{"title":"Applying the confirmatory bifactor modeling and omega-family indices: The case of the foreign language classroom anxiety scale","authors":"Xian Zhang","doi":"10.1016/j.rmal.2025.100265","DOIUrl":"10.1016/j.rmal.2025.100265","url":null,"abstract":"<div><div>This study demonstrates how to use confirmatory bifactor analysis (CbFA) and omega-family indices to evaluate the dimensionality of the Foreign Language Classroom Anxiety Scale (FLCAS). The FLCAS is generally regarded to have high reliability, which is supported by high Cronbach's alpha values often observed in the literature. However, as the FLCAS has often been shown to have multidimensional constructs, it remains unclear if the scale can measure a general construct in the presence of multidimensionality. Confirmatory bifactor modeling can be used to assess whether an instrument can measure a single general psychological construct while accounting for multidimensionality. The model posits a general factor that explains the shared variance across all items, along with specific factors that capture the unique variance within subsets of items. With CbFA, the dimensionality of a factor structure can then be closely examined with statistics such as construct replicability, explained common variance, and omega family indices (e.g., Reise, 2012). In this demonstration, I will show that a smaller subset of FLCAS items effectively measures the general FLA construct, with the general factor explaining the largest portion of the model-wise variance. I will then present recommendations for determining when aggregated scores from a reduced item set can reliably represent the general construct while preserving essential psychometric properties. Finally, I will discuss key considerations for applying and interpreting CbFA in foreign language research.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100265"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145264664","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}
Hung Tan Ha , Duyen Thi Bich Nguyen , Tim Stoeckel
{"title":"Investigating LID in four test conditions - Do instructions, test formats and item positioning matter?","authors":"Hung Tan Ha , Duyen Thi Bich Nguyen , Tim Stoeckel","doi":"10.1016/j.rmal.2025.100233","DOIUrl":"10.1016/j.rmal.2025.100233","url":null,"abstract":"<div><div>Recent research has found the Updated Vocabulary Levels Test (UVLT) to have Local Item Dependence (LID), a violation to the central assumption of all Rasch and Item Response Theory models. LID in the UVLT is hypothesized to be caused by a feature of matching tasks: once an option is selected for one target word, it will not be selected for another. It is also hypothesized that if this feature is removed, LID will be reduced. The present study investigated the effects of LID in four test conditions. The first employed the 3:6 matching format of the UVLT with no instruction concerning option recycling. The second used the same format but with instructions encouraging option recycling. The third utilized a multiple-choice format, with items belonging to the same UVLT cluster using identical sets of 6 options and placed adjacently. The fourth also used a multiple-choice, 6-option format, but items sharing identical options were far apart, making them less “local”. Data from 231 Vietnamese EFL learners were analyzed using Rasch unidimensional modelling and Rasch Testlet Modelling (RTM). Person estimates from the unidimensional models and the general dimensions from the RTMs were compared and correlated. Substantial LID was present in Conditions 1–3. Significant distortions of person estimates were found in all test conditions. However, the findings showed that LID had a negligible impact on person ordering in all test conditions.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100233"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144556765","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":"2025-12-01","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":"Indonesian cross-linguistic named entity recognition","authors":"Danang Arbian Sulistyo , Aji Prasetya Wibawa , Didik Dwi Prasetya , Fadhli Almu’iini Ahda","doi":"10.1016/j.rmal.2025.100236","DOIUrl":"10.1016/j.rmal.2025.100236","url":null,"abstract":"<div><div>This study examines the potential of Named Entity Recognition (NER) in translating cross-biblical texts of Indonesian, Madurese, and Javanese. The goal is to enhance translation precision by incorporating entity categorization. The approach involves training an NER model using Conditional Random Fields (CRF) and evaluating its performance on the Book of Joshua. The annotated dataset includes features such as word identity, shape, part-of-speech identifiers, and semantic information. Tagging the data with labels such as Person, Location, and Organization reveals variations in effectiveness across languages. Indonesian yields the highest F1 score (78.69), reflecting consistent performance across all parameters. Although Madurese achieves a high recall for Location entities (82.16), its precision is lower (74.99). Javanese demonstrates strong precision in identifying locations (77.46), but a slightly lower recall score (77.21). The findings suggest the need to tailor the NER model to suit the specific characteristics of low-resource languages for improved translation quality.