Explore the vast range of titles available.

The increasing number of experimental studies on second language (L2) processing, frequently with English as the L2, calls for a practical and valid measure of English vocabulary knowledge and proficiency. In a large-scale study with Dutch and Korean speakers of L2 English, we tested whether LexTALE, a 5-min vocabulary test, is a valid predictor of English vocabulary knowledge and, possibly, even of general English proficiency. Furthermore, the validity of LexTALE was compared with that of self-ratings of proficiency, a measure frequently used by L2 researchers. The results showed the following in both speaker groups: (1) LexTALE was a good predictor of English vocabulary knowledge; 2) it also correlated substantially with a measure of general English proficiency; and 3) LexTALE was generally superior to self-ratings in its predictions. LexTALE, but not self-ratings, also correlated highly with previous experimental data on two word recognition paradigms. The test can be carried out on or downloaded from www.lextale.com .

Syntactic complexity is an important measure of second language (L2) writing proficiency. Large-grained indices such as the mean length of T-unit (MLTU) have been used with the most consistency in L2 writing studies. Recently, indices such as MLTU have been criticized, both for the difficulty in interpretation and for a potentially misplaced focus on clausal subordination. In this article, the authors attempt to address both of these criticisms by using traditional indices of syntactic complexity (e.g., MLTU), fine-grained indices of clausal complexity, and fine-grained indices of phrasal complexity to predict holistic scores of writing quality. In 4 studies, they used indices of each index type to predict holistic writing quality scores in independent essays on the Test of English as a Foreign Language (TOEFL). They then used all index types in a combined analysis to predict a holistic writing score. The results indicated that fine-grained indices of phrasal complexity were better predictors of writing quality than either traditional or fine-grained clausal indices, though a single fine-grained index of clausal complexity contributed to the combined model. These results provide some support for Biber et al.'s (2011) claims regarding complexity and academic L2 writing proficiency. (Verlag, adapt.).

We present DREAM, the first dialogue-based multiple-choice reading comprehension data set. Collected from English as a Foreign Language examinations designed by human experts to evaluate the comprehension level of Chinese learners of English, our data set contains 10,197 multiple-choice questions for 6,444 dialogues. In contrast to existing reading comprehension data sets, DREAM is the first to focus on in-depth multi-turn multi-party dialogue understanding. DREAM is likely to present significant challenges for existing reading comprehension systems: 84% of answers are non-extractive, 85% of questions require reasoning beyond a single sentence, and 34% of questions also involve commonsense knowledge. We apply several popular neural reading comprehension models that primarily exploit surface information within the text and find them to, at best, just barely outperform a rule-based approach. We next investigate the effects of incorporating dialogue structure and different kinds of general world knowledge into both rule-based and (neural and non-neural) machine learning-based reading comprehension models. Experimental results on the DREAM data set show the effectiveness of dialogue structure and general world knowledge. DREAM is available at .

The present study was an examination of the relationship of lexical richness to the quality of English as a second language (ESL) learners' oral narratives. A computational system was designed to automate the measurement of 3 dimensions of lexical richness, that is, lexical density, sophistication, and variation, using 25 different metrics proposed in the language acquisition literature. This system was used to analyze large-scale data from the Spoken English Corpus of Chinese Learners together with the vocd utility of the Computerized Language Analysis programs, which offers an additional measure of lexical variation, the D measure. This comprehensive analysis allowed us to identify measures that correlate strongly with the raters' judgments of the quality of ESL learners' oral narratives, as well as to understand the relationships among these measures. This research provides ESL teachers and researchers with a robust tool for assessing the lexical richness of ESL language samples and insights into how lexical richness measures may be effectively used as indices of the quality of ESL learners' speaking task performance. (Verlag, adapt.).

For Chinese learners of English as a foreign language (EFL), it is meaningful to identify the factors that suppress their motivation of EFL learning. For this purpose, a questionnaire survey was carried out among 265 Chinese EFL learners attending a Chinese-foreign cooperation program of Henan University, China. Then, the potential influencing factors were identified through a multi-factor analysis of variance, and the correlation between the students’ psychological demotivation intensity and their English test score was discussed through Pearson correlation test and regression analysis. The results show that teacher-related factor, self-related factor and institution-related factor are the main causes of psychological demotivation among Chinese EFL learners; the English test score has a significant negative correlation with psychological demotivation intensity; the freshmen and sophomores had an insignificant different in the institution-related factor. The research findings shed new light on the sustainable psychology development of Chinese EFL learners.

