Monolingual children tend to assume that a word labels only one object, and this mutual exclusivity supports referent selection and retention of novel words. Bilingual children accept two labels for an object (lexical overlap) for referent selection more than monolingual children, but in these previous studies, information about speakers’ language backgrounds was minimal. We investigated monolingual and bilingual 4-year-old children’s ability to apply mutual exclusivity and lexical overlap flexibly when objects were labelled either by one or two speakers with the same or different language backgrounds. We tested referent selection and retention of word–object mappings. Both language groups performed similarly for mutual exclusivity, were more likely to accept lexical overlap in the two-language than one-language condition, and performance was similar for referent selection and later retention. Monolingual and bilingual children can adapt their word-learning strategies to cope with the demands of different linguistic contexts.

We explored the relationships between L2 utterance fluency and cognitive fluency in monologic and dialogic tasks. The study involved 136 Chinese university-level English learners. Utterance fluency was measured through speed, breakdown, and repair fluency aspects. Cognitive fluency was indicated by L2 lexical and syntactic processing efficiency measures. Stepwise regression models, including metrics of L2-specific cognitive fluency, L2 knowledge, and L1 utterance fluency as predictors, targeted L2 utterance fluency as the dependent variable. We found that L2 cognitive fluency predicted limited variance in utterance fluency, with its influence more evident in monologues. L2 lexical processing efficiency paralleled syntactic processing efficiency’s importance in the monologic task but surpassed it in dialogues. Moreover, L2 processing speed had a more significant impact on utterance fluency than processing stability across both contexts. We suggest that cognitive fluency is not the sole determinant of utterance fluency; L2 knowledge and L1 utterance fluency play non-negligible roles.

From the early use of TF-IDF to the high-dimensional outputs of deep learning, vector space embeddings of text, at a scale ranging from token to document, are at the heart of all machine analysis and generation of text. In this article, we present the first large-scale comparison of a sampling of such techniques on a range of classification tasks on a large corpus of current literature drawn from the well-known Books3 data set. Specifically, we compare TF-IDF, Doc2vec and several Transformer-based embeddings on a variety of text-specific tasks. Using industry-standard BISAC codes as a proxy for genre, we compare embeddings in their ability to preserve information about genre. We further compare these embeddings in their ability to encode inter- and intra-book similarity. All of these comparisons take place at the book “chunk” (1,024 tokens) level. We find Transformer-based (“neural”) embeddings to be best, in the sense of their ability to respect genre and authorship, although almost all embedding techniques produce sensible constructions of a “literary landscape” as embodied by the Books3 corpus. These experiments suggest the possibility of using deep learning embeddings not only for advances in generative AI, but also a potential tool for book discovery and as an aid to various forms of more traditional comparative textual analysis.

This article introduces a strategy for the large-scale corpus analysis of music audio recordings, aimed at identifying long-term trends and testing hypotheses regarding the repertoire represented in a given corpus. Our approach centers on computing evolution curves (ECs), which map style-relevant features, such as musical complexity, onto historical timelines. Unlike traditional approaches that rely on sheet music, we use audio recordings, leveraging their widespread availability and the performance nuances they capture. We also emphasize the benefits of pitch-class features based on deep learning, which improve the robustness and accuracy of tonal complexity measures compared to traditional signal processing methods. Addressing the frequent lack of exact work dates (year of composition) in historical corpora, we propose a heuristic method that aligns works with timelines using composers’ life dates. This method effectively preserves historical trends with minimal deviation compared to using actual work dates, as validated against available metadata from the Carus Audio Corpus, which spans 450 years of choral and sacred music and contains 5,729 tracks with detailed metadata. We demonstrate the utility of our strategy through case studies of this corpus, showing how ECs provide insights into stylistic developments that confirm expectations from musicology, thus highlighting the potential of computational studies in this field. For example, we observe a steady increase in tonal complexity from the Renaissance through the Baroque period, stable complexity levels in the 19th and 20th centuries, and consistently higher complexity in minor-key works compared to major-key works. Our visualizations also reveal that vocal music was more complex than instrumental music in the 18th century, but less complex in the 20th century. Finally, we conduct comparative analyses of individual composers, exploring how historical and biographical contexts may have influenced their works. Our findings highlight the potential of this strategy for computational corpus studies in musicological research.

