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    The integration of AI technology and critical thinking in English major education in China: Opportunities, challenges, and future prospects

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    This paper addresses the call to integrate Artificial Intelligence (AI) technology and critical thinking in English major education in China. By examining the perspectives of university, college, and departmental leaders at Shantou University, this paper explores the integration of AI and critical thinking in English major education in China, focusing on opportunities, challenges, and future directions. Through a polylogue with institutional leaders at Shantou University, the paper provides insight into how AI tools can enhance personalized learning, improve academic outcomes, and better prepare students for the global workforce. However, the findings also highlight the ethical and pedagogical challenges of AI, such as the risk of exacerbating educational inequalities and compromising critical thinking. The paper advocates for an approach that balances AI proficiency with the development of independent thinking, ensuring that students are well equipped for the future

    The impact of COVID-19 on sign language assessment

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    This study investigated through an online survey how sign language practitioners changed their sign language assessment practices during the COVID-19 pandemic. The survey consisted of five sections and 29 questions overall. It was provided in written English and German as well as in International Sign and was administered online between October 2021 and December 2022. Twenty sign language testing professionals from a wide variety of countries participated in the survey. The results indicate a sharp increase of online testing during the pandemic, a decrease in the testing of sign language interaction and reception, a decline in the variety of testing purposes with a stronger focus on assessment for learning, and a shift to the use of more online tools such as video conferencing. Additionally, the results show that the home set-up of test takers, including reliable internet connection and access to appropriate hardware, are essential for online sign language testing. Sign language testing professionals reported different measures that were introduced to minimize cheating, such as live video monitoring during sign language exams or the implementation of proctoring software. The paper finishes with recommendations for future sign language assessment

    You only need to change your direction: A look at the potential impact of ChatGPT on education

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    ChatGPT, a generative AI program developed by OpenAI, has raised serious questions about the future of education since its launch in November 2022. This paper argues that ChatGPT has the potential to redefine existing educational theories and the role of teachers in language education. Specifically, the paper examines ChatGPT’s impact on language education and suggests ways to incorporate it into teaching practice. Since people have been proclaiming that AI would replace teachers since the 1970s, the history of AI in education is relevant to this paper. Therefore, the paper first discusses the history of AI in education to provide context and highlight how ChatGPT fits into this larger conversation. Afterwards, the paper then explores how ChatGPT might redefine existing learning theories such as Constructivism and Self-Determination Theory using the AIED framework. ChatGPT has the potential to provide learners with personalized and adaptive learning experiences that align with these learning theories. For this reason, the paper will investigate how ChatGPT may impact the role of learners through the lens of Learner Autonomy before looking at how it might also redefine the role of the teacher in the classrooms of the near future. While ChatGPT has the potential to automate certain aspects of language education, the role of the teacher as a mentor and guide in the learning process is still essential. Finally, the paper offers suggestions for how educators can effectively incorporate generative AI programs like ChatGPT into their teaching practice and curriculum. The paper concludes by emphasizing the importance of approaching the integration of AI in education with caution and a critical perspective

    Language learning through music: A critical review of Lirica https://www.lirica.io/

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    The past decade has been the heyday of mobile-assisted language learning (MALL), with increased use of mobile applications (apps) as learning platforms. Despite the central focus of mobile apps on particular language skills such as vocabulary (e.g., Duolingo) and pronunciation (e.g., BoldVoice), few have factored in both learners and teachers. Lirica is an engaging mobile app that fosters language learning through songs in five languages. Given the pedagogical and psychological affordances of songs and the personalized learning environment offered by mobile apps, this tech review seeks to present an overview of the Lirica app and its potential for language learning while tackling its limitations

    Automated feedback on fluency and complexity measures for L2 academic paragraphs: Student perspectives and impacts on human-rater scores

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    While complexity, accuracy, and fluency (CAF) measures are known to correlate with L2 writers’ scores, less is known about the effectiveness of providing automated feedback based on these measures for improving writing performance. Furthermore, it remains unclear if improvements in specific CAF measures correspond to improvements in human-rater scores. Finally, the trade-off hypothesis predicts that all three components of CAF cannot be improved at once, so providing multiple CAF measures to students at the same time might cause cognitive overload and overwhelm students, reducing their ability to uptake the feedback. To examine these issues, a simple paragraph feedback tool was developed to provide input on number of words, vocabulary variety, supporting detail markers, and sentence length. The tool was implemented repeatedly in L2 academic paragraph writing lessons with 124 students. Improvement was assessed through complexity, accuracy, and fluency (CAF) measures and human-rater scores, while also gathering student opinions. Results showed significant improvements in number of words, sentence length, and supporting detail marker usage from pre- to post-treatment with improvements in number of words and vocabulary variety found to be the strongest predictors of improvements in human-rater scores. Students reported finding vocabulary variety feedback most helpful, while supporting detail marker feedback was perceived as most confusing. Notably, students reported very low cognitive load overall. This article also discusses pedagogical implications of these findings for L2 writing instruction and automated feedback implementation

