Research Methods in Applied Linguistics最新文献

{"title":"Language without borders: A step-by-step guide to analyzing webcam eye-tracking data for L2 research","authors":"Jason Geller ,&nbsp;Yanina Prystauka ,&nbsp;Sarah E. Colby ,&nbsp;Julia R. Drouin","doi":"10.1016/j.rmal.2025.100226","DOIUrl":"10.1016/j.rmal.2025.100226","url":null,"abstract":"<div><div>Eye-tracking has become a valuable tool for studying cognitive processes in second language acquisition and bilingualism (Godfroid et al., 2024). While research-grade infrared eye-trackers are commonly used, several factors limit their widespread adoption. Recently, consumer-based webcam eye-tracking has emerged as an attractive alternative, requiring only a personal webcam and internet access. However, webcam-based eye-tracking introduces unique design and preprocessing challenges that must be addressed to ensure valid results. To help researchers navigate these challenges, we developed a comprehensive tutorial focused on visual world webcam eye-tracking for second language research. This guide covers key preprocessing steps—from reading in raw data to visualization and analysis—highlighting the open-source R package webgazeR (Geller, 2025), freely available at: <span><span>https://github.com/jgeller112/webgazer</span><svg><path></path></svg></span>. To demonstrate these steps, we analyze data collected via the Gorilla platform (Anwyl-Irvine et al., 2020) using a single-word Spanish visual world paradigm (VWP), showcasing evidence of competition both within and between Spanish and English. This tutorial aims to empower researchers by providing a step-by-step guide to successfully conduct webcam-based visual world eye-tracking studies. To follow along, please download the complete manuscript, code, and data from: <span><span>https://github.com/jgeller112/L2_VWP_Webcam</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100226"},"PeriodicalIF":0.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144471641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic examination of generative artificial intelligence (GenAI) use guidelines in applied linguistics journals","authors":"Shuhui Yin,&nbsp;Carol A. Chapelle","doi":"10.1016/j.rmal.2025.100227","DOIUrl":"10.1016/j.rmal.2025.100227","url":null,"abstract":"<div><div>The unannounced appearance of GenAI in 2022 and the speed of its adoption by researchers have left many questions unanswered about its accepted ethical use, with no apparent consensus among applied linguists. In this context, it’s essential for researchers to develop their GenAI literacy for research to engage with GenAI effectively and responsibly. This study contributes to identifying key components of this literacy through examining accepted GenAI uses in research practices. Based on a systematically sampled collection of 170 high-impact journals in applied linguistics, we investigated the scope and nature of GenAI use guidelines provided by 76 journals intended to guide authors. A checklist including four items regarding general statements and 17 items regarding three categories of specific aspects that GenAI guidelines target (authorship, uses, and human responsibility) was identified. Our findings reveal that (1) less than half of the journals provided GenAI use guidelines to guide authors, (2) the number of specific aspects varied across journals, with most falling short of comprehensive coverage, and (3) disagreements were observed about whether AI can be cited and used for manuscript drafting, idea generating, image generating, data generation, data collection, and data analysis and interpretation. Additionally, journals varied in their guidance on how to disclose GenAI uses. We propose recommendations for journals in improving their AI guidelines. Importantly, we introduce and conceptualize the new construct GenAI literacy for research article writing (GenAI-LR) that is important for authors to develop. We provide actionable recommendations accordingly based on our findings.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100227"},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the validity of web-based reaction-time tasks for assessing L2 grammatical knowledge in young learners","authors":"Takeshi Ishihara ,&nbsp;Akira Hamada","doi":"10.1016/j.rmal.2025.100228","DOIUrl":"10.1016/j.rmal.2025.100228","url":null,"abstract":"<div><div>This study investigated the validity of web-based psycholinguistic tasks for assessing automatized explicit and implicit grammatical knowledge in young second language (L2) learners. Specifically, it examined whether a time-pressured grammaticality judgment task and a self-paced reading task administered online produce results comparable to those obtained in an in-person setting. In addition, the influence of the Big Five personality traits on task participation and performance was explored. A total of 192 Japanese first-year middle school students were assigned to either a School group (in-class setting) or a Home group (online setting). The results revealed that accuracy performance on both tasks was generally comparable across settings, supporting the feasibility of remote task administration. However, reaction-time-based measures were more sensitive to testing conditions. In the grammaticality judgment task, the expected reaction-time effect (faster responses to grammatical items) was observed in the School group but not in the Home group. Similarly, the Home group produced faster and more variable reading times in the self-paced reading task, and the expected slowdown for grammatical errors was not observed, raising concerns about the validity of online reading-time data. Personality traits, particularly neuroticism, conscientiousness, and agreeableness, were associated with task participation and reaction-time variability, highlighting the role of individual differences in online task behavior. These findings demonstrate the need for caution when using reaction-time measures in unsupervised web-based experiments with young L2 learners and offer practical recommendations for enhancing data quality in remote L2 assessment.