In the context of Chinese language assessment research, the washback effects of listening tests remain an underexplored area. Considering that the Chinese education system is centered on examinations, major high-stakes tests, such as IELTS and CET-6, have a significant effect on the way Chinese EFL learners engage with English learning. This study aims to investigate the washback effects of IELTS and CET-6 listening tests and identify the differences between them. The significance of this comparison lies in intuitively revealing the differences in washback effects between IELTS and CET-6 listening tests and providing a research basis for further exploring the factors underlying these differences. This comparison will facilitate the future reform of IELTS and CET-6 listening tests, enhancing their positive washback effects on English listening teaching and learning. A total of 42 participants who had completed both IELTS and CET-6 within the previous year participated in this research and completed the questionnaire. The results showed that IELTS Listening had a more positive influence on English listening learning compared to CET-6 Listening. Specifically, in terms of preparation duration, daily practice intensity, the frequency of preparation activities, and behavioral changes, IELTS Listening exhibited more substantial washback effects in promoting students’ listening practice. The findings also indicated that most participants acknowledged the positive effects of their IELTS preparation experience, while they either disagreed or were uncertain about the effects of CET-6 Listening. These differences could stem from the motivational disparity and differences in perceived validity caused by the nature of the test design.

The Speech Assessment of Children's Home Language(s) (SACHL) offers a new, evidence-based clinical protocol for speech-language pathologists (SLPs) to assess speech in unfamiliar languages. This study used implementation science to investigate SLPs' current multilingual speech assessment practices, determine the prospective acceptability of the SACHL, and compare current confidence to prospective confidence with the SACHL. The Consolidated Framework for Implementation Research and the Theoretical Framework of Acceptability were used to explore innovation deliverers' (SLPs and student SLPs) prospective acceptability of the innovation (SACHL). Attendees at in-person and online SACHL presentations were invited to participate. A total of 360 participants responded to an online questionnaire exploring current practices, transcription skills, confidence, and acceptability of the SACHL. Statistical tests compared attendees at different presentations, SLPs and student SLPs, and monolingual and multilingual participants. The majority of participants indicated low current confidence in assessing multilingual children. Most SLPs assessed, transcribed, and analyzed multilingual children's speech in English but rarely or never applied these practices in children's home language(s). The majority of participants rated the SACHL as being culturally responsive, well designed, and easy to understand and that it could increase diagnostic accuracy. There were concerns around the time burden in using the SACHL. Most (87.45%) indicated they would like to use the SACHL in clinical practice, and there was a statistically significant improvement between current confidence and prospective confidence. https://doi.org/10.23641/asha.30716981.

Abstract The current study focuses on the use of Grammatical Error Correction (GEC) technology for assessing language accuracy, which has received relatively less attention than complexity and fluency in the context of automated assessment. Adopting a technology-enhanced approach to language assessment, rather than a technology-driven approach, we critically assessed the suitability of the state-of-the-art GEC system for assessing language accuracy in Korean, an understudied language in this regard. We analyzed how reliable this system is quantitatively and what types of error can be generated by this system qualitatively. Also, we used out-of-domain, inclusive data from heritage speakers of Korean, which has never been considered in the development of GEC. Our accuracy analyses show that the system achieves a fairly high accuracy in differentiating between correct and incorrect sentences on our data (F 0.5 = 0.819). However, the system exhibits a tendency to make unnecessary corrections, such as inserting topics/adverbials or correcting particles, while failing to correct ungrammatical ones in some cases. These findings from our mixed-method analyses suggest that language evaluators should recognize the potential for inaccurate assessments when using a GEC system, as its output may be incorrect at this moment, thus highlighting the critical need for digital language assessment literacy.

