People are frequently concerned about the impressions they make on others (referred to as metaperceptions), but their insights are often inaccurate. Illustrating the phenomenon called the liking gap, speakers interacting in their first language (L1) and second language (L2) tend to underestimate how much they are liked by their interlocutor, and these judgments often predict their desire to engage in future interaction and collaboration. To understand the scope of this bias and its consequences, we focused on L1–L2 dyadic interaction, examining metaperception as a potential barrier to conversations between university students. We recruited 58 previously unacquainted university students to perform a 10-min academic discussion task between one L1 and one L2 speaker. Afterward, the speakers (a) assessed each other’s interpersonal liking, speaking skill, and interactional behavior; (b) provided their metaperceptions of their interlocutor’s assessments of the same dimensions; and (c) estimated their interest in future interaction with the same interlocutor. All speakers showed a reliable metaperception bias to underestimate their interpersonal liking, speaking skill, and interactional behavior. However, only L1 speakers’ desire to engage in future interaction was associated with their metaperceptions of interpersonal liking. We discuss implications of this finding for understanding and promoting academic communication.

Traditional regression models typically estimate parameters for a factor F by designating one level as a reference (intercept) and calculating slopes for other levels of F. While this approach often aligns with our research question(s), it limits direct comparisons between all pairs of levels within F and requires additional procedures for generating these comparisons. Moreover, Frequentist methods often rely on corrections (e.g., Bonferroni or Tukey), which can reduce statistical power and inflate uncertainty by mechanically widening confidence intervals. This paper demonstrates how Bayesian hierarchical models provide a robust framework for parameter estimation in the context of multiple comparisons. By leveraging entire posterior distributions, these models produce estimates for all pairwise comparisons without requiring post hoc adjustments. The hierarchical structure, combined with the use of priors, naturally incorporates shrinkage, pulling extreme estimates toward the overall mean. This regularization improves the stability and reliability of estimates, particularly in the presence of sparse or noisy data, and leads to more conservative comparisons. Bayesian models also offer a flexible framework for addressing heteroscedasticity by directly modeling variance structures and incorporating them into the posterior distribution. The result is a coherent approach to exploring differences between levels of F, where parameter estimates reflect the full uncertainty of the data.

The construct of second language (L2) utterance fluency is typically operationalized through various individual temporal features. However, in natural speech, fluency (or disfluency) is often characterized by the clustering of multiple temporal features, collectively revealing the speaker’s effort in speech production or disfluency recovery. In this study, we explore the co-occurrence patterns of disfluency features in L2 speech and their associations with speakers’ L2 oral proficiency. We initially segmented all speech samples into analysis of speech (AS)-units. Within each AS-unit, six individual fluency features were manually coded, standardized, and subsequently subjected to a hierarchical-based k-means cluster analysis to examine their co-occurrence patterns. The results revealed four distinct disfluency clusters. A subsequent qualitative analysis of disfluencies in each cluster revealed distinct distributional patterns, disfluency makeup, and communicative functions. Additionally, the proportions of different disfluency clusters were significantly influenced by speakers’ proficiency level, first language background, and their interaction. These findings carry implications for L2 speaking research in general, shedding light on the intricate nature of speech fluency and presenting an alternative approach to the operationalization of this multidimensional construct.

Al-Hoorie et al. (2024: Studies in Second Language Acquisition, 1–23) illuminate a validation crisis within the second language (L2) Motivational Self System (L2MSS), revealing empirical flaws in its current measurement. Their analysis indicates a persistent lack of discriminant validity among the system’s constructs, issuing a fundamental challenge in distinguishing the concepts. These findings, echoing previous concerns, underscore a pressing need for theoretical refinement and methodological rigor within the field, leading the authors to advocate for a temporary halt in L2 self-studies to address these issues comprehensively. This commentary discusses the call for a substantive moratorium presented by Al-Hoorie et al. (2024: Studies in Second Language Acquisition, 1–23) as a necessary step toward resolving persistent challenges in the field. By highlighting historical issues and suggesting pathways for theoretical diversification and methodological advancement, I aim to foster a productive dialogue on motivational psychology in language learning while ensuring empirical robustness.

