Lexical Complexity Research Articles

Metacognitive Instruction for Improving the Effectiveness of Collaborative Writing for EFL Learners’ Writing Development

AbstractThere has been substantial research on the effects of metacognitive instruction on improving L2 learners’ language skills. However, little is known about the impact of such instruction on improving the effectiveness of L2 students’ collaborative writing. To fill this research gap, we conducted a quasi-experimental study to investigate how such an instructional programme would help Chinese EFL learners’ writing development through collaborative writing. A total of 62 post-graduate students from a university in central China were randomly allocated to either an experimental group receiving three weeks of collaborative writing interventions with metacognitive instruction for writing collaboratively, or a control group that was taught via a genre-based approach. Pre-test, immediate post-test, and delayed post-tests were administered with both groups at the onset, immediately after, and six weeks after the interventions to compare their change in writing production, specifically in lexical complexity, accuracy, and fluency. Results revealed that the metacognitive instruction and collaborative writing interventions helped improve participants’ writing performance in lexical variation, accuracy, and fluency. However, no significant effects were observed in lexical density and lexical sophistication. We discuss the results for their pedagogical and theoretical implications.

Readability and Writing Quality in Radiation Oncology Journal Articles from 2004 to 2024

PurposeScientific literature is a vital tool which we rely upon to communicate the findings of our studies; however, we rarely direct our study to the writing itself. Methods and MaterialsHere, we make use of modern natural language processing algorithms coupled with the large, open access PubMed Central corpus to analyze trends in writing complexity within the field of radiation oncology from 2004–2024. Changes in 1) required grade-level to comprehend, 2) lexical complexity, and 3) information content were assessed. Articles were also classified—and then analyzed—by disease subsite. ResultsWe found significant increases in the three domains over the twenty-year collection period. Genitourinary literature had the greatest readability while gastrointestinal literature was the most complex. ConclusionsThis analysis reveals broad increases in the complexity of our writing. This study demonstrates metrics to use, and benchmark values to refer to, to evaluate the complexity of radiation oncology journal articles.

A refined and concise model of indices for quantitatively measuring lexical richness of Chinese university students’ EFL writing

In the existing literature, scholars have proposed various indices to measure the lexical richness (LR) of English as a foreign language (EFL) writing. However, there are currently issues of redundant indices and inconsistent usage. Attempting to address the research question of which indices are the most sensitive and effective ones to distinguish between different grade levels of Chinese university students’ EFL writing, this study aims to put forward a refined and concise model of indices that can truthfully reflect LR in EFL writing. A total of 180 compositions were selected from a Chinese EFL learner corpus: <i>Spoken and written English corpus of Chinese learners</i>. Scores of 28 LR indices of these compositions were computed using the software <i>Lexical Complexity Analyzer</i>,<i> MATTR</i>,<i> </i>and<i> Coh-Metrix</i>. One-way ANOVA or Welch’s ANOVA, depending on the variable’s homogeneity of variances, was conducted for each index. Two criteria were applied to determine which index of a measure should be included in the refined model: whether the difference of an index is significant among different grade levels and the effect size of ANOVA. Based on the quantitative results of ANOVAs and qualitative human judgment based on literature, six indices of the six LR measures were included in the refined model: lexical density, lexical sophistication-I, verb sophistication-II, number of different words-expected sequence 50, corrected TTR, and squared verb variation-I. This refined model addresses the issues of redundancy and inconsistency in previous studies, providing a more accurate and efficient tool for assessing LR in EFL writing.

THE CHALLENGES FACED BY ENGLISH STUDENTS IN ACADEMIC WRITING (A CASE STUDY AT UIN SULTHAN THAHA SAIFUDDIN JAMBI)

This study aimed to investigate the difficulties encountered by students of English in academic writing at the Islamic University State Sulthan Thaha Saifuddin Jambi, focusing on previous academic year 2022/2023. Employing a qualitative approach through a case study design, the research gathered data via interviews and document analysis. Findings revealed that students face several challenges in academic writing, including plagiarism, lexical complexities, grammatical errors, topic selection, inadequate planning, lack of motivation, and punctuation issues.

