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ChatGPT and similar generative AI models are increasingly being integrated into educational practice, including second language (L2) writing. However, AI-generated writing may significantly differ from that of developing L2 writers, raising potential issues over academic integrity. With AI detectors still underused in many contexts due to accuracy concerns, it is essential to determine if and how AI-generated texts are similar or different to those of L2 writers. This study compares lexical and collocation choices between essays on the same topic generated by ChatGPT (version 3.5) and human L2 writers using corpus analytic techniques. R statistical software was used for analysis and comparison. Results suggest that when tasked with producing academic essays under the same topic, ChatGPT-3.5 excels in generating texts with formal and complex vocabulary suited for academic and technical themes, while human L2 writers tend to focus on personal and social issues, using more varied and context-rich vocabulary. Accordingly, educators seeking to detect AI use should recognise the distinct linguistic and cultural experiences L2 writers bring to their writing, while students using AI need to understand the nature of the machine-like clarity and directness of expression as produced by ChatGPT as compared with their own typical production. [ABSTRACT FROM AUTHOR]

The aim of this study was to test the possible impact of the form information in presented (reading vs. listening situation) on the comprehension of narrative texts in students with ADHD comorbid with dyslexia. An experimental group with a mean age of 8.5 years and a control group with a mean age of 8.9 years participated. Three measures were used to analyse comprehension: lexical diversity, cohesive resources and episodic structure. The results showed no significant differences in the control group on all the measures under study, but there were significant differences in some measures in the experimental group, so that the use of cohesive resources and lexical diversity were favoured by the reading situation. Measures of episodic structure were not significantly affected by presentation modality. [ABSTRACT FROM AUTHOR]

Copyright of International Journal on Humanities & Social Sciences is the property of International Journal on Humanities & Social Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper focuses on vocabulary development in oral language productions of three elementary school-age sibling pairs growing up in a trilingual setting. This longitudinal study describes the development of the children's narrative competence over three years. The corpus analysed consists of retellings of animated films. The contribution deals with the lexical development in the three languages of the children, in particular the length of the productions, lexical diversity and lexical sophistication. Lexical diversity is measured by the Guiraud Index. It is assumed that the children's vocabulary becomes more diverse with increasing age. Lexical sophistication is examined by measuring the average frequency of words used by the participants. It is assumed that as children's vocabularies grow, they will include more and more 'rare' low-frequency words in their productions. Assuming that the school language is the dominant language, the question is whether lexical diversity and sophistication increase with age in all three of the children's languages, or whether this is only the case in the school language. The results show that lexical development varies from child to child. However, a certain trend can be observed, indicating that school vocabulary is becoming more sophisticated. [ABSTRACT FROM AUTHOR]

This article uses the vocabulary measurement indicators of lexical diversity, lexical sophistication, lexical density, and lexical accuracy for second-language writing levels to systematically measure the lexical richness of essays written by Chinese as a second language (CSL) learners. It employs the methodology of building a corpus based on the collected compositions for data analysis. It shows that the Uber index of lexical diversity and the lexical density of CSL learners does not always show a positive correlation with increased test scores. Lexical sophistication usually positively correlates with test scores, but the growth trend tends to be flat from the 81–90 score range. Lexical accuracy below 80 points is positively correlated with writing scores; however, the data above 91 points is slightly lower than that of 81–90 points. This article further hypothesizes that the above measurement indicators fail to accurately measure CSL students' Chinese lexical ability because those indicators do not include the sememe factors of Chinese words and thus rely too much on word form. This article further puts forward the specific manifestations (polysemes, homographs, and multi-category words) of sememe richness and proposes specific solutions to add sememe richness to the four original formulas through the use of the four above-mentioned measurement indicators in CSL. [ABSTRACT FROM AUTHOR]

A wide range of tools have been used to assess the language proficiency of bilingual speakers. The validity and high reliability of lexical diversity and syntactic complexity measures as instruments for measuring language proficiency have been demonstrated in previous studies across different languages. However, the relationship between self-assessment and the two measures has not yet been investigated. The present study focused on the Italophone bilingual language speakers, an understudied minority diglossic community in Croatia, and investigated whether measures of lexical diversity and syntactic complexity reflect self-assessment of language proficiency in the standard Italian language and the Istrovenetian dialect overall and in four specific domains (reading, writing, speaking, and listening). In addition, we aimed to investigate whether there are possible differences in self-assessment between the standard Italian language and the Istrovenetian dialect and whether there are language varietyrelated differences (standard vs. dialect) in the relationship between selfassessment and measures of lexical diversity and syntactic complexity. The results showed an intricate interplay between self-assessment and the lexical diversity and syntactic complexity of bilingual speech. This suggests that these measures are interrelated and that heritage bilingual language speakers may be able to objectively assess their language proficiency. [ABSTRACT FROM AUTHOR]