This paper responds to Al-Hoorie, Hiver, and In’nami’s (2024) critique of the second language (L2) Motivational Self System (L2MSS) by advocating for an immediate cessation of its use in the absence of substantial revision and validation. We revisit foundational studies in the tradition, exposing critical methodological flaws that we feel undermine empirical support for the model. Further, we examine systemic factors that contributed to the largely uncritical acceptance of the model. Drawing on our own experiences, we reflect on how these dynamics have obstructed the adoption of more robust motivational theories available in psychology and education. We further caution that without a stronger emphasis on validating measurement instruments, similar distractions may continue to hinder progress in the field.

This study focused on the relative contributions of cognitive aptitudes to the incidental learning and automatization of mini-language grammar. Over three sessions, participants (N = 45; first language [L1] Polish; age range: 19–35) completed computerized training in MiniItaliano as well as tasks tapping into working memory, general intelligence, and language analytic ability (LAA). The overt aim of the training was to comprehend messages placed in the context of an Italian supermarket; however, its actual goal was to acquire the target syntactic rules (i.e., subject-verb agreement, gender agreement, word order). The final session included a surprise post-test with untimed and timed grammaticality judgment tasks (GJTs) as measures of explicit and automatized knowledge, respectively. Results showed that performance on both tasks was predicted by LAA over and above other cognitive and control measures. Additionally, scores on the untimed GJTs were related to reliance on (self-discovered) rules, while timed GJTs involved general IQ.

The current study examined the comprehension and production of classifiers, case marking, and morphological passive structures among 414 child Japanese heritage speakers (mean age = 10.01 years; range = 4.02 – 18.18). Focusing on individual differences, we extracted latent experiential factors via the Q-BEx questionnaire (De Cat, Kašćelan, Prévost, Serratrice, Tuller, Unsworth, & The Q.-Be Consortium, 2022), which were then used to predict knowledge and use of these grammatical structures. The findings reveal that: (i) experiential factors such as heritage language (HL) engagement at home and within the community modulate grammatical performance differentially from childhood through adolescence, and (ii) HL proficiency, immersion experiences, and literacy systematically predict HL grammatical outcomes. These results indicate that particular language background factors hold differential significance at distinct developmental stages and that higher proficiency, richer immersion experiences, and literacy engagement in the HL are crucial for the development of core grammatical structures.

In the past decade, researchers have been increasingly interested in understanding the process of language learning, in addition to the effect of instructional interventions on L2 performance gains (i.e., learning products). One goal of such investigations is to reveal the interplay between learning conditions, processes, and outcomes where, for example, certain conditions can promote attention to the learning targets, which in turn facilitates learning. However, the statistical modeling approach taken often does not align with the conceptualization of the complex relationships between these variables. Thus, in this paper, we introduce mediation analysis to SLA research. We offer a step-by-step, contextualized tutorial on the practical application of mediation analysis in three different research scenarios, each addressing a different research design using either simulated or open-source datasets. Our overall goal is to promote the use of statistical techniques that are consistent with the theorization of language learning processes as mediators.

Al-Hoorie, Hiver, and In’nami (2024) offer compelling arguments for why L2 motivational self-system research is currently in a state of validation crisis. Seeking a constructive resolution to the crisis, in this response we argue that two fundamental conditions are needed for the field to emerge stronger: psychological readiness and methodological maturity. For psychological readiness, we call for a reframing of the “crisis” narrative. We highlight the need to value controversy, to normalize failure and (self-)correction, and to resist the allure of novelty. For methodological maturity, we suggest that an argument-based approach to validation can provide a constructive solution to current controversies. We present an integrated framework that can guide systematic validation efforts, and we demonstrate its application using a recent validation study as an example.