Green supplier selection is an important component of sustainable supply chain management, particularly in emerging markets where environmental rules and institutional support may be inadequate. This study addresses the need for a structured, sustainability-focused decision-making strategy by presenting a novel hybrid framework that merges the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The suggested methodology enables systematic evaluation of suppliers by including both subjective expert judgment and objective performance data under conditions of uncertainty. A case study conducted inside the Sri Lankan construction sector demonstrates the practical applicability of the concept. Suppliers were evaluated on four important criteria: environmental, economic, social, and technological. The data reveal that Supplier A is the most suited choice, excelling mainly in environmental and social dimensions. Environmental compliance emerged as the most relevant element in the selection process. By merging fuzzy language assessments with quantitative analysis, the hybrid Fuzzy AHP–TOPSIS method promotes the accuracy, transparency, and consistency of supplier evaluation. The results give valuable insights for industry practitioners, procurement managers, and legislators aiming to connect purchasing choices with long-term sustainability goals. Additionally, the framework gives an accurate platform for future research and application in similar scenarios, helping the growth of green purchasing practices in developing nations.

This article examines the interrelationships between pragmatics and culture and analyzes the role of these relationships in intercultural communication. The assessment of language not only as a structural element, but also as a field of socio-cultural activity reveals the importance of the pragmatic approach (Knoblauch, 2008). In intercultural communication, the correct understanding of the context, the speaker's intention, and social norms is one of the main indicators of pragmatic competence (Wierzbicka, 2006). Politeness strategies, indirect expressions, and contextual meanings manifest themselves in different ways across cultural environments, which can lead to misunderstandings and communication barriers in the communication process (Cohen, 2012). The article explains these differences from a theoretical point of view and at the same time illustrates them with specific examples. In this regard, the study of culture-related aspects of pragmatics is of great importance not only from a theoretical but also from a practical point of view (Ten Thije, 2020). The article examines how the same expressions are understood differently in different cultural contexts, what pragmatic errors can occur, and how these errors affect mutual communication (Žegarac & Pennington, 2000). At the same time, the importance of developing pragmatic competence in language learning processes to ensure mutual understanding in a global communication environment is highlighted (Cohen & Sykes, 2013). These results create a serious basis for establishing effective communication in international relations, translation, teaching as a foreign language, and multicultural societies. The article shows that a deep understanding of the interaction of pragmatics and culture is the key to success in the complex and diverse linguistic/cultural communication environment of the modern world (Hussan, 2024).

Traditional methods for language assessment in psychiatric and neurological disorders, such as clinical scales, are time and resource intensive, and can be hampered by rater biases and subjectivity. These limitations can compromise their reliability and sensitivity, as well as their practical use to measure change over time, which is of particular importance in clinical trials. Objective methods are required to improve the evaluation of language function across a spectrum of psychiatric and neurological conditions. To address these challenges, we introduce an innovative method that uses an artificial intelligence (AI) model, GPT-4, to provide an objective evaluation of language. As a test case, we focus on measuring expressive communication capabilities in autistic participants as they naturally converse with their study partner during an observational clinical trial. The conversations were recorded, professionally transcribed, and then processed with GPT-4 with the aim of predicting the individuals’ Vineland Adaptive Behaviour Scales (VABS-II) expressive communication scores. The model’s predictions were also compared with several benchmark linguistic features (e.g. the number of words spoken per sentence), to determine the added benefit of using such a complex model. We found that GPT-4’s predictions correlated strongly with the actual VABS-II scores (Pearson’s r > 0.65) and demonstrated high test–retest reliability (ICC(2,1) = 0.97). The model’s predictions also accounted for significantly more variance than that explained by the benchmark linguistic features. These findings demonstrate that GPT-4 can provide a holistic, reliable, objective, and time-efficient assessment of expressive communication abilities. This suggests that generative AI models like GPT-4 could transform the assessment of communicative abilities, to support the assessment of treatment efficacy in clinical trials, and provide a faster and more scalable tool for assessing patients in clinical practice.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-26944-8.