The impact of text length on the estimation of lexical diversity has captured the attention of the scientific community for more than a century. Numerous indices have been proposed, and many studies have been conducted to evaluate them, but the problem remains. This methodological review provides a critical analysis not only of the most commonly used indices in language learning studies, but also of the length problem itself, as well as of the methodology for evaluating the proposed solutions. Analysis of three data sets of texts produced by English language learners revealed that indices that reduce all texts to the same length using a probabilistic or an algorithmic approach solve the length‐dependency problem; however, all these indices failed to address the second problem, which is their sensitivity to the parameter that determines the length to which the texts are reduced. The paper concludes with recommendations for optimizing lexical diversity analysis. A one‐page Accessible Summary of this article in nontechnical language is freely available in the Supporting Information online and at https://oasis‐database.org [ABSTRACT FROM AUTHOR]

This study explores the feasibility of cross-linguistic authorship attribution and the author's gender identification using Machine Translation (MT). Computational stylistics experiments were conducted on a Greek blog corpus translated into English using Google's Neural MT. A Random Forest algorithm was employed for authorship and gender profiling, using different feature groups [Author's Multilevel N-gram Profiles, quantitative linguistics (QL), and cross-lingual word embeddings (CLWE)] in both original and translated texts. Results indicate that MT is a viable method for converting a multilingual corpus into one language for authorship attribution and gender profiling research, with considerable accuracy when training and testing datasets use identical language. In the pure cross-linguistic scenario, higher accuracies than the baselines were obtained using CLWE and QL features. [ABSTRACT FROM AUTHOR]

This paper reports on a quasi-experimental study designed to explore the relationship between lexical diversity and academic vocabulary use among Indonesian EFL university students engaging in online academic writing discussions and assignments. The study analysed 11,624 tokens and 5437 types collected from students' contributions in online discussions and academic writing assignments. Findings revealed that the level of lexical diversity among the students was significantly varied depending on the text length and the total amount of data. It was found most students were indicated to possess average ESL level of academic writing with a D value ranging from 50 to 70 while some others indicated a high level of adult ESL with developed academic text in the range between 70 and 80 D level. Moreover, it was also found that the degree of lexical diversity was not affected by the writing topic familiarity or students' academic year. Findings revealed a statistically significant negative correlation between measures of lexical diversity and academic vocabulary use. Contrary to expectations, while a diversified vocabulary generally correlates positively with student writing performance, this relationship reverses in contexts emphasizing the academic quality of writing. These results highlight the complex dynamics of lexical usage in academic writing and suggest that mere lexical diversity does not always equate to higher academic writing quality. This study contributes to a critical understanding of how lexical diversity functions in digital academic environments and offers implications for English language teaching practices in higher education settings.

The introduction of Artificial Intelligence (AI) generative language models such as GPT (Generative Pre-trained Transformer) and conversational tools such as ChatGPT has triggered a revolution that can transform how text is generated. This has many implications, for example, as AI-generated text becomes a significant fraction of the text, would this affect the language capabilities of readers and also the training of newer AI tools? Would it affect the evolution of languages? Focusing on one specific aspect of the language: words; will the use of tools such as ChatGPT increase or reduce the vocabulary used or the lexical diversity? This has implications for words, as those not included in AI-generated content will tend to be less and less popular and may eventually be lost. In this work, we perform an initial comparison of the vocabulary and lexical diversity of ChatGPT and humans when performing the same tasks. In more detail, two datasets containing the answers to different types of questions answered by ChatGPT and humans, and a third dataset in which ChatGPT paraphrases sentences and questions are used. The analysis shows that ChatGPT-3.5 tends to use fewer distinct words and lower diversity than humans while ChatGPT-4 has a similar lexical diversity as humans and in some cases even larger. These results are very preliminary and additional datasets and ChatGPT configurations have to be evaluated to extract more general conclusions. Therefore, further research is needed to understand how the use of ChatGPT and more broadly generative AI tools will affect the vocabulary and lexical diversity in different types of text and languages.

Discourse abnormalities are a prominent feature in schizophrenia spectrum disorders, including poor lexical diversity, and have been found to differentiate patients from healthy subjects. However, discourse processing in individuals with high schizotypal personality traits is less understood and is often overshadowed by research on clinical psychotic symptoms. In the present study, we examined schizotypal traits at a non-clinical threshold and their association with lexical diversity and discourse coherence using two automated Natural Language Processing (NLP) tools - Type-Token-Ratio (TTR) measures from the Tool for the Automatic Analysis of Lexical Diversity (TAALED) and discourse coherence using sentence-level average cosign similarity with FastText to assess sentence similarity. 276 college students completed the full assessment including the Schizotypal Personality Questionnaire- Brief Revised (SPQ-BR) and recorded a speech sample describing a detailed painting. Results revealed that high schizotypal traits, specifically positive traits, were associated with lower lexical diversity and higher sentence similarity. Our findings suggest that even when clinically significant symptoms are not present, discourse abnormalities are present in healthy populations with high ST. The stronger association with positive traits suggests that theories of perseveration and top-down processing may warrant further investigation in schizophrenia-spectrum disorders. [ABSTRACT FROM AUTHOR]

