Word segmentation is a crucial step in children's vocabulary learning. While computational models of word segmentation can capture infants' performance in small-scale artificial tasks, the examination of early word segmentation in naturalistic settings has been limited by the lack of measures that can relate models' performance to developmental…

The recent surge in the popularity of Large Language Models (LLM) for language assessment underscores the growing significance of cost-effective language evaluation in our increasingly digitalized society. This paper posits that the application of computational psychometrics can enable the incorporation of technology into language assessment,…

Many datasets resulting from participant ratings for word norms and also concreteness ratios are available. However, the concreteness information of infrequent words and non-words is rare. This work aims to propose a model for estimating the concreteness of infrequent and new lexicons. Here, we used Lancaster sensory-motor word norms to predict…

Purpose: Acoustic measurement of speech sounds requires first segmenting the speech signal into relevant units (words, phones, etc.). Manual segmentation is cumbersome and time consuming. Forced-alignment algorithms automate this process by aligning a transcript and a speech sample. We compared the phoneme-level alignment performance of five…

Most words in natural languages are polysemous; that is, they have related but different meanings in different contexts. This one-to-many mapping of form to meaning presents a challenge to understanding how word meanings are learned, represented, and processed. Previous work has focused on solutions in which multiple static semantic…

Complex Dynamic Systems Theory (CDST) has significantly reshaped our understanding of second language learning and teaching across the micro, meso, and macro levels for several decades since its systematic introduction by Larsen-Freeman and Cameron (2008). This study conducts a comprehensive review of empirical research on second language learning…

We provide an account of the developmental trajectory of Emirati Arabic negation particles. We treat the non-verbal predicate negator (NVPN) "mub" as a negative copula, in contrast to the verbal predicate negator (VPN) "maa," which encodes sentential negation in verbal and existential contexts. The analysis is supported by…

The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…

This article investigates the roles of the terms agreement and disagreement in teachers' talk in Norwegian Grades 1-4 classrooms. Through an exploration of what teachers said and did when they used these terms, five different themes were identified in the teachers' talk. The teachers tended to use the terms in relation to the process of…

Advances in Natural Language Processing (NLP) over the past decade have largely been driven by the scale of data and computation used to train large neural network-based models. However, these techniques are inapplicable to the vast majority of the world's languages, which lack the vast digitized text datasets available for English and a few other…

The development and construction of doctoral students' academic identity have become an area of research interest, focusing on the link between identity issues and the use of intertextuality in postgraduate students. While prior studies concentrated on written features and citation patterns, a more nuanced understanding of identity negotiations…

Recent scholarship has called for deeper communications and collaborations between writing studies and language studies because such interdisciplinary connections can facilitate the growth of both fields. While research has explored the potential exchanges between writing studies and language-related fields (such as applied linguistics, second…

We study how to automatically generate cloze questions from given texts to assess reading comprehension, where a cloze question consists of a stem with a blank space holder for the answer key, and three distractors for generating confusions. We present a generative method called CQG (Cloze Question Generator) for constructing cloze questions from…

Providing timely and personalized feedback on open-ended student responses is a challenge in education due to the increased workloads and time constraints educators face. While existing research has explored how learning analytic approaches can support feedback provision, previous studies have not sufficiently investigated educators' perspectives…

We conducted two experiments to assess the alignment between Generative AI (GenAI) text personalization and hypothetical readers' profiles. In Experiment 1, four LLMs (i.e., Claude 3.5 Sonnet; Llama; Gemini Pro 1.5; ChatGPT 4) were prompted to tailor 10 science texts (i.e., biology, chemistry, physics) to accommodate four different profiles…