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100236"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144579186","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, 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":"2025-12-01","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":"Leading a scoping review on L2 pronunciation: Some key elements of methodology","authors":"Linda Terrier , Marie Garnier , Saandia Ali","doi":"10.1016/j.rmal.2025.100216","DOIUrl":"10.1016/j.rmal.2025.100216","url":null,"abstract":"<div><div>This article describes the methodology of a scoping review covering 25 years of research on L2 English pronunciation. We focus on two key methodological steps required in any scoping review: identifying the information source and selecting the studies. We present a rationale for employing a manual search across prominent journals in the fields of phonetics and phonology, second language acquisition, and second language learning and teaching. We describe how we delineated the scope of the review by identifying 35 prominent journals and how we organized teamwork to select relevant studies. We show that seemingly straightforward inclusion criteria (L2 English, empirical research, and pronunciation) raise questions about the objects of study in the field. The final corpus includes 463 articles published in the 35 identified journals between 1996 and 2020. We demonstrate that Arksey and O’Malley’s framework for scoping reviews can be applied and adapted to the specificities of L2 English pronunciation research, but we also highlight the challenge of iterativity in study selection. As we present the distribution of articles over time and across journals, we make recommendations for future scoping reviews regarding the time span of the review and the identification of the initial information source. In particular, the <em>Journal of Second Language Pronunciation</em>, which stands out as a central venue for L2 English pronunciation research, would have been missed had we used a more typical keyword search across academic databases.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100216"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524220","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":"Comparing lab-based and remote data collection methods in second language acquisition research. A close replication study","authors":"Kevin McManus , Katherine Kerschen , Yulia Khoruzhaya , Jingyuan Zhuang","doi":"10.1016/j.rmal.2025.100249","DOIUrl":"10.1016/j.rmal.2025.100249","url":null,"abstract":"<div><div>Collecting data remotely is now increasingly common in second language acquisition (SLA) research. However, very little is known about extent to which research data collected remotely are comparable and generalizable to those collected face-to-face in a lab. To address this question, we closely replicated a theoretically and academically impactful line of SLA research, with the seminal study by Ellis and Sagarra (2010b) being frequently cited in the field. In addition, this study has been replicated three times (Ellis et al., 2014; Ellis & Sagarra, 2011; McManus et al., 2025), with all studies being conducted in lab-based contexts. In the current study, our close replication modified one variable to better understand the comparability of research data collected remotely and in a lab. Findings showed that use of the same materials in lab-based and remote modalities did not significantly impact the study’s conclusions, indicating high levels of comparability between these data collection modalities for accuracy data. The implications of these results for the use of remote data collection methods are discussed.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100249"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781784","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":"Do data collection methods matter for self-reported L2 individual differences questionnaires? In-person vs crowdsourced data","authors":"Ruirui Jia , Ekaterina Sudina , Kejun Du","doi":"10.1016/j.rmal.2025.100235","DOIUrl":"10.1016/j.rmal.2025.100235","url":null,"abstract":"<div><div>Crowdsourcing offers great advantages in data collection by enabling researchers to recruit a large number of participants across geographical boundaries within a short period of time. Despite the benefits of crowdsourcing, no study has explored its validity in collecting self-reported individual differences (ID) data in second language (L2) research. The present study aims to address this gap by examining crowdsourcing as a viable alternative or complementary tool to traditional in-person data collection. We recruited a total of 209 in-person and 209 crowdsourced participants for comparison. Both groups completed the short versions of the Foreign Language Classroom Anxiety Scale and the Foreign Language Enjoyment Scale, provided their demographic and language learning background information, and completed the LexTALE test. Measurement invariance testing revealed that most (sub)constructs exhibited partial or full invariance, indicating stability in the measurement systems across both data collection settings. However, crowdsourced participants reported higher enjoyment and lower anxiety than in-person participants. These differences can be attributed to the more relaxed mental state of the crowdsourced participants who completed the survey outside of the classroom. Moreover, some crowdsourced participants tended to overrate their English proficiency and exhibited potentially dishonest behavior during the LexTALE test. These findings suggest that although crowdsourcing offers valuable opportunities for data collection in L2 ID research, the potential for inflated self-assessments and questionable behavior in an unsupervised online testing environment must be considered. Thus, the use of crowdsourcing platforms to collect self-reported L2 ID data requires caution and careful preparation.</div></div>","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100235"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549574","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":"2025-12-01","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":"Corrigendum to “Timelines: Visualizing time in narrative research” [Research Method in Applied Linguistics Vol.4/2, 2025.100215]","authors":"Eric K. Ku","doi":"10.1016/j.rmal.2025.100222","DOIUrl":"10.1016/j.rmal.2025.100222","url":null,"abstract":"","PeriodicalId":101075,"journal":{"name":"Research Methods in Applied Linguistics","volume":"4 3","pages":"Article 100222"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617963","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}