In EFL countries where English is rarely practiced outside the classroom, textbooks have become the major input source for learners. Particularly in Vietnam, multiple textbook series are available simultaneously for the same grade. Thus, it is important to examine if their vocabulary is appropriate and of similar difficulty. This study aims to investigate and compare the lexical demands, sophistication, diversity, and lengths of reading passages in the eight latest series for Vietnamese 10th graders with 53,360 tokens in total. The results revealed that the most frequent 1,000, 2,000-3,000, and roughly 4,000-word families in the BNC/COCA wordlist, plus proper nouns, marginal words, transparent compounds, and acronyms, were respectively needed for 85%, 95%, and 98% coverage. Additionally, pairwise comparisons uncovered that the passages differ significantly in length yet insignificantly in lexical sophistication and diversity. Therefore, the series appear to be well-suited to coimplementation and facilitative to vocabulary development despite not being optimized for independent learning. The study still calls for simplifying the eight textbook series to promote meaning-focused output. Finally, implications for exploiting and revising these textbook series are discussed. [ABSTRACT FROM AUTHOR]

The main objective of this study is to investigate how interactive factors affect the vocabulary usage of second language learners in their spoken language. Participants were 24 L1 Chinese undergraduate students of L2 English at an advanced level. L2 learners' vocabulary use was assessed via tokens, lexical diversity, and frequency-based lexical sophistication. Participants provided speech data in response to seven persuasive speaking tasks across three speaking modes: two monologic, two dialogic, and three trialogic. This study showed that the interactive factor has a varied effect on L2 learners' vocabulary usage. It positively influences the use of advanced vocabulary but does not affect the total number of words produced or the diversity of words used. Second, of all three speaking modes, the dialogic speaking mode is the best speaking condition to trigger L2 learners' use of advanced words. Third, the vocabulary employed in dialogues and trialogues can vary due to the inherent disparities between the two modes of speech. Therefore, we propose the use of the dialogic interactive factor and trialogic interactive factor instead of the term "interactive factor" to encompass two specific conditions in which there was a noticeable difference in the performance of L2 learners. [ABSTRACT FROM AUTHOR]

We examined the potential influence of L1–L2 lexical similarity on L2 lexical diversity, to determine whether the robust facilitative effect of lexical similarity that is found in processing and broad learning outcomes extends to this measure of L2 production. Our sample included two matching learner sub-corpora, containing 8,500 and 6,390 English texts, written in response to ninety-five and seventy-one writing tasks, by speakers of nine typologically diverse L1s, in the A1–B2 cefr range of L2 English proficiency. We found that lexical similarity did not influence L2 lexical diversity at any proficiency level. This finding suggests that the facilitative effect of similarity does not necessarily extend to L2 production, at least in the case of certain global measures, like lexical diversity, and certain task-based settings, like the present educational one, where lexical choices are driven primarily by the constrained communicative needs of the tasks. This is supported by the strong task effects that we found, which we quantified using mixed-effects models, whilst also shedding light on the use of lexical diversity as an indicator of L2 proficiency. [ABSTRACT FROM AUTHOR]

Sentence Repetition Tasks (SRTs) have been convincingly established as a reliable tool for assessing child language development. However, there are important aspects of this task that deserve more attention. For example, few studies have explored their potential role for identifying language disorders in children under 4 years of age, as almost all evidence refers to children above this age. There is also scarce evidence regarding the relationship between the results of these tasks andmeasures of spontaneous language. To address this gap, we conducted a study with 24 Typically Developing (TD) monolingual Spanish speakers aged between 30 and 36 months. They performed a Spanish Sentence Repetition Task (SSRT), and their language was recorded and analyzed during spontaneous play with their parents. Variables such as Mean Length of Utterance (MLU), an index of lexical diversity (ILD) and the structure of the Noun Phrase were considered. The statistical analyses reflect a positive and significant correlation between the results obtained in the SSRT and both the MLU and Noun Phrase structure. A positive and significant relationship is also obtained between the MLU in repetition and theMLU of spontaneous language. However, no significant correlation is found between the ILD with either the SSRT or the other measures of spontaneous language. Based on these results, we interpret that the SSRT effectively mirrors the language development of children measured through spontaneous production and is suitable for assessing language skills of Spanish children under 4 years old. [ABSTRACT FROM AUTHOR]

Bullet‐screen comments (BSCs), a type of novel user‐generated content for online videos, have been rapidly adopted in recent years. Previous research has focused on consumers' responses to the presence and quantity of BSCs but overlooked their contents. We examine how one characteristic feature of BSCs' content—lexical diversity—affects users' payments. A large‐scale real‐world behavioral data set analysis and three lab studies show that high (vs. low) lexical diversity of BSCs increases viewers' payments in online video streaming contexts (e.g., online videos and live streaming). We further reveal that the positive effect of BSC diversity on payment is mediated by perceived social presence and information richness. We also demonstrate the moderating role of viewers' BSC usage level (heavy vs. light), such that the effect of BSC diversity on payment is significant for heavy BSC users, but diminishes for light users. [ABSTRACT FROM AUTHOR]

