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Metadiscourse and metalinguistic talk about script choice in Serbia: Chasms and consequences for criticality
No full textIn Serbia, script diversity remains the norm whereby Serbian is routinely written in both the Cyrillic and Latin alphabets. This is not free of political contestation. Metadiscourses construct Cyrillic as the authentic script and central to ethnoidentity or, alternatively, as indexing dangerous nationalism, conservatism and Russian-leaning politics. On the flip side, metadiscourse associates Latin with modernity and progress, but for some with unwelcomed Western influence. But how do individuals themselves understand script preferences? This paper takes a folk linguistic approach to investigate whether the metalinguistic talk of Serbian individuals about script preferences is indeed informed by political metadiscourse. The data concern not only the stated preferences of individuals but also, borrowing from theory of mind, metatalk about how people explain the script preferences of others. The paper shows that the ideological oppositionality presupposed in metadiscourse tends not to be validated in metalinguistic talk, reminding us to be cognisant of chasms between societal-level metadiscourse and the lived experiences of individuals, and to avoid assumptions about the reach and impact of critical metadiscourse.  
Individual differences in L2 speaker intuitions of phrasal frequency and association strength of multiword sequences
No full textThis brief report presents the results of a re-analysis of data by Yi, Man, and Maie (2023), who investigated L1 and L2 intuitive knowledge of phrasal frequency and collocation strength in multiword sequences. We utilized an individual-differences approach and examined which participant variables (age of onset, length of residence, language use, and L2 proficiency) predicted the participants’ accuracy in judging the phrasal frequency and association strength of multiword sequences in English. We found that the demographic variables were only related to the accuracy in judging association strength, but those variables differentially predicted the accuracy depending on whether the collocations were of high or medium association strength
A case study of the creation of a supervising boundary practice in a work-integrated language learning program
No full textWhen migrating to a new country, there is often a need to learn a new language and find a job. In Sweden, in an effort to meet this need, a type of work-integrated language learning program, called combination courses, with the idea that students learn the language and a vocation simultaneously, is initiated. In this article, such a combination course, centring around the Swedish language as well as cleaning skills and providing apprenticeship workplace placements for the students, is studied. Using a boundary crossing lens to analyse the ethnographical data, consisting of 65 hours of observations, this case study analyses the boundary practices created by one workplace supervisor. The results show that the supervisor establishes a boundary crossing practice that comprises around two hours of theoretical studies for the student each day he spends on the practice, and over time, this boundary practice becomes more and more similar to schoolwork. This boundary practice provides the student with plenty of language learning affordances. It emphasises both oral and written communication, giving the student the opportunity to refine both during the practice. The experiences gained from this work-integrated language learning program provide valuable insights into the supervising practice involved when students are expected to learn both the language and the vocation simultaneously
Transitioning from paper to touch interface: Phoneme-grapheme recognition testing and gamification in primary school classrooms
No full textPhonological processing of written characters has been recognized as a crucial element in acquiring literacy in any language, both native and foreign. This study aimed to assess Japanese primary school students' phoneme-grapheme recognition skills using both paper-based and touch-interface tests. Differences between the two test formats and the relationship between phoneme-grapheme recognition skills and interaction with gamified digital tests were investigated. Participants were sixth-grade students from two public schools. The results of comparison tests indicated that the touch-interface test had lower success rates compared to the paper-based test for most items, suggesting a difference in performance patterns. A consistent relationship between tested phoneme-grapheme knowledge and successful gamified interaction was found. Findings highlight the potential of touch-interface assessments for assessing phoneme-grapheme recognition skills in primary school classrooms and suggest incorporating more digital tasks to enhance student adaptation
Capturing the full potential of Maltese language learning through ChatGPT
No full textChat Generative Pretrained Transformer (ChatGPT) is a state-of-the-art artificial intelligence (AI) language model developed by OpenAI. It employs advanced deep learning algorithms to generate text that mimics human language. Although ChatGPT has gained immense popularity in recent times, its significance is expected to rise further in shaping the future of technology and AI. This study investigates the potential of ChatGPT as a tool for enhancing the learning of Maltese for international adult students. The study involved 41 participants who embarked on a journey of exploration, employing ChatGPT for two weeks to support their Maltese learning. The study evaluated the effectiveness of ChatGPT through surveys and focus group discussions, which revealed that while ChatGPT was convenient and accessible, its ability to provide accurate responses to students' questions and support Maltese grammar, vocabulary, and conversational practice was limited. The participants expressed frustration with the ChatGPT's limitations in understanding and responding to Maltese language. The study emphasizes the need to fully unleash ChatGPT's potential by improving its training on Maltese language and collaborating with Maltese language and AI experts to better support Maltese language learning. The findings have important implications for the development of ChatGPT for less widely spoken languages like Maltese
A worldwide study on language educators’ initial response to ChatGPT