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100228"},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Challenging lexical coverage conventions: Evaluating the vocabulary demands of family-genre film and television","authors":"Brett Milliner ,&nbsp;Geoffrey Pinchbeck","doi":"10.1016/j.rmal.2025.100230","DOIUrl":"10.1016/j.rmal.2025.100230","url":null,"abstract":"<div><div>The contribution of studies investigating lexical coverage to the field of applied linguistics cannot be understated. Lexical coverage research has helped establish the vocabulary knowledge most essential for second language (L2) comprehension and elevate the importance of high-frequency vocabulary knowledge acquisition. Approaches to lexical coverage research have, however, begun to come under closer scrutiny in recent studies, with some experts questioning the accuracy of coverage estimates. Understanding these limitations, the current study applies an alternative approach to evaluating the lexical knowledge required to comprehend the OPUS-family-genre corpus, a collection of closed captions from 1597 family-genre films and television programs (10,744,767 tokens). In contrast to previous conventions that used band-based (1000-word) predictions of lexical coverage, in this study, coverage is evaluated at the individual word-unit level. It compares the coverage provided by four word lists: (1) a lemma list derived from tagging the OPUS-family-genre corpus, (2) a flemma list, and two word-family lists, (3) the BNC, and (4) the BNC/COCA. The study also models how a part-of-speech lexical tagger (TagAnt) can be used to evaluate lemma-based lexical coverage. The analysis revealed that English language learners will know 90, 95, and 98% of the running words appearing in family-genre films and television if they know the first 855, 2005, and 4393 flemmas, from the attached word lists. More simply, knowing the first 900 words from our supplementary word frequency lists would enable English language learners to start viewing family-genre films and television.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100230"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unique and shared roles of the LLAMA subtests for prediction of initial L2 achievement: An application of regression commonality analysis","authors":"Philip S. Dale ,&nbsp;Lars Bokander ,&nbsp;Richard L. Sparks","doi":"10.1016/j.rmal.2025.100224","DOIUrl":"10.1016/j.rmal.2025.100224","url":null,"abstract":"<div><div>Little research has examined the relations of the LLAMA subtests beyond predictive correlations and simple regressions. In this secondary analysis of data from Bokander (2020), we use regression commonality analyses (RCA) to address multicollinearity by decomposing the LLAMA predictive variance into unique components for each subtest alone and for each possible subtest combination. Fifty-five students with Germanic L1 backgrounds completed the LLAMA, followed by an introductory Swedish course, and then a written C-test. LLAMA-D, sound-sequence recognition, was the most important unique predictor of L2 achievement. LLAMA-E (sound-symbol association) unique variance and shared variance with LLAMA-D and LLAMA-B (vocabulary learning) was the next most important contributor to prediction. Similar to results for MLAT, these results demonstrate the major role of phonetic script/sound-symbol relationship skills both uniquely and shared with other subtests. The most important difference is the equally important, distinct role of speech sound-sequence recognition, a skill not previously included in aptitude tests prior to the LLAMA. The paper concludes with a discussion of the strengths and limitations of regression commonality analysis, which appears to have considerable usefulness for studies involving prediction.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100224"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rethinking fluency in task-based L2 writing: A critical examination of product- and process-based measures","authors":"Mahmoud Abdi Tabari ,&nbsp;Mark D. Johnson","doi":"10.1016/j.rmal.2025.100225","DOIUrl":"10.1016/j.rmal.2025.100225","url":null,"abstract":"<div><div>This paper offers a theoretically informed critical examination of current conceptualizations of fluency in task-based writing, a growing focus within second and foreign language writing research and pedagogy. To date, research in this area has employed both product- and process-oriented metrics, with a notable shift toward process-based approaches over the past few years. This review traces the evolution of these analytic frameworks in writing research, evaluating their respective strengths and limitations. Building on these insights, the paper provides recommendations for the application of each approach in pedagogical and research settings, emphasizing the importance of inclusivity and equity in both second and foreign language instruction and task-based L2 writing research.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100225"},"PeriodicalIF":0.0,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conducting sociolinguistic interviews via generative AI: A methods tutorial","authors":"Annita Stell,&nbsp;Hao Tran,&nbsp;Peter Crosthwaite","doi":"10.1016/j.rmal.2025.100223","DOIUrl":"10.1016/j.rmal.2025.100223","url":null,"abstract":"<div><div>Sociolinguistic interviews (Labov, 1984) are integral to dialectology studies, providing insights into language variation and the social contexts influencing the emergence of new dialects (Hoffman, 2013; Pizarro Pedraza, 2016). Such data, while incredibly valuable, is typically time-consuming and expensive to collect. However, with the advent of generative AI (GenAI) applications e.g., ChatGPT 4o purported to produce discourse in multiple languages, its affordances for generating sociolinguistic interview data across different dialects of dialect-rich languages remain largely unknown. Building on a Gen-AI-assisted Mandarin/ Vietnamese dialect study in Tran and Stell (2024), this tutorial offers step-by-step guidance on conducting sociolinguistic interviews with ChatGPT. Key steps include generating prompts by establishing a dialogue context, formulating appropriate structured open-ended questions to elicit target dialectal varieties, and a cross-validation process with actual dialect speakers. While acknowledging the potential limitations of conducting sociolinguistic interviews with ChatGPT, this tutorial serves to aid those new to GenAI for dialectology research while suggesting future directions for refining this process as GenAI continues to develop.