Comprehensibility, a major concept in second language (L2) pronunciation research that denotes listeners’ perceptions of how easily they understand L2 speech, is central to interlocutors’ communicative success in real-world contexts. Although comprehensibility has been modeled in several L2 oral proficiency scales—for example, the Test of English as a Foreign Language (TOEFL) or the International English Language Testing System (IELTS)—shortcomings of existing scales (e.g., vague descriptors) reflect limited empirical evidence as to which linguistic aspects influence listeners’ judgments of L2 comprehensibility at different ability levels. To address this gap, a mixed-methods approach was used in the present study to gain a deeper understanding of the linguistic aspects underlying listeners’ L2 comprehensibility ratings. First, speech samples of 40 native French learners of English were analyzed using 19 quantitative speech measures, including segmental, suprasegmental, fluency, lexical, grammatical, and discourse-level variables. These measures were then correlated with 60 native English listeners’ scalar judgments of the speakers’ comprehensibility. Next, three English as a second language (ESL) teachers provided introspective reports on the linguistic aspects of speech that they attended to when judging L2 comprehensibility. Following data triangulation, five speech measures were identified that clearly distinguished between L2 learners at different comprehensibility levels. Lexical richness and fluency measures differentiated between low-level learners; grammatical and discourse-level measures differentiated between high-level learners; and word stress errors discriminated between learners of all levels.

Automated evaluation systems (AESs) for spoken language assessment are increasingly adopted in global educational settings, yet their validity in non-Western contexts remains underexplored. This study addresses this gap by examining three widely used Chinese-developed AES tools in their assessment of spoken English proficiency among 30 Chinese undergraduates. The study employed an IELTS-adapted speaking test, assessed simultaneously by AESs and human raters, with scoring alignment analyzed through intra-class correlation coefficients, Pearson correlations, and linear regression. Results revealed that two systems demonstrated strong agreement with human ratings, while the third exhibited systematic score inflation, likely due to algorithmic discrepancies and limited consideration of nuanced language features. Our findings suggest the potential of AESs as valuable complements to traditional language assessment methods, while highlighting the necessity for calibration and validation procedures. This research has significant implications for integrating AESs in educational contexts, particularly in English as a Foreign Language (EFL) settings, where they can enhance efficiency and standardization.

The main purpose of the current study was to examine the relative significance of vocabulary knowledge (VK) and syntactic knowledge (SK) in second language (L2) listening ability, while accounting for the effect of several cognitive and affective factors. A total of 263 English-as-a-foreign-language learners took a standardized listening test (IELTS), as well as a battery of nine linguistic (two aural SK tests and two aural VK tests—covering both breadth and depth of VK), cognitive (two working memory tests and a metacognitive knowledge questionnaire), and affective measures (two L2 listening anxiety questionnaires). Structural equation modeling analysis revealed that both VK and SK were significant predictors of L2 listening ability; however, VK was a stronger predictor with an effect size being almost twice as much as the one for SK (.55 vs. .28). The results also showed that metacognitive knowledge, working memory, and L2 listening anxiety are significant predictors of L2 listening ability.

Considering the undeniable importance of examining the role of domain- and skill-specific individual difference factors in second-language (L2) writing research, this study examined the possible roles of English-as-a-foreign-language (EFL) learners’ ideal L2 writing self and growth L2 writing mindset in their L2 writing grit, which may in turn contribute to their L2 writing achievement (WA). Data were collected from 532 English-major students selected via convenience sampling by administering a questionnaire to measure their growth L2 writing mindset, ideal L2 writing self, and L2 writing grit. The International English-Language Testing System (IELTS) academic writing tasks 1 and 2 were used as measures of the learners’ L2 WA. The psychometric properties of the scales were investigated and verified through confirmatory factor analyses. Structural equation modeling (SEM) results revealed that ideal L2 writing self and L2 writing grit directly predicted L2 WA. Additionally, growth L2 writing mindset and ideal L2 writing self predicted L2 WA through the mediation of L2 writing grit. This study highlighted the importance of domain- and skill-specific individual difference factors in L2 WA and the vital necessity of considering them in L2 writing instruction.

In recent years, the boom in the field of positive psychology in second language acquisition research has seen an increasing number of scholars focusing on the individual well-being of second language learners alongside their learning effectiveness. Despite this growing interest, there is a need to further investigate the specific emotional factors influencing academic achievement in foreign language learning. This study investigates the impact of three emotions—enjoyment, boredom, and burnout—on academic achievement, and the moderating role of academic buoyancy. Data were collected from 563 college English-as-a-foreign-language (EFL) students from China’s mainland using latent moderated structural equation modeling with Mplus. The results of the latent bivariate correlation analysis showed significant correlations between EFL learning emotions, academic buoyancy, and test performance. In the latent moderated structural equations model, enjoyment and burnout predicted test performance. Moreover, academic buoyancy moderated the relationships between enjoyment and test performance, and between burnout and test performance. EFL test performance was highest when enjoyment and buoyancy were both high, or when burnout and buoyancy were both low. These findings highlight the importance of fostering positive emotions and resilience in language learners to enhance their academic performance, offering valuable insights for educators and policymakers aiming to improve foreign language education.