Impact of Social Media on English Language Learning Among First-Year Students at Qassim University

The diverse aspects and networks of social media have wielded a remarkably profound impact on both individual lives and the broader societal, economic, and political landscape of its users. Language patterns used by conversational partners on social media have been influenced significantly. This study aims to investigate how the English language learning process of non-native Saudis has been impacted by the use of social media. To investigate these effects, a quantitative methodology was employed through the distribution of an online questionnaire to selected groups of first-year students at Qassim University, Saudi Arabia. Responses from 47 participants from different genders were analyzed using measures of central tendency and other statistical measures. The findings revealed that first-year Qassim University students consider social media platforms to be beneficial for improving their L2 proficiency and evaluate them to have an overall positive impact on various language learning skills. Based on these findings, it is reasonable to indicate that social media can be a significantly helpful tool in improving English language learning. These results were subjective to variables related to gender and the multimodal nature of specific aspects of social media. The study implies that employing social media networks can illustrate a more student-centered approach to language learning through the facilitation of interactive collaboration and information exchange, resulting in enhanced syntactic and lexical complexity.

Vocabulary exposure to children is enhanced by using both informational and narrative picture books for read‐alouds: A comparative modelling study using data science methods

BackgroundThe language that children are exposed to in their early years is enhanced by children's picture books. It is important to better characterise this input, and recent research has begun to explore corpora of narrative picture books. However, previous research has been restricted by methodological limitations that make it difficult to develop large datasets. Further, information texts become increasingly important as children progress through school, but little is known about the language of their earliest form, namely, informational picture books. The current study investigates how informational and narrative picture book exposure might change the language environment of children in a way that supports reading development.MethodsThe study applies data science methods to build a larger language model than previously possible and investigates the lexical profile of over 2000 narrative and information picture books. Picture book vocabulary is innovatively derived from digital sources of books read‐aloud online, which pushes the field forward by providing researchers access to larger pools of data than previously possible. Detailed comparisons of informational and narrative picture books are reported regarding their lexical diversity, density, morphology, academic vocabulary and semantic clusters. Models are developed to estimate the additional word‐type exposure a child may encounter in their language environment from narrative and informational picture books.ResultsThe study demonstrates that information and narrative picture books expose children to substantially different semantic environments. It is demonstrated that information picture books provide extensive exposure to academic vocabulary, providing important input aligned with later reading needs. Further, computational models indicate that book reading once every day or second day over a year might boost unique‐word exposure by approximately 10% for some language environments.ConclusionsCombining informational and narrative picture books enhance the language environment of children more than narratives alone, providing more lexical diversity, density and complex morphology.

Over-lexicalization and Under-lexicalization of Physical Violence Expression in Laut Bercerita and Its Translation by Leila S. Chudori

Although research on lexicalization has been extensively documented, little is known about over- and under-lexicalization in translation. "Laut Bercerita" and its translation contain mostly violent physical expressions, leading to either excessive or deficient lexical representation compared to the source text. This research aims to analyze over- and under-lexicalization in expressions of physical violence in the novel "Laut Bercerita" and its translation "The Sea Speaks His Name". The research method used is comparative descriptive, which combines comparing the meanings of the source text and target text. Data were collected using note-taking techniques. In the analysis stage, the data were first segmented or classified based on categories of physical violence. Subsequently, the data were analyzed by adopting a lexical variation of Fowler’s theory. The results of the study showed that over-lexicalization occurred in the form of physical violence such as (1) kicking, (2) torturing, (3) electric shocking, (4) slapping, (5) punching, and (6) stepping on, accounting for 47%. Meanwhile, under-lexicalization occurred in the form of physical violence such as (1) hitting, (2) kicking, (3) torturing, (4) electric shocking, (5) handcuffing, (6) punching, and (7) stepping on, accounting for 57%. Under-lexicalization occurs when there is a reduction of lexical items and simplification of meaning concepts, while over-lexicalization occurs with the addition of lexical items and complex meanings. Over-lexicalization and under-lexicalization imply that the translation may not meet standard translation norms through lexicon choices but still maintains equivalence.

An Examination of the Degree of Complexity of Teacher Questions in English-Medium University Courses

Research has demonstrated that questions are essential when teachers endeavor to foster students’ comprehension and learning of the subject taught. However, there is a scarcity of studies on questioning practices in English-medium instruction (EMI) settings. In this study, we aim to fill this gap by focusing on the linguistic complexity of the questions put forward by EMI lecturers by paying particular heed to whether the disciplinary culture exerts any influence on the complexity of lecturers’ questioning practices. The study was conducted at four public Spanish universities in which the classes delivered by nine EMI lecturers from three different disciplines (history, economics, and engineering) were recorded and analyzed. The statistical analyses performed found no significant differences in the lexical and syntactic complexity of the questions posed in the three disciplines, while language at the C level of the Common European Framework of Reference for Languages (CEFR) was conspicuous by its absence. These results lead us to conclude that if students are not widely exposed to language at the C level of the CEFR, oral language development and improvement may not be promoted in EMI courses. Therefore, EMI teacher training should be given more attention.