Copyright of Croatica et Slavica Iadertina is the property of University of Zadar, Department of Croatian & Slavic Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This mixed-methods study aims to investigate the impact of traditional and digital storytelling (DST) on English as a foreign language (EFL) learners' writing performance in terms of complexity, accuracy, lexical diversity, and fluency (CALF) measures. Moreover, the study sheds light on how learners were engaged along behavioral, cognitive, affective, and agentive dimensions when completing the DST task. The participants were 45 intermediate-level college students who were assigned to the DST and traditional storytelling (TST) groups. Under a four-week curriculum, the participants constructed their stories by using either an online platform or traditional pen-and-paper format. Adopting a quasi-experiment design, within-group and between-group comparisons were made. A series of paired samples t-tests were run to compare the pretest and post-test of each group (within-group comparison) and assessed any improvement from the pretest to the post-test across CALF measures. Also, a 2 × 2 mixed-methods analysis of variance (ANOVA) was run on the post-test scores of the two groups across CALF measures (between-group comparisons). The results of these tests unveiled that the storytelling task, in either traditional or digital mode, effectively enhanced students' overall writing performance. However, there was a significant impact of DST on syntactic complexity, accuracy, and lexical diversity, while writing fluency remained unaffected. Moreover, the results of the questionnaire and interview data revealed the students' multidimensional engagement (behavioral, cognitive, affective, and agentive) while performing the DST task, with the agentive aspect emerging as most prominent. Pedagogical implications of incorporating DST in EFL contexts were discussed.

Child-directed print corpora enable systematic psycholinguistic investigations, but this research infrastructure is not available in many understudied languages. Moreover, researchers of understudied languages are dependent on manual tagging because precise automatized parsers are not yet available. One plausible way forward is to limit the intensive work to a small-sized corpus. However, with little systematic enquiry about approaches to corpus construction, it is unclear how robust a small corpus can be made. The current study examines the potential of a non-sequential sampling protocol for small corpus development (NSP-SCD) through a cross-corpora and within-corpus analysis. A corpus comprising 17,584 words was developed by applying the protocol to a larger corpus of 150,595 words from children's books for 3-to-10-year-olds. While the larger corpus will by definition have more instances of unique words and unique orthographic units, still, the selectively sampled small corpus approximated the larger corpus for lexical and orthographic diversity and was equivalent for orthographic representation and word length. Psycholinguistic complexity increased by book level and varied by parts of speech. Finally, in a robustness check of lexical diversity, the non-sequentially sampled small corpus was more efficient compared to a same-sized corpus constructed by simply using all sentences from a few books (402 books vs. seven books). If a small corpus must be used then non-sequential sampling from books stratified by book level makes the corpus statistics better approximate what is found in larger corpora. Overall, the protocol shows promise as a tool to advance the science of child language acquisition in understudied languages. [ABSTRACT FROM AUTHOR]

Research on first language (L1) attrition typically focuses on immigrant populations in their second language (L2) environment, yet we know comparably little about L1 attrition in the L1 setting. This study used two lexical tasks to test L1 attrition, a time-sensitive word decision task and a video retelling. Chinese teachers of English vs. Chinese teachers of other subjects (N = 25/group) were recruited at a secondary school in China. The aim was to provide an exploratory basis of the L2 influence on L1 lexical attrition in the L1 environment, both on the level of lexical comprehension and production. Mixed-effects models were used to analyse multiple measures including response accuracy and reaction times in comprehension, and lexical diversity, density, sophistication, and accuracy in production. The results showed Chinese teachers’ L1 lexical attrition in the form of longer response times to high-frequency Chinese words compared to non-English Chinese teachers, and the use of significantly fewer sophisticated words in their retellings. Also, teachers of English were faster and more accurate in decisions about Chinese borrowings from English, suggesting L2-driven influence on their mental lexicon. Considering participants’ background information, analyses showed that increased L2 exposure and frequency of use can predict L1 lexical attrition. [ABSTRACT FROM AUTHOR]

The present study examined the difference between L1 and L2 lexical diversity of argumentative and narrative writings of L2 learners, and the contribution of syntactic complexity and lexical diversity to the writing quality in the L2 argumentative and narrative writings of EFL learners. To this end, 46 pre-intermediate and intermediate Iranian EFL learners from four intact classes wrote one argumentative and one narrative essay in L2, and one argumentative and one narrative essay in L1 on different topics. Paired-samples t-tests revealed that lexical diversity surfaced more in the L1 writing of the learners. Multiple linear regressions indicated that among five measures of syntactic complexity, mean length of T-unit and clauses per T-unit better predict the quality of argumentative writing. In addition, complex nominals per clause are better predictors of narrative writing quality. Simple linear regressions showed that lexical diversity is a significant predictor of L2 writing in both genres. Based on the findings, writing instructors are advised to provide L2 learners with explicit instruction on the use of diverse vocabulary and different syntactic structures in order to help them improve the quality of their writing. [ABSTRACT FROM AUTHOR]

