Cyriel Mallart , Andrew Simpkin , Nicolas Ballier , Paula Lissón , Rémi Venant , Bernardo Stearns , Jen-Yu Li , Thomas Gaillat
{"title":"Assessing the validity of syntactic alternations as criterial features of proficiency in L2 writings in English","authors":"Cyriel Mallart , Andrew Simpkin , Nicolas Ballier , Paula Lissón , Rémi Venant , Bernardo Stearns , Jen-Yu Li , Thomas Gaillat","doi":"10.1016/j.rmal.2025.100238","DOIUrl":"10.1016/j.rmal.2025.100238","url":null,"abstract":"<div><div>This article addresses Second Language (L2) writing development through an investigation of alternation-based metrics. We explore the paradigmatic production in learner English by linking language functions to specific grammatical paradigms. Using the EFCAMDAT as a gold standard and a corpus of French learners as an external test set, we employ a supervised learning framework to operationalize and evaluate seven alternations. We show that learner levels are associated with these seven alternations. Using ordinal regression Modeling for evaluation, the results show that all syntactic alternations are significant but yield a low impact if taken individually. However, their influence is shown to be impactful if taken as a group. These alternations and their measurement method suggest that it is possible to use them as part of broader-purpose Computer-Assisted Language Learning (CALL) systems focused on proficiency assessment.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100238"},"PeriodicalIF":0.0,"publicationDate":"2025-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766490","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":"From lab to web: Replicating cross-language translation priming asymmetry in an online environment","authors":"Zhiyi Wu, Mireia Toda Cosi","doi":"10.1016/j.rmal.2025.100247","DOIUrl":"10.1016/j.rmal.2025.100247","url":null,"abstract":"<div><div>In second language (L2) acquisition research, understanding how learners process words across languages is crucial, with the translation priming paradigm consistently revealing that an L2 word can be processed significantly faster after a brief presentation of its translation equivalent in one’s first language (L1) but not vice versa. This study attempted to replicate Chen et al.’s (2014) investigation of translation priming asymmetry with Chinese-English bilinguals in an online environment using the Naodao crowdsourcing platform. We conducted three masked priming lexical decision experiments: two testing L1-to-L2 and L2-to-L1 priming with a 50-ms prime duration, and one examining L2-to-L1 priming with an extended 250-ms prime duration. Results showed that the classic asymmetry pattern was not fully reproducible in this online setting at 50-ms prime duration, with null effects in both directions. However, significant priming effects emerged with the extended prime presentation in the L2-to-L1 direction. These findings suggest that online implementation of timing-sensitive paradigms may require methodological adaptations.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100247"},"PeriodicalIF":0.0,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723188","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":"Introducing and comparing two techniques for key lexical bundles analysis","authors":"Tove Larsson, Taehyeong Kim, Jesse Egbert","doi":"10.1016/j.rmal.2025.100245","DOIUrl":"10.1016/j.rmal.2025.100245","url":null,"abstract":"<div><div>Multiword units, specifically lexical bundles, have been found to be important building blocks in language production and processing. We also know that using the text rather than the full corpus as the unit of analysis increases the linguistic validity of the results, given that written language is produced through texts (e.g., Egbert & Biber, 2019). However, researchers wishing to look at which bundles are characteristic of, or <em>key</em> to, a population (e.g., students from a specific first-language background) are currently out of luck if they are interested in using the text as the unit of analysis. The present paper introduces two methods designed for looking at key lexical bundles using texts as the unit of analysis: <em>text dispersion keyness</em> and <em>mean text frequency keyness</em>. We subsequently compare the results from these methods to existing <em>whole-corpus frequency keyness</em>. The results show that the techniques produce similar lists, but that mean text frequency keyness produced the largest number of content generalizable bundles (i.e., bundles that can be generalized across texts in the corpus). By contrast, text dispersion keyness helped us obtain the largest number of content distinctive bundles (i.e., bundles that clearly distinguish the target corpus from the reference corpus). Text dispersion keyness also produced the highest number of bundles that were both content generalizable and distinctive. Researchers may therefore wish to make a choice among these methods based on the objectives of their analysis.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100245"},"PeriodicalIF":0.0,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713472","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}
Kathy Minhye Kim , Michael Bornstein , Xiaoyi Liu , Yongyue Li
{"title":"A Bayesian approach to implicit L2 learning: Web-based replication of Williams (2005) and Kim et al. (2023) with underrepresented learners","authors":"Kathy Minhye Kim , Michael Bornstein , Xiaoyi Liu , Yongyue Li","doi":"10.1016/j.rmal.2025.100242","DOIUrl":"10.1016/j.rmal.2025.100242","url":null,"abstract":"<div><div>Expanding participation beyond university samples is increasingly seen as key to more inclusive and generalizable SLA research. This study examined the effectiveness of web-based experimentation for L2 grammar learning among adults without post-secondary education—an underrepresented population in the field. Building on Williams (2005) and replicating Kim et al. (2023), we implemented a fully remote, researcher-supervised design to enhance accessibility and participant engagement. Forty-nine participants without college degrees completed a semi-artificial language learning task. Bayesian analyses indicated comparable overall learning outcomes, with greater variability in training accuracy and item reliability in the web-based condition. Crucially, no evidence of implicit learning was found among unaware learners—replicating Kim et al. (2023) and highlighting limits to generalizing such effects to non-traditional populations. These findings underscore the importance of inclusive research designs that expand research access while safeguarding data quality.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100242"},"PeriodicalIF":0.0,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703178","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}