This study investigates the integration of technology in the English as a Foreign Language (EFL) assessment process at a Vocational High School in Samarinda. Although the role of technology in education is increasing, its application in EFL assessment is still minimal in this context. Using a qualitative approach, data were collected through interviews involving EFL teachers. There are three research questions underlying this study, the first is what are technology tools used in the EFL assessment process in a Vocational High School in Samarinda? the second is How is the technology used by the English Teachers of a Vocational High School in Samarinda? and the last is, What are the challenges in using technology for the EFL assessment process? This study reveals that English teachers at a Vocational High School in Samarinda have integrated various technological tools in EFL assessment, especially post-distance learning due to the COVID-19 pandemic. Tools such as Google Forms, Duolingo, Google Classroom, Quizizz, and Kahoot are widely used although most teachers have only acquired these skills through self-learning. The stages carried out by teachers in using digital technology tools in the assessment process are first preparation and drafting of online exam questions, second online assessment strategies and methods, third fraud monitoring and prevention, and finally exam materials and topics. The main challenges faced include limited internet access, unstable Wi-Fi networks in schools, and students' low digital literacy on the platforms used. Nevertheless, teachers are adapting and working towards effective assessment.

Teachers’ language assessment literacy: Exploring its construct and contextual factors

Abstract Iran’s Konkur exam (national university entrance test) assesses EFL proficiency solely through multiple-choice items, neglecting writing/speaking despite their academic importance. This study compares Intelligent Computer-Assisted Language Assessment (ICALA) and traditional assessments to address this gap. This 12-week mixed-methods study examined how ICALA affected motivation, anxiety, and proficiency in 120 intermediate Iranian EFL learners (CEFR B1–B2). The experimental group ( n = 60) used ICALA via DeepSeek, while the control group ( n = 60) received traditional instructor-led assessments with identical tasks (250-word essays, 2-min oral responses). Quantitative data from standardized measures (motivation, anxiety, and proficiency scales) and qualitative data from interviews and reflective journals were analyzed. ICALA demonstrated stronger benefits for motivation, anxiety reduction, and proficiency gains compared to traditional assessments, particularly among upper-intermediate (B2) learners. Qualitative analysis revealed three dominant themes: (1) enhanced competence through specific feedback, (2) reduced evaluation pressure, and (3) systematic skill improvement. While B2 learners thrived with ICALA’s detailed feedback (e.g., cohesion suggestions), some B1 learners required simplified guidance due to cognitive load. Although Konkur omits productive skills, ICALA improves writing and speaking proficiency, bridging the gap between exam preparation and academic needs. Simplified feedback for B1 learners, along with balanced speaking tasks, could further enhance outcomes. These findings inform EFL instruction reform in Konkur-driven contexts and contribute to Asia–Pacific and global AI assessment research.

This study aims to investigate the feasibility of implementing the Common European Framework of Reference (CEFR) for languages to reform English language assessment in Nepalese secondary schools, aligning teaching and testing with global standards. Through a qualitative approach, the study draws on a literature review of CEFR implementation in Asian contexts (Japan, Malaysia, and Vietnam), as well as semi-structured interviews with three stakeholders: two secondary school teachers and one policymaker. Findings reveal that Nepal’s current English assessment practices, which are heavily reliant on rote memorization and written tests, do not align with curriculum goals that emphasize communicative competence. Key challenges to CEFR adoption include inadequate teacher preparedness, resource constraints, misalignment between curriculum and assessment, and limited stakeholder engagement. Despite these barriers, CEFR offers opportunities to standardize assessments, promote balanced evaluation of all language skills, and enhance global comparability. Drawing on successful Asian models, the study recommends integrating the CEFR in a contextualized manner through sustained teacher professional development, curriculum revision, and inclusive stakeholder collaboration. Phased implementation and pilot testing are proposed to ensure equitable and sustainable reform, enabling Nepalese students to meet the linguistic demands of higher education and globalized contexts.

Abstract Understanding what makes second language (L2) listening comprehension difficult is crucial for advancing language learning and assessment. In L2 listening assessment, a key challenge is developing items with targeted difficulty levels. This difficulty can be influenced by textual and acoustic features from different item segments (i.e. stimuli, stems, and options) embedded in a multi-layered structure, along with task-related features. This study explores a feature-based machine learning (ML) approach to predicting difficulty of multiple-choice listening items on a local language proficiency test. We extracted construct-relevant textual and acoustic features from item segments across five dimensions: lexical complexity, syntactic complexity, fluency, pronunciation, and similarities among item segments. Incorporating these features, we compared traditional and mixed-effects ML models for predictive accuracy and interpretability. The best-performing model—a mixed-effects Ridge model with twenty-three features—achieved high accuracy (R2 = 0.860) and showed meaningful feature-difficulty relationships. This study presents methodological innovations for item difficulty modeling and offers practical implications for human- and machine-mediated item development. It also demonstrates potential of incorporating computational linguistics and ML in enhancing L2 listening assessment.