Successful spoken discourse requires a speaker to be informative to deliver a coherent, meaningful message. The informativeness of discourse can be conveyed by the variety of vocabulary produced (i.e., lexical diversity [LD]), the typicality of vocabulary items used (i.e., core lexicon [CL]), and the amount of relevant content produced (i.e., information units). Yet, it is well documented that older adults produce less informative content compared to younger adults despite relatively subtle changes to LD. The typicality of core lexical items has not been assessed in healthy aging. Paradoxically, these results indicate that some aspects of discourse informativeness remain stable or even improve across the adult lifespan, while other aspects decline. The purpose of the current study is to understand how microlinguistic processes of informativeness change across the adult lifespan. The cross‐sectional study included narrative language samples from two wordless picture books collected from 420 healthy participants between 20 and 89 years old. LD and percent of correct information units (%CIUs) were analyzed, as well as CL nouns and verbs. The results indicate that %CIUs and CL nouns demonstrate a quadratic decline starting around the ages of 40 and 60, respectively. LD shows a slight linear decline as a function of age. CL verbs are resistant to age‐related changes but are influenced greater by education. The differing findings across the microlinguistic measures can be explained by the weakened connections within the language system and the differential characteristics of the measures. The findings contribute to the aging literature by systematically identifying the trajectory of how variables of informativeness change with age. [ABSTRACT FROM AUTHOR]

Lexical complexity has been a key consideration of teaching preparation in determining grade appropriateness of teaching materials. However, the lack of quantified and defined standards for benchmarking lexical complexity has made it difficult for teachers when adapting source texts to target learners. This study has assessed quantitative differences in lexical complexity of exemplar texts at different points of schooling using a range of lexical diversity and sophistication features. The data consists of 2,372 texts from popular curriculum packages adopted from 1 to 12 grades of the English curriculum in China. One-way ANOVAs revealed significant differences in 16 out of 17 lexical complexity indices among different grades. Subsequent post hoc tests identified three lexical diversity features and four sophistication features that helped to differentiate exemplar texts across these 12 grades. These findings on the nature and role of lexical complexity have yielded new insights into the establishment of grade-level benchmarks for material preparation. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Language Academy is the property of Rota Kariyer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this era of information and communication technology, a large population relies on the Internet to gather information. One of the most popular information sources on the Internet is Wikipedia. Wikipedia is a free encyclopedia that provides a wide range of information to its users. However, there have been concerns about the readability of information on Wikipedia time and again. The readability of the text is defined as the ease of understanding the underlying text. Past studies have analyzed the readability of Wikipedia articles with the help of conventional readability metrics, such as the Flesch-Kincaid readability score and the Automatic Readability Index (ARI). Such metrics only consider the surface-level parameters, such as the number of words, sentences, and paragraphs in the text, to quantify the readability. However, the readability of the text must also take into account the quality of the text. In this study, we consider many new NLP-based parameters capturing the quality of the text, such as lexical diversity, semantic diversity, lexical complexity, and semantic complexity and analyze their impact on the readability of Wikipedia articles using artificial neural networks. Besides NLP parameters, the crowdsourced parameters also affect the readability, and therefore, we also analyze the impact of crowdsourced parameters and observe that the crowdsourced parameters not only influence the readability scores but also affect the NLP parameters of the text. Additionally, we investigate the mediating effect of NLP parameters that connect the crowdsourced parameters to the readability of the text. The results show that the impact of crowdsourced parameters on readability is partially due to the profound effect of NLP-based parameters. [ABSTRACT FROM AUTHOR]

A wide range of tools have been used to assess the language proficiency of bilingual speakers. The validity and high reliability of lexical diversity and syntactic complexity measures as instruments for measuring language proficiency have been demonstrated in previous studies across different languages. However, the relationship between self-assessment and the two measures has not yet been investigated. The present study focused on the Italophone bilingual language speakers, an understudied minority diglossic community in Croatia, and investigated whether measures of lexical diversity and syntactic complexity reflect self-assessment of language proficiency in the standard Italian language and the Istrovenetian dialect overall and in four specific domains (reading, writing, speaking, and listening). In addition, we aimed to investigate whether there are possible differences in self-assessment between the standard Italian language and the Istrovenetian dialect and whether there are language variety-related differences (standard vs. dialect) in the relationship between self-assessment and measures of lexical diversity and syntactic complexity. The results showed an intricate interplay between self-assessment and the lexical diversity and syntactic complexity of bilingual speech. This suggests that these measures are interrelated and that heritage bilingual language speakers may be able to objectively assess their language proficiency.

Substantial literature suggests that reading to children is positively associated with language outcomes, but the causal pathways are less well understood. One possibility is that reading to children promotes language input that is particularly useful for some aspects of language learning. To better understand the language that is produced during picture book reading, we built a sharable corpus of caregiver-child interactions during book reading recorded in homes. Caregivers overwhelmingly read the book text. However, books varied in the language they generated, with some books promoting more conversational turns and extra-textual language, while others promoted more overall words, unique words, and longer utterances. Relative to other conversational contexts, books generally generated overall more words, more lexically diverse talk, and longer utterances. We see different profiles of language generated during book reading that are all plausibly linked with language skills. If a causal pathway exists between shared book reading and language outcomes, a sensible candidate may be that reading provides a varied range of linguistic experiences.