This study investigates how second language (L2) learners engage in prediction based on their processing goals. While prediction is a prominent feature of human sentence comprehension in first–language speakers, it remains less understood when and how L2 learners engage in predictive processing. By conducting a visual–world eye–tracking experiment involving Chinese–speaking L2 learners of Korean, we tested the hypothesis that L2 learners determine whether to engage in prediction by evaluating the costs and benefits of anticipatory processing. The experiment specifically focused on the impact of a top–down comprehension goal for L2 learners’ predictive use of an honorific form in Korean by providing them with different types of task instruction. Our results indicated that all groups engaged in predictive processing in early and entire predictive regions. However, in the late predictive region, L2 learners presented with a prediction–oriented task, but not those with a simple comprehension task, actively generated expectations about the honorific status of an upcoming referent. These findings lend support to the utility account of L2 prediction, suggesting that L2 learners’ engagement in prediction depends on their current goals and strategies for processing efficiency.

Various theories have been proposed in the field of second language (L2) sentence processing research and have significantly advanced our understanding of the mechanisms underlying L2 sentence interpretation processes. However, many existing theories have only been formulated verbally, and little progress has been made towards formal modelling. Formal modelling offers several advantages, including enhancing the clarity and verifiability of theoretical claims. This paper aims to address this gap in the literature by introducing formal computational modelling and demonstrating its application in L2 sentence processing research. Through practical demonstrations, the paper also emphasises the importance of formal modelling in the formulation and development of theory.

Skill acquisition theory conceptualizes second language (L2) learning in three stages (declarative, procedural, and automatic), yet competing theoretical models with fewer stages also exist, and the number of stages has never actually been tested. We tested the validity of the three-stage model by investigating the number and nature of learning stages in L2 skill acquisition. Seventy-three participants deliberately learned grammar and vocabulary of a miniature language through explicit-deductive instruction. They systematically practiced comprehending the language until their accuracy and speed of performance did not improve anymore. Participants received a battery of tests assessing individual differences in their declarative and procedural learning abilities. We first applied hidden Markov modeling to participants’ reaction time data (obtained from the language practice) to compare rival hypotheses on the number of stages in L2 skill acquisition. We then examined which cognitive variables predicted participants’ performances (accuracy and speed) in each stage. Our results indicated that participants indeed acquired L2 skills in three stages and that their performance correlated initially with declarative learning ability, but there was a tendency for procedural learning ability to take over in the later stages. Our findings provide the first formal evidence for the influential three-stage model of L2 skill acquisition.

A common way of acquiring multiword expressions is through language input, such as during reading and listening. However, this type of learning is slow. Identifying approaches that optimize learning from input, therefore, is an important language-learning endeavor. In the present study, 85 learners of English as a foreign language read short texts with 42 figurative English phrasal verbs, repeated three times. In a counterbalanced design, we manipulated access to definitions (before text, after text, no definition) and typographic enhancement (with bolding, without bolding). The learning was measured by immediate and delayed gap-fill and meaning generation posttests. All posttests showed that learning with definitions was better than without, and that access to definitions after reading was more beneficial than before reading. Typographic enhancement effectively promoted contextual learning of phrasal verbs and increased the learning advantage associated with presenting definitions after reading.

Al-Hoorie, Hiver, and In’nami (2024) challenged the validity and corresponding validation processes of L2 Motivational Self System (L2MSS) research. A component of this challenge included claims of weak discriminant validity due to high correlations among L2MSS constructs. Papi and Teimouri (2024) countered by using semi-partial correlations to control for other L2MSS constructs, finding weak-to-moderate associations, which they claimed mollified potential discriminant validity concerns. In this methods-oriented response paper, we present a historical case that semi-partial correlations should be viewed within the context of multiple regression analysis, not as a standalone bivariate metric. Challenging Papi and Teimouri’s approach, we suggest that their method does not adequately address discriminant validity issues. Furthermore, when their semi-partial correlations are treated as multiple regression models, Al-Hoorie et al.’s concerns remain valid. Finally, we demonstrate that L2MSS literature does not support the assignment of outcome and predictor variables in Papi and Teimouri’s semi-partial correlations when correctly considered as multiple regression models.