Allie Spencer Patterson , Christopher Nicklin , Joseph P. Vitta
{"title":"Methodological recommendations for webcam-based eye tracking: A scoping review","authors":"Allie Spencer Patterson , Christopher Nicklin , Joseph P. Vitta","doi":"10.1016/j.rmal.2025.100244","DOIUrl":"10.1016/j.rmal.2025.100244","url":null,"abstract":"<div><div>Internet-based experiment administration has enabled remote access to diverse populations and large pools of crowdsourced participants. In recent years, webcam-based eye tracking has extended these benefits to a research paradigm historically limited to researchers with sufficient resources for access to technology. While a proliferation of eye-tracking research could reap benefits for applied linguistics and related fields, reporting standards should be modified and updated to account for not only the unique logistic flexibility offered via online administration, but also the methodological limitations of the technology, which include lower spatial/temporal sensitivity and stringent calibration requirements. To facilitate the creation of such standards, a methodological scoping review of 31 experiments published in 22 studies was conducted. Researchers were found to have adhered to psycholinguistic reporting standards for sample size and participant demographics. However, reporting of minimum inclusion criteria, specifically for minimum hardware standards, was often found to lack sufficient detail for replication and requires refinement. Furthermore, critical experiment details, such as calibration procedures, were often found to lack vital details. Based on the findings derived from this review, we present a list of methodological recommendations for implementing and reporting psycholinguistic webcam-based tracking experiments.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100244"},"PeriodicalIF":0.0,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144711720","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":"Validation of online L2 vocabulary tests: Test performance across laboratory, virtual meeting, and crowdsourcing contexts","authors":"Ayako Aizawa","doi":"10.1016/j.rmal.2025.100246","DOIUrl":"10.1016/j.rmal.2025.100246","url":null,"abstract":"<div><div>Online data collection has become increasingly common in diverse fields, including marketing and psychology, and is gaining ground in applied linguistics. Although concerns have been raised about the validity and reliability of online assessments, previous research on online data collection suggests that, with appropriate precautions, data quality can be comparable to that obtained using in-person methods. However, the validity and reliability of online vocabulary tests have not been thoroughly investigated. To fill this gap, the present study compared the results of online vocabulary tests with those of face-to-face administration. In this study, 159 Japanese university students took the Vocabulary Size Test and Phrasal Vocabulary Size Test in three environments: (a) in-person (laboratory), (b) online with supervision (virtual meeting), and (c) online without supervision (crowdsourcing). Reliability and validity were analysed, and results showed that test performance was largely comparable: test environment and presence or absence of supervision had minimal effects on three out of the four tests, with only the meaning recall format of the Vocabulary Size Test showing significantly inflated scores in the crowdsourcing condition. While the findings suggest that pooling data online and aggregating data from different environments are feasible for vocabulary testing research, they also highlight the need for careful planning in research design to achieve a desirable environment for the participants to take the tests.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100246"},"PeriodicalIF":0.0,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696442","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":"Exploring sentiment across disciplines and argumentative moves: A sentiment analysis of open-access comments","authors":"Wenjuan Qin , Yueling Sun , Tan Jin","doi":"10.1016/j.rmal.2025.100243","DOIUrl":"10.1016/j.rmal.2025.100243","url":null,"abstract":"<div><div>Sentiment analysis, a computational method originating from natural language processing, has recently gained interest in applied linguistics as a tool for examining evaluative language in academic discourse. This study applies sentiment analysis to analyzing open-access comments (OA comments), a novel academic genre designed to engage a broad readership across disciplines. Studying sentiment in these comments is crucial, as it reveals how scholars express not only factual information but also their emotion and attitudes towards the topics under discussion. The corpus includes 361 open-access comments published in <em>Nature</em>. The results reveal significant differences in sentiment scores across hard and soft science disciplines and in different argumentative moves. These findings highlight the potential of sentiment analysis as a promising method to explore open-assess comments as a unique academic genre, deepening our understanding of academic writing and informing academic writing pedagogy, particularly in emerging hybrid genres such as OA comments.