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Snapshots of teacher identity in English as an additional language or dialect (EAL/D) education in Australia: Insights for pre-service educators
No full textThis article presents a series of practitioner-focused identity “snapshots” drawn from interviews with experienced teachers of English as an Additional Language or Dialect (EAL/D) working in Australian schools. It supports pre-service and early-career EAL/D educators in understanding the lived realities of Australian EAL/D teaching through thematically organised insights based on teachers’ personal narratives and reflections. Based on interviews exploring personal experiences, classroom practices, and sociopolitical contexts, five key identity themes were identified: (1) personal background shapes teaching identity, (2) teaching is deeply student-centred, (3) institutional and policy challenges impact classroom practice, (4) emotional labour is a significant part of the job, and (5) EAL/D teachers often become advocates. These snapshots offer accessible, authentic accounts of Australian EAL/D teaching, designed to support reflective practice and professional learning in teacher education programs. Accompanied by a practical identity reflection toolkit, they translate teacher narratives into structured, applied learning. Addressing a gap in Australian EAL/D research, the study centres teacher voice through thematically organised practitioner accounts purpose-built to scaffold identity work in teacher preparation
A frequency-based wordlist of Japanese junior high school textbook vocabulary
No full textSeveral studies have examined the content of Japanese junior high school textbooks in relation to various frequency-based word lists such as the New General Service List (NGSL) (Browne et al., 2013) (e.g, Nakayama, 2022a,b) and the British National Corpus (BNC) (e.g, Wongsarnpigoon, 2018), and have identified potential issues in terms of lexical coverage and the repetition of vocabulary items. Considering the potential differences in individual textbook series and differences between frequency-based wordlists, it is worthwhile to evaluate the entirety of the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) approved junior high school textbooks (MEXT, 2024) in relation to multiple researched word lists including the NGSL, and the New JACET8000 (JACET, 2016) wordlist. To do so, a corpus of 18 textbooks from 6 publishers was analyzed using the software AntConc (Anthony, 2022) to generate a junior high school vocabulary wordlist sorted by the combined frequency and range of each item. While MEXT has advanced the target number of vocabulary items junior high school (JHS) students in Japan are expected to know entering high school to a range between 2,200 and 2,500 words (MEXT, 2019), the content of those words is relatively unknown. Thus, the aim of this study is to evaluate the content of the collective vocabulary items within the catalogue of MEXT approved JHS textbooks, by examining their range, frequency, and difference in ranking between the NGSL and JACET8000 wordlists. Additionally, the pedagogical applications derived from the analysis of a JHS textbook wordlist are discussed
The effects of online flipped peer dynamic assessment on EFL learners' academic writing skills
No full textThis study used an explanatory sequential mixed-methods design to investigate the effects of the Online Flipped Peer Dynamic Assessment (OFPDA) approach on English as a foreign language (EFL) learners' academic writing skills. 48 EFL learners at an Iranian university participated in the study through convenience sampling. Learners were randomly divided into flipped (n = 24) and non-flipped (n = 24) groups. The two groups followed DIALANG, pretest, intervention (for the flipped group), conventional teaching (for the non-flipped group), and post-test procedures. Moreover, one second of the flipped participants were voluntarily invited for a focus group interview. Data were analyzed using two independent sample t-tests: a microgenetic development approach was used to analyze moment-to-moment changes in learners' behaviours during peer interactions and a thematic analysis approach. The quantitative results showed that the flipped group significantly outperformed the non-flipped group in terms of academic writing skills. In addition, microgenetic development analysis revealed that implementing online peer graduation and contingent prompts considerably enhanced students' writing performance. The focus group interview findings also revealed that EFL learners had positive attitudes towards OFPDA. These findings have pedagogical implications for policymakers, educators, and teachers, who will benefit from the affordances of OFPDA, especially in technology-enhanced flipped settings, to improve learners' learning outcomes
Spontaneous use of generative artificial intelligence in preparing for college English test: GenAI adoption factors, learners' motivation, and self-efficacy
No full textThis study investigates the adoption and impact of Generative Artificial Intelligence (GenAI) tools on English as a Foreign Language (EFL) learners, focusing on self-efficacy, motivation, and predicted exam performance. Using a mixed-methods approach, the research combines survey data (N = 595) and interviews (N = 8) from Chinese university students preparing for the College English Test 4. Quantitative analysis shows that positive attitudes, perceived usefulness, and ease of use predict GenAI usage frequency, while intrinsic motivation negatively correlates with use. GenAI use frequency did not significantly affect predicted test scores or self-efficacy levels. Younger students used GenAI more frequently. Qualitative data reveals that students primarily use GenAI as supplementary learning resources, which, while beneficial, do not substantially enhance self-efficacy or predicted exam performance. The study founds a knowledge gap in the effectiveness of these tools in EFL contexts. It suggests strategies for optimizing GenAI in EFL learning, including blending with traditional methods, providing user training, balancing technology with traditional approaches, ensuring equal access, and customizing GenAI for education. The findings imply a need for educators to supervise GenAI use and for institutions to facilitate effective integration. Future research should examine long-term and cultural effects of GenAI use in education