As the field of heritage language acquisition expands, there is a need for proficiency to compare speakers across groups and studies. Elicited imitation tasks (EITs) are efficient cost-effective tasks with a long tradition in proficiency assessment of second language (L2) learners, first language children, and adults. However, little research has investigated their use with heritage speakers (HSs), despite their oral nature, which makes them appropriate for speakers with variable literacy skills. This study is a partial replication of Solon, Park, Dehghan-Chaleshtori, Carver & Long (2022), who administered an EIT originally developed for advanced L2 learners on a group of HSs. In this study, we administered the same EIT with minor modifications to 70 HSs and 132 L2 learners of Spanish with different levels of proficiency and ran a Rasch analysis to evaluate the functioning of the task with the two groups. To obtain concurrent validity evidence, scores on the EIT were compared with participants’ performance in an oral narration; evaluated for complexity, accuracy, and fluency (CAF); and compared with a standardized oral proficiency test, the Versant Spanish Test. Results of Rasch analyses showed that the EIT was effective at distinguishing different levels of ability for both groups, and analyses showed moderate to strong correlations between CAF measures and the EIT and very strong correlations between the EIT and the Versant Spanish Test. These results provide evidence that the EIT is an efficient and adequate proficiency test for HSs and L2 learners of Spanish; its use in research settings is recommended.

This paper reports an expansion of the English as a second language (L2) component of the Multilingual Eye Movement Corpus (MECO L2), an international database of eye movements during text reading. While the previous Wave 1 of the MECO project (Kuperman et al., 2023) contained English as a L2 reading data from readers with 12 different first language (L1) backgrounds, the newly collected dataset adds eye-tracking data on English text reading from 13 distinct L1 backgrounds (N = 660) as well as participants’ scores on component skills of English proficiency and information about their demographics and language background and use. The paper reports reliability estimates, descriptive statistics, and correlational analyses as means to validate the expansion dataset. Consistent with prior literature and the MECO Wave 1, trends in the MECO Wave 2 data include a weak correlation between reading comprehension and oculomotor measures of reading fluency and a greater L1-L2 contrast in reading fluency than reading comprehension. Jointly with Wave 1, the MECO project includes English reading data from more than 1,200 readers representing a diversity of native writing systems (logographic, abjad, abugida, and alphabetic) and 19 distinct L1 backgrounds. We provide multiple pointers to new venues of how L2 reading researchers can mine this rich publicly available dataset.

In recent years, the L2 Motivational Self System has faced increasing scrutiny over its theoretical clarity and empirical rigor. One element of this model, the L2 Learning Experience, remains ambiguously defined and theoretically underdeveloped. This study examined the content validity of the L2 Learning Experience scale and its potential overlap with intrinsic motivation, a cornerstone of self-determination theory. Using a panel of experts, we assessed to what extent items traditionally associated with the L2 Learning Experience scale align with their intended construct. Findings revealed that the items were predominantly identified as intrinsic motivation, not the L2 Learning Experience. These results suggest a significant overlap between the two constructs and raise concerns about a potential jangle fallacy. Our results also underscore the need for greater theoretical and terminological clarity in the field. Aligning language learning motivation research with broader psychological frameworks could lead to more parsimonious and robust theoretical models.

This study is designed to understand embarrassment in the second/foreign language (L2) context. Following a mixed-method design, in Phase 1, a sample of 141 tertiary-level Austrian English language learners were asked to write a narrative about their experiences of embarrassment in their language learning histories. Analyzing the narratives showed that L2 embarrassment is a multidimensional construct that is frequently experienced by a range of language learners. In Phase 2, we developed and validated an L2 classroom speaking embarrassment (L2CSE) scale among a sample of 402 international English language learners drawing on the literature and analysis of the narratives. Data showed that L2 embarrassment is best represented by a bifactor exploratory structural equation model, capturing both general and specific aspects of L2 embarrassment. We found that a supportive classroom environment and fostering a growth mindset can decrease the risk of L2 embarrassment. As expected, L2 embarrassment was a negative predictor of willingness to communicate and self-perceived language proficiency. These initial findings suggest that L2 embarrassment could be an important and influential emotion in the language learning classroom context which requires further research.