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100243"},"PeriodicalIF":0.0,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144694345","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":"Developing and piloting SemiMed—A resource for semi-technical medical vocabulary","authors":"Chinh Ngan Nguyen Le, Julia Miller","doi":"10.1016/j.rmal.2025.100239","DOIUrl":"10.1016/j.rmal.2025.100239","url":null,"abstract":"<div><div>Semi-technical medical vocabulary—words that often convey different meanings depending on context—commonly poses challenges for teaching and learning. These difficulties are largely due to polysemy and homography, which are not fully addressed in conventional dictionaries or frequency wordlists. This study aimed to develop and pilot a new lexical resource, named SemiMed, that explicitly accounts for polysemy and homography in semi-technical medical vocabulary. The starting point was Hsu’s (2013) corpus-based Medical Word List, which is useful for the teaching and learning of words with single but not multiple meanings. Multi-meaning semi-technical medical words in Hsu’s list were analyzed using a lexical semantic approach to polysemy and homography. A corpus-based analysis followed, to quantify word meaning frequency. Cantos and Sanchez’s (2001) Lexical Constellations were then adapted to showcase intricate interrelations between general and specialized meanings of semi-technical medical words. To examine SemiMed’s usefulness, a pilot study was conducted where 18 EFL medical students were provided with lexical resources, including SemiMed samples and conventional dictionaries, to help them use appropriate vocabulary while role-playing targeted medical scenarios. Focus groups were conducted to gain participants’ feedback on the usefulness of SemiMed.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100239"},"PeriodicalIF":0.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144685765","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":"From black box to transparency: Enhancing automated interpreting assessment with explainable AI in college classrooms","authors":"Zhaokun Jiang , Ziyin Zhang","doi":"10.1016/j.rmal.2025.100237","DOIUrl":"10.1016/j.rmal.2025.100237","url":null,"abstract":"<div><div>Recent advancements in machine learning have spurred growing interests in automated interpreting quality assessment. Nevertheless, existing research is subject to certain limitations, including the insufficient examination of language use quality, restricted modeling effectiveness due to data scarcity at the highest and lowest performance tiers, and a lack of efforts to explain model predictions. To address these gaps, the present study proposes a multi-dimensional modeling framework that integrates feature engineering, data augmentation, and explainable machine learning. This approach prioritizes explainability over “black box” predictions by utilizing only construct-relevant, transparent features and conducting SHAP analysis, an explainable AI (XAI) method. Our results demonstrated relatively strong predictive performance on a self-compiled English-Chinese consecutive interpreting dataset: XGBoost excelled in predicting fluency (<em>ρ</em> = 0.86, RMSE = 0.61) and target language use (<em>ρ</em> = 0.79, RMSE = 0.75), while Random Forest was optimal for modeling information completeness (<em>ρ</em> <strong>=</strong> 0.68, RMSE = 1.05). SHAP analysis identified the strongest predictive features for each dimension: BLEURT and CometKiwi scores for information completeness, pause-related features for fluency, and Chinese-specific phraseological diversity metrics for language use. Overall, this study presents a scalable, reliable, and transparent alternative to traditional human evaluation, holding significant implications for automated language assessment. Notably, the emphasis on explainability facilitates the provision of detailed diagnostic feedback for learners and supports self-regulated learning—advantages not afforded by automated scores in isolation.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100237"},"PeriodicalIF":0.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631669","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":"Applying a polytomous Rasch model to investigate Likert scale functioning and L2 writing strategy use","authors":"Apichat Khamboonruang","doi":"10.1016/j.rmal.2025.100240","DOIUrl":"10.1016/j.rmal.2025.100240","url":null,"abstract":"<div><div>While Rasch models have been increasingly employed in applied linguistics research, their use remains underexplored in L2 writing strategy research, which has relied primarily on statistical methods that assume continuous data. This study aimed to address this methodological gap by applying a polytomous Rasch modelling approach to investigate Likert scale functioning in the context of L2 writing strategy use. Participants were 172 Thai EFL English-major undergraduates who completed a 26-item, 5-category Likert-type scale designed to measure five strategy domains: metacognitive, effort-regulation, cognitive, social, and affective strategies. The data were analysed using a Rasch rating scale model (RSM) implemented in Winsteps and Facets software programmes. The main results indicated that the RSM analysis provided sound evidence of appropriate item and category functioning, while revealing specific areas for refinement, such as limited item coverage, item redundancy, and category disordering. The RSM analysis also revealed systematic trends in Thai EFL students’ writing strategy use across domains and proficiency levels: metacognitive strategies were used most often and clearly differentiated higher- and lower-achieving students, while social strategies were less common and more frequently used by lower achievers. These findings highlight the value of a polytomous Rasch modelling approach in examining not only rating scale functioning but also writing strategy use. The present findings have implications for rating scale validation and L2 writing strategy instruction.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100240"},"PeriodicalIF":0.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144597529","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}