ABSTRACT Oral narratives are important for assessing children as narratives provide useful information about children's language development. This study aimed to explore how the narrative skills of Cypriot-Greek speaking children develop in the domains of syntactic productivity, complexity, and lexical diversity, during their preschool and primary school years. Additionally, the study sought to determine whether there was any difference in the performance of boys and girls on the narrative measures. One hundred and twenty-nine 4–9-year-old typically developing Cypriot-Greek-speaking children were recruited for the study. The Renfrew Bus Story was administered to elicit narratives, and microstructure measures were calculated and analysed. The results showed that there were developmental changes in three measures of syntactic productivity (number of C-units and total number of words) and lexical diversity (number of different words). On the contrary, measures of syntactic complexity (MLU-word, number of subordinate clauses and mean of the five longest sentences) did not significantly differentiate children between the three groups. In addition, the results showed no significant gender effect on narrative skills. This study provides initial evidence in retelling narrative development patterns on typically developing Cypriot-Greek-speaking children. Speech and language therapists can use this knowledge to compare children’s performance and detect children who are at high risk of experiencing language disorders.

The purpose of this study was to comprehensively examine written language performance in logopenic variant primary progressive aphasia (lvPPA) by (a) characterizing the types of errors made during single-word spelling-to-dictation and oral reading; (b) examining the role of phonological, semantic, and phonology-orthography transcoding skills on spelling and reading performance; and (c) exploring the influence of psycholinguistic properties on spelling and reading accuracy. Twenty-two individuals with lvPPA and 21 neurotypical controls performed comprehensive language assessment that included spelling to dictation and oral reading of pseudowords and real words with regular or irregular sound-letter correspondences. Factor scores representing phonological, semantic, and phonology-orthography transcoding skills were entered into multiple linear regressions to determine the degree to which these skills predicted performance on spelling and reading tasks. The psycholinguistic properties of real word stimuli were extracted at the item level and entered as predictors of spelling and reading accuracy in stepwise linear regression analyses. The mediating role of psycholinguistic properties on the relationship between semantics and phonology and spelling of real words was also explored. Pseudoword spelling performance was predicted by phonology-orthography transcoding skills. Spelling accuracy for regular words was predicted by semantics, phonology, and transcoding, whereas irregular word spelling performance was predicted by semantics and transcoding. Semantic neighborhood density, frequency, and imageability were significant predictors of spelling accuracy, while age of acquisition and imageability predicted reading accuracy. Semantic neighborhood density mediated the relationship between phonology and regular word spelling accuracy, whereas frequency mediated the relationship between semantics and irregular word spelling accuracy. The results of this study contribute to the understanding of language processes underlying spelling and reading performance in lvPPA. Specifically, we provide insights regarding the differential influence of phonological and semantic abilities on written language in lvPPA, and we highlight the importance of the psycholinguistic properties of linguistic stimuli in spelling and reading performance. https://doi.org/10.23641/asha.30594788.