The present paper reports on a study that examined the contribution of lexical frequency to lexical diversity in narrative texts composed by 119 multilingual and monolingual English-speaking students enrolled in first-year college writing courses. The Measure of Textual Lexical Diversity (MTLD) quantifed lexical diversity and the BNC-COCA 25 strand in Lextutor’s VocabProfle Compleat sorted the words according to frequency band. Overall, results from statistical analyses indicated that sample’s lexical diversity was not significantly impacted by the use of high-frequency (1,000-3,000 bands) or low-frequency (9,000+ bands) terms. Instead, texts showed greater differences in the mid-frequency (3,000-9,000) bands (p

Sentence Repetition Tasks (SRTs) have been convincingly established as a reliable tool for assessing child language development. However, there are important aspects of this task that deserve more attention. For example, few studies have explored their potential role for identifying language disorders in children under 4 years of age, as almost all evidence refers to children above this age. There is also scarce evidence regarding the relationship between the results of these tasks and measures of spontaneous language. To address this gap, we conducted a study with 24 Typically Developing (TD) monolingual Spanish speakers aged between 30 and 36 months. They performed a Spanish Sentence Repetition Task (SSRT), and their language was recorded and analyzed during spontaneous play with their parents. Variables such as Mean Length of Utterance (MLU), an index of lexical diversity (ILD) and the structure of the Noun Phrase were considered. The statistical analyses reflect a positive and significant correlation between the results obtained in the SSRT and both the MLU and Noun Phrase structure. A positive and significant relationship is also obtained between the MLU in repetition and the MLU of spontaneous language. However, no significant correlation is found between the ILD with either the SSRT or the other measures of spontaneous language. Based on these results, we interpret that the SSRT effectively mirrors the language development of children measured through spontaneous production and is suitable for assessing language skills of Spanish children under 4 years old.

Early linguistic environment has shown an impact on children's later language development, particularly, child directed speech has been associated with providing children with linguistic input from which to look for regularities and patterns, and boosting children to produce utterances beyond their current competence. This article aims to examine linguistic and interactive features of the speech addressed to Argentinean toddlers (mean age 19.9 month) living under different socioeconomic circumstances. We focused on the lexical diversity (VOCD) and syntactic complexity (MLU) that characterize utterances that fulfil different pragmatic functions (comments, requests for verbal and non-verbal response) addressed to children living under vulnerated and non-vulnerated socioeconomic circumstances. Results showed differences regarding lexical diversity between groups of households for requests for non-verbal response, while regarding syntactic complexity differences between groups were found in both requests for non-verbal response and for verbal response. [ABSTRACT FROM AUTHOR]

For proper assessment, diagnosis, and treatment of language disorders in Mandarin children, it is important to have measures that closely track the course of normal development. The current study uses a large collection of spontaneous conversational language samples to track the developmental course of five language measures: mean length of utterance (MLU), the MLU of the five longest utterances (MLU5), vocD, number of repetitions, and number of retracings. We used cross-validation-based linear regression to estimate the relationship between age, gender and each of the five variables derived from the conversational language samples in 101 typically developing Mandarin-speaking children aged 3 to 7. Each of the five measures showed significant age-related effects during the period from age 3 to age 7. As norm-referenced measures of language development in children speaking Mandarin, these developmental data could inform clinical therapists regarding assessments and interventions for children with language disorder or impairment. [ABSTRACT FROM AUTHOR]

The main objective of this study is to investigate how interactive factors affect the vocabulary usage of second language learners in their spoken language. Participants were 24 L1 Chinese undergraduate students of L2 English at an advanced level. L2 learners’ vocabulary use was assessed via tokens, lexical diversity, and frequency-based lexical sophistication. Participants provided speech data in response to seven persuasive speaking tasks across three speaking modes: two monologic, two dialogic, and three trialogic. This study showed that the interactive factor has a varied effect on L2 learners’ vocabulary usage. It positively influences the use of advanced vocabulary but does not affect the total number of words produced or the diversity of words used. Second, of all three speaking modes, the dialogic speaking mode is the best speaking condition to trigger L2 learners’ use of advanced words. Third, the vocabulary employed in dialogues and trialogues can vary due to the inherent disparities between the two modes of speech. Therefore, we propose the use of the dialogic interactive factor and trialogic interactive factor instead of the term “interactive factor” to encompass two specific conditions in which there was a noticeable difference in the performance of L2 learners.