No full textThis exploratory study investigated how 367 university language educators from 48 countries/regions responded to ChatGPT in the first 10 weeks after its release. It explored awareness, use, attitudes and perceived impact through a survey collecting both quantitative and qualitative data. Most participants demonstrated moderate awareness, but little teaching application. Around half had used ChatGPT in some way, but only 16% for educational purposes. Interest was high but many concerns were raised, particularly about misuse. Most agreed to a likely future use for creating materials, but were less open to use it as a writing feedback assistant or for automated assessment. Perceptions of the impact of ChatGPT were cautiously optimistic, with more positivity from hands-on users. Concerns focused on misuse, while benefits were noted in terms of efficiency. Qualitative data were analysed using an adapted version of the Concerns-Based Adoption Model (CBAM), which revealed that teachers were primarily in the early ‘awareness’ or ‘personal’ stages of concern, suggesting a gradual adoption process. Key implications are that educators need support in developing skills for pedagogical applications of ChatGPT, while critically evaluating appropriate use. More empirical evidence on effective practices is needed. This timely study provides baseline data on language teachers’ initial engagement with ChatGPT, highlighting promising directions but also remaining concerns. Further research can track how responses evolve
Augmented linguistic analysis skills: Machine translation and generative AI as pedagogical aids for analyzing complex English compounds
No full textIn this article, our aim is to assess the efficacy of machine translation tools and state-of-the-art generative AI platforms such as ChatGPT in fostering enhanced linguistic analysis skills among students in order to improve their understanding of the language. Our case study deals with the analysis of complex English compounds—a known challenge for French learners of English as a second language. Our investigation centers on students’ ability to identify the head noun within complex noun phrases, both in full sentences and in press titles. The study involved two distinct cohorts: students in their third and final year of an undergraduate program in applied foreign languages, and students in their second and final year of a master's program in professional translation. We evaluated the participants’ ability to identify head nouns—a necessary skill for comprehending complex noun phrases—under two conditions: (i) without the aid of any linguistic tools and (ii) with the assistance of machine translation outputs by a generic online translator. Subsequently, we explored the capabilities of advanced generative AI tools—in this instance ChatGPT—of correctly identifying head nouns. Our results show that students may benefit from the presence of machine translation outputs, albeit with varying degrees of success. Our experimentation with ChatGPT shows that, given appropriate prompts, the tool is capable of identifying head nouns, suggesting that generative AI tools may be a more effective tool in helping students analyze and understand complex noun phrases in English
Review of conducting technology acceptance research in Education Theory: Models, implementation, and analysis
No full textFinding the human in an era of machine intelligence: A flat ontological analysis of generative AI and language learning
No full textAmid the optimism of generative Artificial Intelligence (gen-AI) in language education, there remains a weak connection to learning practices. The emergence of gen-AI has preceded considerations of how it should be applied in teaching and learning. However, while gen-AI has been justified in terms of the possibilities to enhance learner agency by expanding opportunities to engage with language, such as through the generation of content or the translation of texts, it can also take power away from learners. How can learners be self-determining in light of how choices become increasingly guided by Artificial Intelligence? In this paper, I conceive the arrangements of humans and software as an assemblage of complex and dynamic social, and technical processes. Drawing on a flat ontology, where all agents (human and non-human, material and subjective) have equal ontological status, I argue that learner agency has its origins in the messy and lively interactions between heterogenous actors. In particular, I consider active and passive affects as being part of the same process: active when we bring something into effect ourselves, passive when our self-determination is changed not by our own power, but through external forces acting on it (such as gen-AI). From this, I explore the constraining and enabling potential of artificial intelligence. Finally, I extend this discussion to the emergence of learner agency
Exploring ethical dimensions of AI-enhanced language education: A literature perspective
No full textAdvances in artificial intelligence (AI), particularly in generative AI, continue to affect language education paradigms. The integration of AI in language education raises deep-seated ethical concerns such as privacy and data security, potential biases and hidden ideologies in the output, transparency and accountability, dependency and autonomy, digital divide, and job displacement and professional development. The article analyzes these ethical concerns and introduces the multifaceted dimensions of ethics associated with AI in language education. This article comprehensively examines the potential biases of AI in language education. These biases can be algorithmic, demographic, cultural, linguistic, temporal, confirmation, ideological and political. The analysis includes factors contributing to biases, such as training data , labelling and annotation, product design decisions, policy decisions, and algorithms. This paper analyzes algorithmic transparency and advocates for more transparent AI systems to address bias in algorithms. Violations of student privacy emerge as one of the profound ethical issues in the discourse on AI-enhanced language education. The article also examines the challenges and risks associated with the protection of student data privacy, emphasizing the need for robust privacy frameworks to alleviate concerns regarding privacy, human agency and the lack of transparency in the collection of an excessive amount of personal information. By synthesizing the key findings, the paper will conclude with a potential framework of ethical guidelines for the responsible and ethical integration of AI in language education.