Background: Although modifiers and function words are critical in cognitive linguistic assessments and cognitive training has proven to promote synaptic neural activity, they often receive limited attention, particularly in computational data-scarce settings. This study addresses communication difficulties associated with cognitive impairments using engineering data, a design to improve the evaluation of language attributes, applied specifically to these elements. A framework was developed to analyze potential language alterations resulting from traumatic brain injury (tbi), using narrative samples, primary data, and unconventional methods to overcome the limitations of existing resources. Methods: The core technique involves pairing language attributes based on defined relationships and assessing responses using standard statistical learning methods. Direct and normalized evaluations of variables, calculated using the Northwestern Narrative Language Analysis (nnla) profile from the original data, serve as benchmarks. The Area Under the Curve (auc) metric with the corresponding statistical support are reported. Results: The results indicate that the proposed method revealed informative patterns involving modifiers and function words that remained hidden in the baseline approaches. Although some exceptions were observed, results showed a substantially consistent behavior, and the responses achieved promote their use in a clinical setting. Conclusions: The findings can provide valuable directions for theoretical and applied research in language assessment. Identifying specific points of breakdown within language structures can improve the accuracy of rehabilitation plans and better leverage the neuroplastic response of the brain for recovery.

This paper examines the role of multiple-choice questions (MCQs) in language assessment, combining a review of existing research with a focused case study from Uzbekistan. From a pedagogical and psychometric perspective, the paper explores both the affordances and limitations of MCQs as tools for assessing language knowledge, receptive skills, and aspects of discourse and pragmatics. Drawing on sources such as Phakiti and Leung (2024), Hughes and Hughes (2020), and Bachman and Palmer (2010), the analysis highlights the standardisation, efficiency, and diagnostic precision that MCQs can offer, particularly in large-scale and high-stakes testing environments. At the same time, it addresses critical concerns, including the inability of MCQs to assess productive language skills, their tendency to fragment language knowledge, and their potential to distort teaching and learning. The paper also evaluates alternative assessment formats (e.g., cloze tests, constructed-response tasks, portfolios) and outlines principles for writing effective MCQs. The second part of the paper presents a document-based case study of the Pedagogical Excellence and International Assessment Centre in Uzbekistan and its use of MCQs in national summative assessments. The research material includes government resolutions and sample items from the end-of-quarter summative exams (ChSB), supported by critical commentary from local media sources. Analysis of this material suggests that MCQs have been instrumental in supporting the country’s transition to criterion-referenced, CEFR-aligned assessment, but that tensions may remain between goals of standardisation and concerns about test validity, teacher autonomy, and pedagogical washback. The paper concludes that MCQs are neither inherently flawed nor universally appropriate: their effectiveness depends on alignment with construct definitions, assessment purposes, and broader educational values.

This study investigates the implementation of Speech-to-Text (STT) and Text-to-Speech (TTS) technologies in multimodal English as a Foreign Language (EFL) assessment for students with disabilities in Indonesian special senior high schools (SMALB). Using an embedded mixed-methods design, the research involved 25 students with diverse disabilities, alongside teachers and support staff, to explore how STT and TTS tools support inclusive pedagogy and assessment. Qualitative data from observations, interviews, and student work samples were integrated with quantitative results from language performance tests and attitude questionnaires. The findings indicate that STT and TTS technologies enhanced accessibility, engagement, and learner autonomy, allowing students to demonstrate language competence through alternative modalities aligned with Universal Design for Learning (UDL) principles. Teachers reported increased sensitivity to learner diversity and adopted more flexible, student-centered assessment strategies. Quantitative analyses showed significant improvements in students' speaking and writing performance, as well as positive shifts in motivation and confidence. Despite implementation challenges such as limited infrastructure and teacher readiness, the study highlights the transformative potential of assistive technologies in advancing equitable and meaningful EFL instruction in inclusive settings. These insights contribute to the growing discourse on inclusive digital education in under-resourced contexts and inform future policy, practice, and teacher training initiatives.

Evaluation in Arabic language learning is essential to measure students' achievement; however, the quality of tests used in Indonesia still requires improvement. This study employed the Systematic Literature Review (SLR) method to analyze the validity, reliability, difficulty level, and discrimination power of Arabic test items, based on a synthesis of six articles indexed in SINTA and Scopus, published between 2019 and 2024. This SLR approach offers a new contribution by systematically revealing national trends and gaps in item quality, which have not been comprehensively analyzed in previous studies. The findings show that on average, 66% of the items were valid, and most tests demonstrated very high reliability (≥ 0.85), although some tests had low reliability (0.54). The distribution of difficulty levels was imbalanced, with 50.83% of items being too easy and only 7.67% classified as difficult, deviating from the ideal distribution. Additionally, 34% of the items exhibited low discrimination power, reducing the effectiveness of assessments in distinguishing students' abilities. These imbalances can lead to biased evaluations and hinder students' competency development. The practical implications of this study include the importance of teacher training in item analysis, the application of Bloom's Taxonomy to balance item difficulty levels, and the development of a standardized, data-driven item bank. The main contribution of this research is to provide empirical foundations for improving Arabic language assessment policies in Indonesia and to propose a more accurate and fair evidence-based evaluation approach.