A linguistic depiction of a picture description task using Register Analysis
No full textPicture description tasks are a common task-based activity that is often used both in the classroom as well as on major English language tests like the Eiken. This paper provides a linguistic description of a picture description task by using lexical bundles analyzed with a Register Analysis (RA) methodology. A picture description of a neighborhood from the National Institute of Information and Communications Technology (NICT-JLT) corpora was used. The study used the same structural taxonomy as Biber et al. (2004); however, the author of the paper created a different functional taxonomy for the specific communication goals of the task. This study found that verb phrase bundles made up the majority of lexical bundles and were often used to describe action and existence, though there was also a large amount of noun phrase/prepositional phrase bundles which were widely used to describe location. Specifically, verb phrase bundles consisting of the structures There + is + NP and Third Person Singular + present participle were very common. Bundles expressing location and direction (e.g., in front of the, on the car) were very common noun phrases/prepositional phrase bundles. This information can assist teachers in preparing and executing picture description tasks in their classrooms by providing them with the common lexico-grammatical patterns associated with the task
Beyond basics: A ten-lesson in-depth unit on generative AI for language students
No full textHow should we handle generative AI in the classroom? Many educators create policies that restrict or limit its use, which may be effective short-term but overlook the long-term impact on language learners as global digital citizens. Limiting AI to specific activities can lead to misconceptions about its capabilities and limitations. It’s essential to dedicate class time to exploring AI’s true affordances and pitfalls, allowing students to make informed decisions about its use. This paper will outline a 10-lesson unit integrated into 1st and 2nd-year courses across several universities in Japan. The unit introduces students to the current AI landscape, covering the history and inner workings of generative AI, while also teaching effective usage. A final project involves designing a local newspaper using AI, with evaluation focused on reflection and prompt effectiveness rather than the product itself. The unit also addresses ethical issues in employing generative AI
An introduction to corpus technology in the age of AI
No full textCorpus technology has been noted as a facilitative tool in data-driven learning (DDL) due to its advanced search capabilities and access to vast linguistic databases. Despite its potential, many teachers shy away from direct corpus use, which involves teacher- and learner-corpus interaction. Based on teacher and learner feedback, this hesitation is due to the overwhelming amount of corpus data and unfamiliarity with corpus query functions and techniques. To address these questions, this practice-based article aims to bridge the gap between teachers and the evolving landscape of corpus technology in the artificial age. First, it provides a brief introduction to the term corpus and its associated technology. Second, it highlights the common types of corpora available for teachers as an open resource. Next, it addresses corpus basics using Laurence Anthony’s AntConc 4.2.4 software. Then, it suggests three simple ways to incorporate corpus technology in the classroom. Finally, the article summarizes a corpus-informed lesson following the Illustration-Induction-Interaction (I-I-I) model
ChatGPT for self-regulated language learning: University English as a foreign language students’ practices and perceptions
No full textFocusing on the global trend of artificial intelligence (AI) in language learning, this survey-based study explored the practices and perceptions of Japanese English as a foreign language students (EFL) toward ChatGPT for second language (L2) learning. A mixed-method research design was utilized to achieve the study’s aims, with data being collected from three universities in Japan. The technology acceptance model-based survey was administered in the fall of 2023 and a total of 521 EFL students fully completed it. Quantitative analysis related to the students’ practices revealed that less than 25% of the respondents had used ChatGPT in their English studies, with formal language learning being more common than informal L2 learning outside of English coursework. Summarizing information written in the English language and translation were the top reported uses of ChatGPT for L2 English learning. According to the Likert scale responses, the L2 students’ perceived usefulness, perceived ease of use, and behavioral intention to use ChatGPT for English learning were positive. Content analysis of the qualitative data indicated contrasting findings, namely, while the students believed the AI chatbot could enhance their L2 learning, they were also concerned that it could hinder their language learning if overly relied upon. These results indicate that although a growing number of L2 learners are using ChatGPT and perceive it to be a useful resource for language learning, they are also aware of the drawbacks it poses to the language learning process