Despite comments in the ELT literature on the importance of word-stress for comprehensibility in English, there are many places where native speakers of English appear to pay it little attention, showing systematic variation as well as errors. At the very least, there is a paradox here, in that learners are told to get a feature right that native speakers feel free to ignore. More detailed consideration, though, shows that matters are not as simple as this implies. In this paper, several types of stress variation in English are exemplified, and it is also shown that in everyday usage native English speakers are flexible in what they will accept where stress is concerned. This raises questions about the best model for teaching stress in English as a second or foreign language. A simple right/wrong dichotomy is unlikely to reflect native usage.

To better understand language teacher turnover, this study closely replicates and extends McInerney et al.’s (2015) research, which found that teacher commitment predicted turnover intentions to schools (44.2%) and the profession (45.2%) among Hong Kong schoolteachers (N = 1,060). Given the relatively stable employment conditions in that context, the generalizability of these findings to more mobile populations, such as expatriate native English-speaking teachers (NESTs), remains uncertain. In this replication, (1) the population was changed to NESTs in East Asia, and (2) subgroup comparisons were extended to reflect distinctions relevant to the replication sample. Additionally, results were directly compared to the original. A total of 215 NESTs participated. Results showed similar directional patterns but stronger effects: commitment explained 51.8% of variance in turnover intentions to schools and 59.7% to the profession. Affective commitment was the strongest predictor, though NESTs reported lower commitment and higher turnover intentions than in the original study.

This study examined the interaction of different types of crosslinguistic cues in second language (L2) morphosyntactic processing. Our target constructions, Korean morphological causatives, contain morphosyntactic constraints that present interlingual overlap for Japanese speakers when the construction is derived from an intransitive verb, while constituting interlingual contrast when derived from a transitive verb. For Chinese speakers, these constraints only exist in the L2 and thus constitute L2-unique information. In two self-paced reading experiments involving proficiency-matched Japanese- and Chinese-speaking learners of Korean, we found that Japanese speakers successfully detected morphosyntactic errors only in the intransitive-based construction, which shares overlapping constraints with Japanese, but not in the transitive-based construction whose morphosyntactic constraints contrast with the Japanese counterparts. In contrast, Chinese speakers exhibited sensitivity to the violations in both intransitive- and transitive-based constructions. These findings suggest that crosslinguistic competition causes a major problem in L2 sentence processing.

The love factor in the field of second language acquisition has gained considerable traction since the turn of the century. This article is the first to take a variationist perspective to investigate how multilingual coupledom affects sociolinguistic development in the second language (L2). Participants were 76 users of L2 German living in Austria, all of whom were in a romantic relationship with an Austrian partner. We analyzed the effects of multilingual coupledom on self-reported changes in learners’ use of, attitudes toward, and proficiency in standard German, the Austrian dialect variety, and first language(s), and whether (psycho-)social variables moderate this relationship. Individual differences in psychological and social variables (e.g., adaptability, Open-mindedness, length of residence, orientation toward the Austrian dialect) predicted reported changes in the sociolinguistic repertoire. Qualitative analysis revealed a blended operation of socioaffective and exposure-related factors, which helped explain why, how, and for whom multilingual coupledom affects (socio-)linguistic development.

The present article provides a diachronic analysis of the negation and contraction patterns of will and would in British and American English. It contrasts nineteenth- and twentieth-century data from British and American fiction, comparing the collocational preferences of negated versus non-negated and contracted versus non-contracted modals. Utilising Configural Frequency Analysis, we explore frequency differences as well as variety-specific association patterns. Results reveal predominantly commonalities. The spread of the modal contractions ’ll and ’d as well as the spread of the contracted negator n’t proceeded at similar speeds in both varieties. The analysis at the level of cotextual configurations shows the emergence of several emancipated subschemas that are each differentially entrenched and conventionalised.