Simultaneous interpreting (SI) is a cognitively demanding task that imposes a heavy cognitive load on interpreters. Interpreting into one's native (A language) or non-native language (B language), known as interpreting directionality, involves different cognitive demands. The cognitive requirements of simultaneous interpreting as well as interpreting directionality affect the interpreting process and product. This current study focused on the lexical features of a specially designed corpus of United Nations Security Council speeches. The corpus included non-interpreted speeches in US English (SubCorpusE), and texts interpreted from Chinese into English (A-into-B interpreted texts, SubCorpusC-E) and from Russian into English (B-into-A interpreted texts, SubCorpusR-E). Ten measures were used to analyze the lexical features of each subcorpus in terms of lexical density, lexical diversity, and lexical sophistication. The three subcorpora were regrouped into two pairs for the two research questions: SubCorpusR-E versus SubCorpusE and SubCorpusR-E versus SubCorpusC-E. The results showed that the interpreted texts in SubCorpusR-E exhibited simpler vocabulary features than the non-interpreted texts in SubCorpusE. In addition, compared with the A-into-B interpreted texts, the B-into-A interpreted texts demonstrated simplified lexical characteristics. The lexical features of the interpreted texts reflect that experienced simultaneous interpreters consciously adopt a simplified vocabulary approach to manage the cognitive load during simultaneous interpreting. This study provides new insights into the cognitive aspects of simultaneous interpreting, the impact of directionality, and the role of lexical strategies. These findings have practical implications for interpreter training, professional growth, and maintaining interpreting quality in diverse settings. [ABSTRACT FROM AUTHOR]

There is an established research agenda on dissecting an article's components and their association with a journal's prestige. However, journals' titles and their overview, aim and scope (i.e. journal's mission statement – JMS(s)) have not been investigated with the same diligence. This study aims to conduct a comprehensive outlook of titles and JMSs' lexical structure and identify significant differences between journals prestige and type of access and their JMS content in the field of business, management and accounting (BMA), considering the field's experience in developing and applying mission statements. Titles and JMSs' structural analysis reflected current and critical discussion in BMA: a predilection for counterintuitive findings and information and communication technology (ICT) tools. JMSs expressed primarily target customers and markets. JMSs from reputable journals showed a higher betweenness for key-terms related to rigorous features. In contrast, JMSs of lower reputable journals highlighted indexing attributes. The Wilcoxon rank-sum and the Kruskal–Wallis tests showed significant differences in the JMSs' median diversity regarding the journal's type of access and best quartiles. [ABSTRACT FROM AUTHOR]

Readability is the measure of how easier a piece of text is. Readability assessment plays a crucial role in facilitating content writers and proofreaders to receive guidance about how easy or difficult a piece of text is. In literature, classical readability, lexical measures, and deep learning based model have been proposed to assess the text readability. However, readability assessment using machine and deep learning is a data-intensive task, which requires a reasonable-sized dataset for accurate assessment. While several datasets, readability indices (RI) and assessment models have been proposed for military agencies manuals, health documents, and early educational materials, studies related to the readability assessment of computer science literature are limited. To address this gap, we have contributed Computer science (CS) literature dataset AGREE, comprising 42,850 learning resources(LR). We assessed the readability of learning objects(LOs) pertaining to domains of Computer Science (CS), machine learning (ML), software engineering (SE), and natural language processing (NLP). LOs consists of research papers, lecture notes and Wikipedia content of topics list of learning repositories for CS, NLP, SE and ML in English Language. From the statistically significant sample of LOs two annotators manually annotated LO’s text difficulty and established gold standard. Text readability was computed using 14 readability Indices (RI) and 12 lexical measures (LM). RI were ensembled, and readability measures were used to train the model for readability assessment. The results indicate that the extra tree classifier performs well on the AGREE dataset, exhibiting high accuracy, F1 score, and efficiency. We observed that there is no consensus among readability measures for shorter texts, but as the length of the text increases, the accuracy improves. The AGREE and SELRD datasets, along with the associated readability measures, provide a novel contribution to the field. They can be used to train deep learning models for readability assessment, develop recommender systems, and assist in curriculum planning within the domain of Computer Science. In the future, we plan to scale AGREE by adding more LOs and adding multimedia LOs. In addition, we would explore the use of deep learning methods for improved readability assessment.

Language is the primary means of human communication in which the addresser uses a given linguistic sign to arouse a specific set of meaning(s) in the addressee. The term meaning is used here to refer to the images, interpretations and feelings or signification aroused by a particular sign or lexical item. In other words, communication takes place when there is a correspondence of meaning/ signification between the communicator and the receiver. Lexical diversity is a significant aspect of Urdu news media. It occurs due to the fact that the news editors, belonging to diverse news agencies, choose from diverse lexical resources at their disposal to convey the same message in their own style and as per their own needs. However, it needs to be considered that the linguistic signs/ words are not just useless or insignificant entities that are used haphazardly and randomly. They have a certain role and signification and are used with certain intent by the news editors while framing the news items. It is clear that meaning of these signs/lexical items depends upon a host of factors including their collocation, socio-cultural setting and context of use. As such, these language symbols are selected and utilized very consciously and systematically by the news editors and, in doing so, they chose and exploit the lexical items in a planned manner to convey the intended message to the audience. Given this backdrop, the present paper aims to undertake a psycho-semiotic analysis of Urdu news media to throw light on the selective use of lexical items by the news editors according to their background, purpose, and intention.

