Abstract In an era of global migration, where public discourse often assumes that migrants lack exposure to and command of local majority language(s), it is a crucial research task to understand how migrants learn and use new languages in their everyday lives. This study provides empirical evidence about the quantity and nature of everyday language exposure and use (LEU) among migrants in Sweden. Using the Experience Sampling Method and the Lang-Track-App, we collected rich self-report data across three weeks from 45 adult migrants with diverse backgrounds. Group-level quantitative analyses revealed that, despite considerable individual variation and occasional linguistic challenges, Swedish was the most used language across a broad range of self-reported daily activities. Complementary qualitative analysis of two cases illustrated the nuanced and fluctuating nature of LEU, which did not align predictably with structural factors such as employment, student status, or social networks. Instead, LEU appeared to emerge through dynamic interplay between individual agency and contextual affordances. These findings challenge prevailing narratives about migrants’ limited contact with the majority language and underscore the value of capturing LEU through temporally and contextually sensitive methods.

Abstract Language commodification has emerged as a prominent field of inquiry for studying how languages are transformed into marketable commodities within the globalized economy. In this contribution, I argue that the discussions have become overly concerned with theoretical technicalities, revealing more about how we, in our professional capacity as researchers, think about language commodification than how our participants imagine language as a commodity and are affected by these imaginations. By conceptualizing language commodification as a language ideological process that is spatiotemporally structured, I conduct an emic exploration of commodity imaginations and their consequences in the context of online Mandarin teaching. While ideologically commodifying Taiwanese Mandarin allows the twelve interviewed Taiwanese teachers to situate themselves on the market in a way that makes sense of their linguistic repertoires, past experiences and personal convictions, it also raises concerns about their status as speakers of a non-dominant Mandarin variety, leading to material and ideological challenges thus far underexplored in the literature.

Abstract This article revisits the dilemmas of creativity–standardization, inclusion–fixity, and meaning–form, as proposed by Jeon et al. (2025), in relation to the intersection of generative artificial intelligence (GenAI) within translanguaging. While their contribution centers on a mechanism-level analysis of the input–output asymmetry of large language models, I adopt a pedagogical perspective and argue that these dilemmas remain pertinent in the context of pedagogical translanguaging. However, they may not always apply in the same way across classroom settings, particularly when standardization, fixity, and form are not inherently problematic and are instead intentionally calibrated by educators to foster creativity, inclusion, and meaning. I therefore recast the dilemmas as questions of classroom governance rather than properties of GenAI or translanguaging, and propose a reciprocal framing–reframing approach in which pedagogical translanguaging sets the terms of GenAI’s participation and GenAI, once introduced, presses those terms to be made explicit and auditable.

Abstract This study critically examines the intersection of English language teaching (ELT) and global citizenship education (GCE) in higher education (HE) through data from state-funded universities in the Global South (Colombia, Iraq, Thailand, and Vietnam). It examines how students, educators, and administrators perceive and engage with global and intercultural citizenship through the medium of English. Data were collected through 126 semi-structured interviews and analysed using thematic and content analysis to identify cross-contextual patterns and context-specific interpretations. Participants described a two-fold experience in which English facilitated global academic, professional, and personal access and mobility, while generating concerns about the erasure of local identities and knowledge systems, framed by enduring forms of epistemic inequality, cultural hierarchy, and instrumental pressures reinforced by neoliberal frameworks. In response, many educators and learners challenged dominant Anglophone models by adopting decolonial pedagogies that emphasise ethical engagement, foster critical reflexivity, and reflect locally rooted practices. The study calls for reconfiguring GCE and ELT as interconnected domains of transformation that support inclusive, context-responsive, and socially engaged models of global citizenship within Southern HE settings.

Abstract Heritage language speakers’ self-perception as native has been recently shown to be linked to various measures of proficiency, including objective measures of lexical and grammatical knowledge. The relationship between age of first exposure, a crucial factor dividing heritage from L2 speakers in the traditional sense, is less clear. This paper, thus, explores the relationship between a heritage and traditional L2 classroom learner’s perception as native and their age of first exposure with the proficiency and grammatical knowledge that they attain. Findings confirm that native perception is intrinsically linked to outcomes measured as formal proficiency, self-rated proficiency, and morphosyntactic knowledge. However, age of exposure is linked to self-rated proficiency but neither formal proficiency nor morphosyntactic knowledge. The latter finding crucially suggests that high proficiency can be attained, despite a late start. Heritage speakers often share some intrinsic properties linked to literacy, language use, or input, which result in grammatical knowledge that is neither L2 nor L1-like, but properly “heritage”-like.

Abstract With the advancement of generative artificial intelligence (AI), foreign language (FL) education has stepped into a transformative new era. Despite the widespread usage of generative AI, understanding the role of self-regulation in micro-level language skills within generative AI-enhanced learning environments is inadequate. To address this gap, drawn on self-regulated learning (SRL) theory, this study explores how mobile self-regulated learning (MSRL) affects FL learners’ generative AI awareness (optimism and dependence) and morphological skills (discrimination, interpretation, and recognition) among 614 English FL learners. The results of path analysis based on partial least squares reveal that MSRL is positively associated with both dimensions of generative AI awareness and negatively associated with the three morphological skills. The mediation analysis results reveal that the dependence dimension of generative AI awareness significantly mediates the relationship between MSRL and morphological skills (interpretation and discrimination). Contrarily, optimism does not play a mediating role. This study extends SRL theory into micro-level language skills development in AI contexts and provides pedagogical implications for designing language instruction and learning platforms in the digital era.

Abstract Extramural English (EE), referring to English-mediated leisure activities, has become a core part of English learning in many contexts. This prompts the need to explore how informal learning can best interact with English language teaching (ELT). To investigate possible ways of linking EE and ELT, we asked secondary school teachers in Austria, Finland, France, and Sweden in a survey to illustrate an activity they would do with students making extensive use of EE. We recruited teachers through convenience sampling and received responses from 239 teachers. Swedish teachers most frequently illustrated activities, followed by Austrian, Finnish, and French teachers. Austrian and French teachers mostly referred to activities based on authentic (i.e. non-pedagogic) material. Contrarily, Finnish and Swedish teachers more often illustrated activities raising learners’ awareness of register differences. The findings point to possible contextual variation in how EE is considered in instruction, potentially influenced by political and sociocultural factors, such as learners’ average EE use and dominant instructional priorities. The findings can inform stakeholders seeking to support teachers in effectively connecting classroom instruction with learners’ EE.

Abstract Understanding what makes second language (L2) listening comprehension difficult is crucial for advancing language learning and assessment. In L2 listening assessment, a key challenge is developing items with targeted difficulty levels. This difficulty can be influenced by textual and acoustic features from different item segments (i.e. stimuli, stems, and options) embedded in a multi-layered structure, along with task-related features. This study explores a feature-based machine learning (ML) approach to predicting difficulty of multiple-choice listening items on a local language proficiency test. We extracted construct-relevant textual and acoustic features from item segments across five dimensions: lexical complexity, syntactic complexity, fluency, pronunciation, and similarities among item segments. Incorporating these features, we compared traditional and mixed-effects ML models for predictive accuracy and interpretability. The best-performing model—a mixed-effects Ridge model with twenty-three features—achieved high accuracy (R2 = 0.860) and showed meaningful feature-difficulty relationships. This study presents methodological innovations for item difficulty modeling and offers practical implications for human- and machine-mediated item development. It also demonstrates potential of incorporating computational linguistics and ML in enhancing L2 listening assessment.