How do sensory experiences shape the words we learn first? Most studies of language have focused on hearing children learning spoken languages, making it challenging to know how sound and language modality might contribute to language learning. This study investigates how perceptual and semantic features influence early vocabulary acquisition in deaf children learning American Sign Language and hearing children learning spoken English. Using vocabulary data from parent-report inventories, we analyzed 214 nouns common to both languages to compare the types of meanings associated with earlier Age of Acquisition. Results revealed that while children in both groups were earlier to acquire words that were more strongly related to the senses, the specific types of sensory meaning varied by language modality. Hearing children learned words with sound-related features earlier than other words, while deaf children learned words with visual and touch-related features earlier. This suggests that the easiest words to learn are words with meanings that children can experience first-hand, which varies based on children’s own sensory access and experience. Studying the diverse ways children acquire language, in this case deaf children, is key to developing language learning theories that reflect all learners.

Speakers adapt their syntactic preferences based on syntactic experience. However, it is not clear what cognitive mechanism underlies such adaptation. While error-based mechanisms suggest that syntactic adaptation depends only on the relative frequency of syntactic structures, memory-based mechanisms suggest that both frequency and recency of syntactic structures matter in syntactic adaptation. To distinguish between these two mechanisms, I manipulated the order of passive and active primes in two syntactic priming experiments, presenting passive primes either before active primes (active-recent condition) or after them (passive-recent condition), while controlling for frequency. The results showed that the magnitude of priming was numerically greater in the passive-recent condition than in the active-recent condition in Experiment 1, and significantly greater in Experiment 2. These results provide novel evidence that syntactic adaptation involves a memory-based mechanism.

This study investigated an 18‑week teacher education model grounded in technological pedagogical content knowledge (TPACK). Known as CATERR (comprehending, analyzing, teaching, evaluating, reflecting, and refining), this teacher education model cultivated the computer-assisted language learning (CALL) competencies of 43 content and language integrated learning (CLIL) preservice teachers (PSTs) from Taiwan. The model promotes peer coaching, where participants collaborate, reflect, and refine their teaching over three rounds. The study utilized a multi-method case study and triangulated the quantitative and qualitative data. Quantitative data refers to the TPACK-CLIL questionnaire administered before and after the teacher education model. Qualitative data included lesson plans, self-analysis, teaching demonstration videos, revised lesson plans, classroom discussion records, peer evaluations, and reflection notes. Data analysis involved paired-samples t-tests and descriptive statistics for the coding framework, thematic analysis for qualitative data, and a repeated measures ANOVA to compare three total scores across three rounds using scoring rubrics. Results showed that the CATERR teacher education model enhanced CLIL PSTs’ self-perceived and observed CALL competencies. Specifically, as “digital native” PSTs with high levels of technological knowledge (TK), they successfully transferred their TK into TPACK by adding pedagogical values and contextualizing the ICT tools in their CLIL lessons. Meanwhile, their ability to use ICT tools to facilitate interaction and students’ autonomous learning substantially improved. The theoretical and pedagogical implications for CALL teacher education research and practice are discussed.

This study examines how English is semiotically represented in video games, an under–explored but promising virtualscape. Drawing on the concept of semiotic landscape, this study critically explores how English and other semiotic resources work together to create social meanings and what are the ideological forces governing the process of semiotic appropriation. Data were collected from the in–game English representation and other semiotic resources from two female–oriented Chinese video games. It is found that English embodies cosmopolitan and poetic dispositions in the romanticized virtual space. Such dispositions are made relevant to the globally consuming elite class who are assumed not only to have access to the world consumption opportunities but also to show literary appreciation with a sense of distinction. The paper highlights the implications of these findings for understanding romance–mediated English as classed and gendered ideologies in the context of the increasing popularity of female–oriented game sphere.

This paper introduces the Chinese Learner English Corpus (CLEC), comprising argumentative texts written by Chinese lower and upper secondary school students. CLEC expands learner corpus research by including texts from intermediate-level learners and rich metadata on their backgrounds, including engagement with self-initiated, so-called Extramural English (EE) activities outside the classroom. To illustrate potential uses, two case studies are presented. The first uses a keyword analysis to reveal thematic and stylistic differences between CLEC and its Swedish counterpart, SLEC, highlighting linguistic priorities related to distinct learning contexts. The second investigates lexical bundles associated with gaming, demonstrating how EE engagement might influence learners’ use of multiword units. Freely available online, CLEC facilitates contrastive interlanguage analysis and supports further research into L2 learning and use, particularly regarding the role of language exposure. The corpus is also a valuable resource for teacher trainees aiming to deepen their understanding of SLA processes.