Mapping the interactions between task sequencing, anxiety, and enjoyment in L2 writing development

This study explores the relationships between task sequencing, task anxiety, task enjoyment, and second language (L2) writing development. While L2 writing is influenced by various factors, including task sequencing and learner-related variables, empirical evidence on the interactions between task sequencing and task emotions in L2 writing development is scarce. To address this gap, 75 L2 English students performed nine versions of three decision-making tasks in different sequences (simple to complex, complex to simple, or random) over nine weeks. The participants completed post-task questionnaires on their perceptions of the tasks, task anxiety, and task enjoyment, and their essays were analyzed for syntactic complexity, accuracy, lexical complexity, and fluency (CALF). Linear mixed-effect modeling examined the effect of task sequencing on CALF measures and task emotions. Results revealed that the simple-to-complex group had the best performance in CALF measures compared to other groups. Furthermore, the complex-to-simple group outperformed the random group in accuracy, lexical complexity, and fluency measures. Participants showed improved writing over time and experienced less task anxiety and more task enjoyment in the simple-to-complex group. Overall, this study suggests that task sequencing plays a crucial role in L2 writing development by improving learners’ performance, enjoyment, while reducing anxiety.

Does “more complexity” equal “better writing”? Investigating the relationship between form-based complexity and meaning-based complexity in high school EFL learners’ argumentative writing

The study examines the relationship between form-based complexity and meaning-based complexity in argumentative essays written by high school students learning English as a foreign language (EFL) in relation to writing quality. The data comprise argumentative essays written by 102 Japanese high school learners at different proficiency levels. The students’ proficiency levels were determined based on the evaluation of their argumentative essays by human raters using the GTEC rubric. The students’ essays were analyzed from multiple dimensions, focusing on both form-based complexity (lexical complexity, large-grained syntactic complexity, and fine-grained syntactic complexity features) and meaning-based complexity (argument quality). The results of the multidimensional analysis revealed that the most influential factor in determining overall essay scores was not form-based complexity but meaning-based complexity achieved through argument quality. Moreover, the results indicated that meaning-based complexity was strongly correlated with the use of complex nominals rather than clausal complexity. These insights have significant implications for both the teaching and assessment of argumentative essays among high school EFL learners, underscoring the importance of understanding what aspects of writing to prioritize and how best to assess student writing.

A comparison of narrative abilities in Malay school-age typically developing children and children with developmental language disorder

ABSTRACT Research on narrative skills in the Malay language is scarce for both typically developing (TD) and children with Developmental Language Disorders (DLD). This study examines the differences in narrative abilities of Malay-speaking school-age children with and without DLD. Fifteen Malay-speaking TD children and 15 children with DLD told four stories elicited using the Multilingual Assessment Instrument for Narrative (MAIN). Group comparisons were conducted in narrative production (story retelling and story generation) as well as in comprehension. We also examined the differences in both groups’ story complexity (e.g. the combination of goals (G), attempts (A) and outcomes (O)). General microstructure features such as the total number of words (TNW), total number of sentences (TNS) and total number of different words (NDW) were also investigated. TD children outperformed children with DLD in both narrative production and comprehension performances. TD children constructed a higher combination of G, A, and O components than children with DLD. Children with DLD frequently produced G, A, and O in isolation in comparison to TD children. In language productivity and lexical complexity, TD children had a significantly higher frequency in TNW and NDW than children with DLD, resulting in longer narratives and higher uses of different words than children with DLD. Distinct differences are found in the narrative profile of TD children and children with DLD. The results are relatively consistent with the findings of similar studies that utilised and adapted the MAIN in other languages. Clinical implications and recommendations are discussed.

