This study applies the Apriori algorithm to analyse patterns, syntactic structures, and thematic clusters in Chinese studies data from various genres. This study aims to identify recurring linguistic elements in order to shed light on the dynamic nature of the Chinese language across different contexts and time periods. The Apriori algorithm is…

In this paper we describe a framework for teaching students when they should, or should not use generative AI such as ChatGPT. Generative AI has created a fundamental shift in how students can complete their class assignments, and other tasks such as building resumes and creating cover letters, and we believe it is imperative that we teach…

Multisyllabic words constitute a large portion of children's vocabulary. However, the relationship between phonological neighborhood density and English multisyllabic word learning is poorly understood. We examine this link in three, four and six year old children using a corpus-based approach. While we were able to replicate the well-accepted…

This study investigated the effects of semantic transparency of Chinese suon Chinese as a second language (CSL) learners' incidental learning of word meanings in sentence-level reading and passage-level reading. The accuracy of the learners' lexical inferencing was compared among various types of words (transparent, semi-transparent, and opaque…

Deficits in working memory have not been fully explored in toddlers and preschoolers with autism spectrum disorder (ASD). We investigated the relationship between language (verbal ability, verbal self-talk) and visuospatial working memory in 2- and 4-year-olds with ASD (n = 65) and typical development (TD) (n = 54). Children with ASD displayed…

Peer assessment can be a more effective pedagogical method when reviewers provide quality feedback. But what makes feedback helpful to reviewees? Other studies have identified quality feedback as focusing on detecting problems, providing suggestions, or pointing out where changes need to be made. However, it is important to seek students'…

Evidence from fMRI research indicates that individual creative thinking ability -- defined as performance on divergent thinking tasks, subjectively assessed by human raters -- can be predicted based on the strength of functional connectivity (FC) between the brain's default mode network (DMN) and frontoparietal control network (FPCN). Here, we…

Using eye-tracking, we examined whether overspecification hinders or facilitates referent selection and the extent to which this depends on the properties of the attribute mentioned in the referring expressions and the underpinning processing mode. Following spoken instructions, participants selected the referent in a visual display while their…

Automated Essay Scoring (AES) using neural networks has helped increase the accuracy and efficiency of scoring students' written tasks. Generally, the improved accuracy of neural network approaches has been attributed to the use of modern word embedding techniques. However, which word embedding techniques produce higher accuracy in AES systems…

The present study uses event-related potentials (ERPs) to examine nonlocal agreement processing between native (L1) English speakers and Chinese-English second language (L2) learners, whose L1 lacks number agreement. We manipulated number marking with determiners ("the" vs. "that"/"these") to see how…

An investigation is presented through the processing of natural language and text analysis found in the abstracts of the educational publication Profundidad of the Faculty of Administrative and Economic Sciences at the Universidad Francisco de Paula Santander Ocaña. The indicators analysed are magnitude, year of publication, importance weighting…

What is the processing cost of being garden-pathed by a temporary syntactic ambiguity? We argue that comparing average reading times in garden-path versus non-garden-path sentences is not enough to answer this question. Trial-level contaminants such as inattention, the fact that garden pathing may occur non-deterministically in the ambiguous…

Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…

This article presents a brief overview of the state-of-the-art in large language models (LLMs) like ChatGPT and discusses the difficulties that these technologies create for educators with regard to assessment. Making use of the 'arms race' metaphor, this article argues that there are no simple solutions to the 'AI problem'. Rather, this author…

Artificial intelligence-driven Chatbots, especially large language models (LLMs) like GPT-4, represent significant progress in digital education. These models excel in mimicking human-like text and transforming learning and teaching methods. This study examines the development, application, and impact of LLMs in education. It highlights their role…