This preliminary study evaluated the relative importance of seven language screening measures, including sentence repetition, vocabulary, nonword repetition, listening comprehension, and word learning, in predicting overall language ability. A total of 126 kindergarten and first-grade students completed a comprehensive language screening battery, followed by an overall language assessment. Dominance analysis was used to assess complete, conditional, and general dominance for all language predictors. Sentence repetition emerged as the most dominant predictor, demonstrating complete dominance over all other language predictors. A synonyms task was the second strongest predictor, though there was a substantial gap in the variance explained between sentence repetition and synonyms. The word learning task was the weakest predictor among all measures. This study supports prior research underscoring the strength of sentence repetition as a screening measure. While sentence repetition should serve as the cornerstone of language screening, further research is needed to explore whether additional language measures enhance accuracy.

ABSTRACT Background Individuals with aphasia (IWA) often exhibit challenges in single-word oral reading as well as in reading comprehension. Recently, eye-tracking technology has become instrumental in delving deeper into reading behaviors. Specifically, it has illuminated the differences in word reading and comprehension abilities among English speakers who have aphasia. However, there is a noticeable scarcity of research focusing on these aspects among Chinese IWA. Purpose This study aimed to compare single-word oral reading (regular, irregular, pseudowords) and comprehension abilities between Chinese IWA and neurotypical controls, while investigating eye-tracking measures (fixation durations, saccades) during sentence reading and their association with comprehension. Method Twenty-one IWA and Twenty-two controls, aged 18–80, were diagnosed using CT or MRI and the Western Aphasia Battery (WAB). In addition, all participants underwent cognitive screening and language assessment using the China Rehabilitation Research Center Aphasia Examination (CRRCAE). Eye movements during Chinese sentence reading were recorded using the Tobii Pro Spectrum eye-tracker. Reading comprehension and word-reading accuracy were assessed. Data were analyzed using Mann-Whitney U tests and one-way ANOVAs, controlling for education and time post-onset. Results Controls outperformed IWA in reading accuracy across all word types and comprehension tasks. IWA exhibited longer fixations, more frequent fixations, and shorter saccades. Significant correlations between regular/irregular word reading and comprehension were found in IWA, but not in controls. Regression analysis revealed regular and irregular word reading accounted for 62.4% in IWA, even after controlling for education and time post-stroke. Conclusions The strong influence of regular and irregular word oral reading on comprehension in IWA suggests potential for targeted interventions. This study underscores the complexity of reading comprehension, highlighting the need for holistic approaches in future research to explore factors influencing reading in Chinese IWA and neurotypical individuals.

While extensive research has focused on ChatGPT in recent years, very few studies have systematically quantified and compared linguistic features between human-written and artificial intelligence (AI)-generated language. This exploratory study aims to investigate how various linguistic components are represented in both types of texts, assessing AI’s ability to emulate human writing. Using human-authored essays as a benchmark, we prompted ChatGPT to generate essays of equivalent length. These texts were analyzed using Open Brain AI, an online computational tool, to extract measures of phonological, morphological, syntactic, and lexical constituents. Despite AI-generated texts appearing to mimic human speech, the results revealed significant differences across multiple linguistic features such as specific types of consonants, nouns, adjectives, pronouns, adjectival/prepositional modifiers, and use of difficult words, among others. These findings underscore the importance of integrating automated tools for efficient language assessment, reducing time and effort in data analysis. Moreover, they emphasize the necessity for enhanced training methodologies to improve AI’s engineering capacity for producing more human-like text.