The dynamics of syntactic and lexical complexity measures in academic writing

This study explores the L2 production of university students enrolled in an English as a Medium of Instruction (EMI) course, by means of the analysis of the complexity of their academic writing performance. It focuses on syntactic and lexical complexity and their relationship with L2 writing quality and L2 proficiency. The participants were 182 L2 college-level students at difference levels of proficiency in English. The essays were evaluated by means of both global ratings of writing quality and quantitative measures of syntactic and lexical analysis. Results showed that the length of sentences and noun phrases, as well as subordination are all related to writing quality. In addition, the length of noun phrases along with lexical richness and diversity can differentiate proficiency levels. This study shows a greater use of complex phrasal constructions in the writing of more competent third-level students. Finally, our study that at advanced competence levels syntactic and lexical complexity are not synchronous, as syntactic complexity remains stable while lexical complexity continues increasing.

EXPLORING LEXICAL COMPLEXITY IN SCIENTIFIC WRITING: A CORPUS-BASED STUDY ACROSS DISCIPLINES

This study examines the lexical complexity of scientific writing. It specifically focuses on the degree of lexical density and lexical diversity in the results and discussion sections of research articles. Using a qualitative approach with quantification to back it up, this study scrutinized 60 results and discussion sections of research articles written by Tunisian linguistics and engineering scholars. The analysis was conducted using the lexical complexity analyzer developed by Lu (2010). Moreover, descriptive analysis and the independent T-test were conducted to ascertain the statistical distinctions between the discussion and results sections of linguistics and engineering disciplines. The findings suggest that engineering scholars wrote in a more concise and information-dense style, with a greater lexical density, while linguistics scholars used a broader range of linguistic forms, resulting in more diverse and richer expressions. The differences in writing style can be attributed to the nature of the disciplines and the types of research conducted within each field. The results obtained from this study may offer valuable implications for English for Academic Purposes (EAP) writing instructions.

Tapping into the Pedagogical Potential of infinigoChatIC: Evidence from iWrite Scoring and Comments and Lu & Ai’s Linguistic Complexity Analyzer

ChatGPT has drawn rapid interest among linguists and language teachers, with academics and industries rushing to tap into its potential. Yet the pedagogical potential of ChatGPT for L2 English writing remains to be further explored academically. This study aims to examine the effects of ChatGPT, or one of its Chinese versions called infinigoChatIC, in improving the quality of L2 writing and in facilitating the development of L2 proficiency among some postgraduate students learning an English reading and writing course in a prestigious university in Southwest China. Specifically, the main research questions focus on how infinigoChatIC-polished L2 English writings perform in comparison to L2 learner writings, and how the improvement of English writing is reflected in the changes of lexical and syntactic complexity, as evidenced by measured data and its pedagogical significance. A set of 24 English writings are collected as part of regular homework assignments, then this set of English writing is polished by the teacher researcher in the infinigoChatIC dialogue box with the prompt “please correct grammatical errors in the following English text so that it is grammatically accurate.” These two sets of writings are scored in iWrite automatic scoring system and then analyzed in Lu & Ai’s web-interfaced linguistic complexity analyzer. The study finds that infinigoChatIC can effectively improve the quality of L2 English writing, with lexical complexity vastly improved and yet surprisingly overall syntactic complexity slightly reduced. Pedagogical implications are discussed.

Artificial Intelligence-Assisted Chinese L2 Writing: An Empirical Study on Educational Sustainability in Africa

This study investigates the impact of ChatGPT on Chinese L2 writing proficiency among African students, aligning with the Sustainable Development Goals (SDGs) for quality education and reduced inequalities. Employing a mixed-methods approach, the research involved 46 participants to quantitatively assess improvements in syntactic and lexical complexity, accuracy, and fluency. Qualitative insights were garnered through semi-structured interviews, revealing positive perceptions of ChatGPT in enhancing writing skills, yet highlighting challenges like technological access and economic constraints. The findings suggest that while ChatGPT effectively enhances Chinese L2 proficiency, its integration in African educational contexts requires addressing infrastructural and pedagogical barriers. This study contributes to the discourse on Artificial Intelligence in language education and its role in advancing African sustainable educational practices.