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100223"},"PeriodicalIF":0.0,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144253234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating L2 textbook input for grammar learning: from research findings to operationalized evaluation criteria","authors":"Raphaël Perrin,&nbsp;Anita Thomas","doi":"10.1016/j.rmal.2025.100213","DOIUrl":"10.1016/j.rmal.2025.100213","url":null,"abstract":"<div><div>Prior studies investigating the quality of linguistic input in L2 textbooks have mainly focused on lexical frequencies for vocabulary development. The present study explores how previous findings on the role of salience, frequency, and explicit instruction can be used in the form of operationalized criteria to evaluate input quality in L2 textbooks for the learning of grammatical target features. To this aim, we have reviewed research on the subject, suggested evaluation criteria based on this literature, and chosen two French textbooks and two sample target features – the position of French reflexive pronouns and their coreference with the subject – to explore the applicability of the criteria.</div><div>The example analysis suggests that the developed criteria are applicable and useful for evaluating L2 textbook input quality for the learning of grammatical features. However, the example analysis also highlights several challenges, such as interpreting frequency counts in the absence of benchmarks. More complete textbook analyses are needed to test the applicability of the suggested approach.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100213"},"PeriodicalIF":0.0,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genre-based fine-tuning of large language models with self-organizing maps for automated writing evaluation","authors":"Stephanie Link,&nbsp;Robert Redmon,&nbsp;Martin Hagan","doi":"10.1016/j.rmal.2025.100219","DOIUrl":"10.1016/j.rmal.2025.100219","url":null,"abstract":"<div><div>Automated Writing Evaluation (AWE) systems have significantly advanced in providing feedback for academic essay writing. However, their predominant focus on sentence-level features highlights the need for a broader approach to AWE development. While genre-based AWE systems aim to address the socio-rhetorical complexities of writing for specific audiences and purposes, their availability remains limited. This scarcity is largely due to methodological constraints in developing robust feedback engines that effectively support discipline-specific writing needs. This article describes a new method for fine-tuning large-language models (LLM) and evaluating model performance, which we refer to as G-FiT Mapping (Genre-based FIne-Tuning with self-organizing maps). This method utilizes semi-automated annotation of genre-based functional-rhetorical units of text to efficiently fine-tune an LLM and then uses self-organizing maps to evaluate and improve network performance. The G-FiT Mapping method resulted in a new automated feedback engine for an intelligent tutoring system called Dissemity, for DISSeminating research with clarITY, that supports discipline-specific, scientific writers in writing for publication. We demonstrate use of G-Fit Mapping for establishing measurable improvements in network performance, offering implications for network interpretation, genre-based AWE, and AI-based learning systems development.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100219"},"PeriodicalIF":0.0,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing language education with ChatGPT: A path to cultivate 21st-century digital skills","authors":"Amir Reza Rahimi ,&nbsp;Ramin Teimouri","doi":"10.1016/j.rmal.2025.100218","DOIUrl":"10.1016/j.rmal.2025.100218","url":null,"abstract":"<div><div>Artificial Intelligence (AI) has become increasingly integrated into education, human life, and work as we continue to enter the 21st century, resulting in an increased expectation that learners and humans should possess more skills, referred to as 21st-century digital skills. These skills have become essential for learning, working, and living with Artificial Intelligence and the latest generation of Information and Communication Technologies (ICTs). While recent studies have examined Artificial Intelligence, particularly ChatGPT, in terms of its ability to assist language learners in developing their language skills as well as their subskills, they have not explored its role in the development of their 21st-century digital skills. For this sake, in this study the researchers integrated ChatGPT into the language classroom procedure in three high schools in Tehran, where the language teacher tried to cultivate 21st-century digital skills with ChatGPT and led students to take advantage of its features to improve their 21st-century digital skills throughout the academic year of 2023–24 and then filled out the study survey. The results of the Partial Least Square Modelling Approach (PLS-SEM) showed that ChatGPT's personalization, interactivity, accuracy, and responsiveness, along with its anthropomorphism, significantly shaped language learners' 21st-century digital skills, including critical thinking digital skills, information evaluation skills, creative digital skills, and problem-solving skills. In addition, the study found a sign of digital self-authenticity, where language learners perceived that AI-assisted language learning enhanced their 21st-century digital skills more than previous language learning contexts, albeit at the expense of their digital collaboration skills. Therefore, the study broadened the existing literature by focusing on the 21st-century digital skills of language learners, going beyond their language skills and sub-skills. It suggests that ChatGPT has the potential to enhance and develop language learners' 21st-century digital skills. However, language teachers must devise metrics to encourage learners to engage in both collaborative and personalized language learning with ChatGPT, thereby fostering the development of all 21st-century digital skills.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 2","pages":"Article 100218"},"PeriodicalIF":0.0,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}