Straightforward linguistic measures may be indicators of reduced language production and lexical diversity among individuals with schizophrenia with negative symptoms and neurocognitive impairments. We compared 98 patients with schizophrenia to 101 unaffected controls on six language variables (e.g. , number of relationships between objects, use of complex transitions in the narrative structure), number of words produced, and lexical diversity computed as the moving average type-token ratio from both speaking and writing tasks. Patients differed from controls on nearly all of the linguistic measures; number of words produced had the strongest effect, with an average Cohen's d of 0.68; values pertaining to lexical diversity were 0.50 and 0.32, respectively, for the speaking tasks and the writing tasks. Most measures were correlated with alogia and other domains of negative symptoms (including avolition-apathy and anhedonia-asociality), as well as with diverse neurocognitive domains, especially those pertaining to working memory, verbal learning, and verbal category fluency. Further work is needed to understand longitudinal changes in these linguistic variables, as well as their utility as measures of alogia. [ABSTRACT FROM AUTHOR]

The present study aimed to evaluate lexical diversity and sentence types in English. Sequential bilingual children from third (n=60) and fifth grade (n=60) were evaluated using an observation checklist and a language screening. 120 children identified with age-appropriate skills from screening were selected and written samples were collected in English using three written tasks. These samples were analyzed using TTR and Sentence Types. t-Test was done to identify the effect of age, gender, parental education, and school location on TTR, and Chisquare test was used to identify the influence of these factors on sentence production. Findings suggested that lexical diversity is not significantly influenced by grade but is influenced by gender, parental education, and school location. However, sentence types are influenced by all of these factors. [ABSTRACT FROM AUTHOR]

This study examines lexical density, lexical diversity and academic vocabulary use in the dissertation abstracts written by EFL (English as a foreign language), ESL (English as a second language) and English L1 (Native Speakers) postgraduate students to find out whether these lexical features differ across different English language backgrounds of writers. The data for this study came from a total of 75 dissertation abstracts (n=25 per group) which were about English Language Teaching and related areas. The abstracts were analyzed whereby automated text processing tools and the mean differences were compared between groups with ANOVA and post hoc analysis. A correlation analysis was also computed between the investigated variables. According to the findings, the lexical diversity index produced statistically significant differences between EFL and NS groups, however, the subtle mean differences in lexical density and academic vocabulary use were not found significant. On the other hand, the correlation co-efficient scores offered insights into the nature of relationships of the variables in question. The findings are discussed within the framework of the idiosyncratic context of the 'abstract genre'. [ABSTRACT FROM AUTHOR]

Crosslinguistic studies on motion events have revealed that S-languages demonstrate finer-grained lexical categories than V-languages in representing motion manners/gaits. But these studies were restricted to the semantic domain of motion events and confined to a limited number of S- or V- languages. In this paper, we further investigate whether the association between lexical diversity and language typology is manifest in a similar way in the semantic domain of separation events by focusing on Mandarin, Russian and Korean. Our results suggest that: (1) Separation expressions support the diversity-typology correlation proved in motion expressions because the two S-languages Mandarin and Russian demonstrate richer lexical diversity than the V-language Korean; (2) It is further pointed out that apart from language typology, lexical diversity is influenced by multiple factors including lexical resources, conceptual salience, event construal, and event type; (3) Though typologically different, these three languages, in their lexical naming of separation events, are constrained by the biomechanical structure and follow the principle of prototypicality. Overall, this study opens up a new crosslinguistic perspective by showing how lexical diversity is typologically and linguistically driven. [ABSTRACT FROM AUTHOR]

The development of artificial intelligence tools has seen an enormous growth recently. Linguistic artificial intelligence tools are being successfully applied in the field of speech analysis and discourse. In our study, we used automatic NLP tools to detect differences in picture description in the discourse of people diagnosed with Alzheimer's disease (AD), Mild Cognitive Impairment (MCI) and healthy people. A measure of lexical diversity was used to compare discourse complexity. Transcripts of recordings of the probands within the EWA project were used in the study. From the multiple comparisons, we found that there is a statistically significant difference between healthy people and people suffering from MCI and AD. Our results indicate that healthy people have more lexical diversity than people suffering from MCI and AD – a more diverse vocabulary in spontaneous speech, in our case, when describing a picture. [ABSTRACT FROM AUTHOR]

This paper discusses a case of constructional contamination (Pijpops and Van de Velde 2016; Pijpops et al. 2018), a phenomenon which describes the relation between two or more constructions such that usage frequencies of one construction influence the patterns of variation in another (Hilpert and Flach 2022). Specifically, I investigate the influence of structures of the type she gave a nod of intelligence or she nodded with satisfaction on the variation in the object slot of the so-called English Reaction Object Construction (ROC; Levin 1993), as in she nodded intelligence and she nodded satisfaction. Using the British Sentimental Novel Corpus (Ruano San Segundo and Bouso 2019) and the method of distinctive collexeme analysis (Gries and Stefanowitsch 2004; Hilpert 2006, 2014), it is argued that early and frequent structures superficially similar to the ROC, like those just mentioned, partly explain the lexical diversity found in the object slot of the nineteenth-century ROC (Bouso 2020b). The results thus corroborate findings on the pervasiveness of constructional contamination in English syntax, confirm the claim put forward in Bouso (2021) that the ROC can be treated as an example of a multiple source construction, and provide evidence of the large-scale transitivisation process experienced by the English language since Old English times.