Translation Algorithm of Proper Nouns in English-Chinese Translation Based on Lexical Knowledge Spectrum Map

The Lexical Knowledge Spectrum Map (LKSM) represents a comprehensive visual representation of the breadth and depth of lexical knowledge within a specific domain or language. By categorizing words and phrases along a spectrum ranging from basic to advanced levels of complexity, the LKSM provides learners and educators with a clear overview of vocabulary proficiency and progression. This dynamic tool not only helps individuals track their language learning journey but also guides instructional planning by identifying areas of focus and potential gaps in lexical understanding. With its intuitive interface and adaptable framework, the LKSM serves as a valuable resource for promoting effective vocabulary acquisition and mastery across diverse linguistic contexts and educational settings. This paper introduces a novel translation algorithm designed specifically for handling proper nouns in English-Chinese translation, leveraging the Lexical Knowledge Spectrum Map (LKSM) and Feature Vector Optimization with Statistical (FVOS) techniques. Proper nouns pose a unique challenge in translation due to their cultural and contextual significance, often requiring specialized handling to ensure accuracy and coherence in the target language. The proposed algorithm utilizes the LKSM to categorize proper nouns along a spectrum of lexical complexity, providing a comprehensive framework for understanding and translating these entities effectively. Additionally, FVOS techniques are employed to optimize feature vectors for proper noun translation, enhancing the algorithm's ability to capture and preserve semantic nuances across languages. With FVOS model English proper nouns translated into Chinese, the proposed algorithm achieves an average accuracy of 85%, outperforming baseline translation methods by 15%. Moreover, specific proper noun categories exhibit notable improvements, with names of people achieving an accuracy of 90%, followed by locations at 85%, and organizations at 80%.

Modifying Language for a Higher Goal: Investigating Quantitative Features of Apple’s Launch Event Speech from 2016 to 2022

ABSTRACT In response to the COVID-19 pandemic, Apple Inc. switched its product launch from onsite events to pre-recorded online broadcasts. Yet this form has been carried on even though the pandemic has faded. It is unclear if this shift was accompanied by a move in language complexity and how the communication effect was influenced. This study analysed Apple’s product launch events from 2016 to 2022 using quantitative linguistics metrics such as lexical complexity, word token length, entropy, readability, and sentence length distribution. The analysis adopted the reach-effect-durability framework for interpreting the effects of strategic communication. The results showed that Apple’s online product launch events featured richer and longer words, increased text difficulty, and a decrease in the proportion of short sentences. Such changes happened in a balanced manner that can be interpreted in view of the driving and restraining forces resulting from the mode shift of the launch event. This study demonstrates the feasibility of assessing efforts and strategies used in a communication campaign through quantitative text analysis.

Song lyrics have become simpler and more repetitive over the last five decades

Music is ubiquitous in our everyday lives, and lyrics play an integral role when we listen to music. The complex relationships between lyrical content, its temporal evolution over the last decades, and genre-specific variations, however, are yet to be fully understood. In this work, we investigate the dynamics of English lyrics of Western, popular music over five decades and five genres, using a wide set of lyrics descriptors, including lyrical complexity, structure, emotion, and popularity. We find that pop music lyrics have become simpler and easier to comprehend over time: not only does the lexical complexity of lyrics decrease (for instance, captured by vocabulary richness or readability of lyrics), but we also observe that the structural complexity (for instance, the repetitiveness of lyrics) has decreased. In addition, we confirm previous analyses showing that the emotion described by lyrics has become more negative and that lyrics have become more personal over the last five decades. Finally, a comparison of lyrics view counts and listening counts shows that when it comes to the listeners’ interest in lyrics, for instance, rock fans mostly enjoy lyrics from older songs; country fans are more interested in new songs’ lyrics.

Mediating effects of NLP-based parameters on the readability of crowdsourced wikipedia articles

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.

Dynamic Development in L2 Written Complexity of Chinese EFL Learners

Abstract The present study investigated the developmental trajectories of written language of two Chinese EFL learners in terms of complexity over one semester and explored the relationship between syntactic complexity and lexical complexity under the framework of Complex Dynamic Systems Theory (CDST). The data were processed using dynamic analyses (min-max graphs, moving correlations and Change-point analysis) to visualize the developmental process and variability of each subsystem of complexity with 4 measures (mean length of T-unit, mean length of clause, clauses per T-unit and VocD) and interactions between different subsystems. The results showed, first, that different subsystems of written language complexity developed dynamically and nonlinearly with different degrees of variability, and varied in the two participants. Second, interactions existed between syntactic complexity and lexical complexity, which shaped as competitors for Jenny but as connected growers for Helen. The results further deepened the understanding of the development in learners’ written complexity, providing significant implications for EFL writing teaching.