    Pecha, a language practice peer: Guiding language learning interactions through large language models

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    The interaction hypothesis of second language acquisition (Long, 1981) states that negotiated interaction is necessary for language development. In many language learning contexts, educators and stakeholders seek to provide opportunities for learners to engage in meaningful real-life interactions that help them build linguistic, semantic, and rhetorical competence. However, the opportunities provided for interaction can vary in their degree of effectiveness and may only sometimes lead to increased language ability. If these interactions are scaffolded correctly, they can be tuned to maximize their benefits (Loewen & Sato, 2018). Unfortunately, this is not always practical from a temporal and economic perspective. Artificial intelligence (AI) could be the solution for providing learners with individualized, comprehensive assistance during their learning interactions. Accordingly, the authors developed a bespoke application that employs advanced natural language processing and large language model AI technologies to support learner interactions. The application was developed to support students in two different contexts: Kanda University of International Studies in Japan, where students study English, and Massachusetts Institute of Technology in the United States, where learners study Japanese. The rationale for creating the application and selecting its major features is discussed. This is followed by a discussion of how the application functions and how it will be used.  The authors will then discuss their plans for implementation into both informal and formal learning contexts at the two universities. They conclude by discussing potential limitations and plans for improving the application

    Linguistic discourse analysis of lexico-grammatical features of moves in the research abstracts of medical students in a Ghanaian university

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    Writing a quality research abstract is crucial for a scholarly report. An abstract should be information and lexically dense, formal, and have a professional tone. This requires precision, objectivity, logicality, technicality, and comprehensiveness. However, writing a good-quality research abstract is a hurdle for novice and inexperienced undergraduate students who study English as a Second Language (ESL), that is English language learners worldwide. This article interrogates the research abstracts written by undergraduate medical students who also studied English Language at the University of Health and Allied Sciences (UHAS) in Ho, Ghana. A qualitative-quantitative approach, guided by Hyland’s (2000, 2004) five-move model, was used to analyze the lexico-grammatical features in the rhetorical moves of the research abstracts written by these students. A corpus of 23 extracts representing a quota of sample tenses, hedges, boosters, and nominalization were analyzed. The data were coded manually and presented as frequency counts and percentages in tables and graphically. The results revealed that rhetorical moves in the research abstracts written by undergraduate medical students of UHAS in Ho, Ghana were replete with simple past, simple present, and perfect tenses, and lexico-grammatical devices such as hedges, boosters, and nominalization to a greater or lesser extent. The study concludes that the research abstracts written by undergraduate medical students of UHAS follow Hyland’s (2002, 2004) five rhetorical move model, and are constituted by specific lexico-grammatical features.  The pedagogical implications are discussed, and suggestions for future research are provided

    Review of developing translanguaging repertoires in critical teacher education

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    Towards becoming a transnational language educator

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    The issues surrounding the personal and professional lives of TESOL educators in transnational landscapes have gained increased attention in the past decade. Existing research on transnationalism underscores the significance of expatriates’ experiences, particularly those who originate from ‘non-center’ and whose careers lead them to work in ‘periphery’ countries, setting their experiences apart from those of (im)migrants. This study examines the experiences of ‘non-native’ English-speaking (NNEST) teachers working in transnational contexts, their motivations for relocation, and the challenges they face in adapting to new societies. Guided by the concept of ‘becoming’, the research investigates the key turning points and types of becomings encountered by these expatriate teachers in their journeys towards a transnational identity. Drawing on theories of the ‘Third Space’, the article attempts to understand the ideological transformations that occur within transnational spaces. The findings offer insights into the complex and evolving process of becoming transnational for expatriate ‘non-native’ language educators. By understanding their journeys of self-transformation, this study contributes to the literature on transnationalism and offers valuable perspectives for policymakers and educational bodies. The outcomes of this study endeavor to enhance support for NNESTs by recognizing their transnational experiences as pedagogical resources

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