK and synthesized TPACK. Further, confirmatory factor analysis using structural equation modeling substantiated the validity and reliability of the adapted 32-item TCSL-TPACK survey instrument. The study also found that the teachers were slightly satisfied with their overall TPACK but were least confident of their technological knowledge (TK), and the more experienced teachers exhibited higher confidence in all six factors. These findings not only remind educators and policymakers of the need to revise current teacher training programs but also persuade TCSL student teachers to explore methods that can help integrate technology into lesson designs.