Understanding how a child's language system develops into an adult-like system is a central question in language development research. An increasingly influential account proposes that the brain constantly generates top-down predictions and matches them against incoming input, with higher-level cognitive models serving to minimize prediction…

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…

With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better…

Natural languages contain systematic relationships between verb meaning and verb argument structure. Artificial language learning studies typically remove those relationships and instead pair verb meanings randomly with structures. Adult participants in such studies can detect statistical regularities associated with words in these languages and…

During spoken word processing, native (L1) listeners use allophonic variation to predictively rule out word competitors and speed up word recognition. There is some evidence that second language (L2) learners develop an awareness of allophonic distributions in their L2, but whether they use their knowledge to facilitate word recognition online,…

Background/purpose: ChatGPT has become one of the groundbreaking examples of artificial intelligence-based chatbots with its capacity to produce texts and engage in human-like conversations. Therefore, it has garnered the attention of people with diverse backgrounds, including educational professionals. The current study aims to investigate how…

Background/Purpose: Integrating artificial intelligence tools within educational settings has generated considerable debate, yet empirical research that offers implications of its usage remains scarce. This study aims to qualitatively assess the perceptions and experiences of school principals and teachers regarding the use of ChatGPT in K-12…

Purpose: This qualitative work aims to explore the university students' attitude toward advantages, drawbacks and prospects of ChatGPT. Design/methodology/approach: This paper applies well accepted Colaizzi's phenomenological descriptive method of enquiry and content analysis method to reveal the ChatGPT user experience of students in the higher…

Massive online user review platforms, with their star ratings and text reviews, are reshaping the information available for consumer and public service decisions. We study the leading K-12 schooling platform, GreatSchools, applying machine learning (Natural Language Processing, NLP) to 600,000 reviews that encompass the vast majority of the…

In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digital learning platforms may need to examine and provide feedback across many images of students' math work. To assess the potential of VLMs to support…

The use of machine translation has become a topic of debate in language learning, which highlights the need to thoroughly examine the appropriateness and role of machine translation in educational settings. Under the theoretical framework of task-technology fit, this explanatory case study set out to investigate the predictive role of machine…

During the last few years, the popularity of chatbots has risen and grown exponentially with the increase in demand for smartphones and messaging applications. Chatbots can be utilized in education by providing information about educational content, communication, and assistance, enhancing classroom participation, and facilitating collaborative…

Evidence from neuropsychological studies of individuals with brain damage post-stroke has supported the separation of working memory (WM) capacities for semantic (word meaning) and phonological (speech sound) information. These separate capacities have been shown to play different roles in supporting multiword language production, with semantic WM…

Recent developments in technology have accelerated the influence of artificial intelligence (AI) on our lives. The National Literacy Trust is interested in exploring how such platforms might influence, and potentially redefine, what it means to be literate in the digital age. Based on data from more than 50,000 children and young people taking…

Urban and rural children have different levels of performance in arithmetic processing. This study investigated whether such a residence difference can be explained by phonological processing. A total of 1,501 Chinese primary school students from urban and rural areas were recruited to complete nine cognitive tasks: two in arithmetic performance…