Breaking down complex words into smaller meaningful units (e.g., "unhappy = un- + happy"), known as morphemes, is vital for skilled reading as it allows readers to rapidly compute word meanings. There is agreement that children rely on reading experience to acquire morphological knowledge in English; however, the nature of this…

The ever-changing global educational landscape, coupled with the advancement of Web3, is seeing rapid changes in the ways pedagogical artificially intelligent conversational agents are being developed and used to advance teaching and learning in higher education. Given the rapidly evolving research landscape, there is a need to establish what the…

The formation of autism advocacy organisations led by family members of autistic individuals led to intense criticism from some parts of the autistic community. In response to what was perceived as a misrepresentation of their interests, autistic individuals formed autistic self-advocacy groups, adopting the philosophy that autism advocacy should…

Maloof & Associates (M&A), a well-regarded small auditing and accounting firm in Atlanta, kept a close eye on the media buzz surrounding ChatGPT. The partners knew that they must make decisions soon regarding the new technology, but they did not realize how soon until they lost a long-standing and substantial client to a rival that had…

Purpose: Neurotypical individuals show a robust "global precedence effect (GPE)" when processing hierarchically structured visual information. However, the auditory domain remains understudied. The current research serves to fill the knowledge gap on auditory global-local processing across the broader autism phenotype under the tonal…

Purpose: Children with hearing loss (CHL) who use hearing devices (cochlear implants or hearing aids) and communicate orally have trouble comprehending sentences with noncanonical order. This study explores sentence comprehension strategies in Spanish-speaking CHL, focusing on their ability to integrate morphosyntactic cues (word order,…

Background: Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has…

Students with autism spectrum disorder (ASD) are included in the general education classroom more often than ever before. Despite mathematical strengths and early success, these students experience poor outcomes (academic and employment) compared to their typically developing peers. The language of mathematics increases in complexity, use, and…

Large language models are increasingly used in educational and psychological measurement activities. Their rapidly evolving sophistication and ability to detect language semantics make them viable tools to supplement subject matter experts and their reviews of large amounts of text statements, such as educational content standards. This paper…

GPT-based models have enabled the creation of natural language chatbots that support both Inquiry-Based and Structured Learning approaches. This study offers a direct comparison of these two paradigms within a UNIX Shell scripting course by means of two chatbots: a Lesson Plan-Driven chatbot that ensures all students cover the same topics…

Purpose: The notion of using a generative artificial intelligence (AI) engine for text composition has gained excessive popularity among students, educators and researchers, following the introduction of ChatGPT. However, this has added another dimension to the daunting task of verifying originality in academic writing. Consequently, the market…

This study explores the impact of ChatGPT, an advanced Large Language Model (LLM), as a virtual tutor in online education across five key dimensions: answering questions, writing assistance, study resources, exam preparation, and availability. Utilizing an experimental design, 68 undergraduate students from a public university interacted with…

Generative AI (GenAI) is quickly becoming a valuable tool for sociological research. Already, sociologists employ GenAI for tasks like classifying text and simulating human agents. We point to another major use case: the extraction of structured information from unstructured text. Information Extraction (IE) is an established branch of Natural…

We investigated methods to enhance the generalizability of large language models (LLMs) designed to classify dimensions of collaborative discourse during small group work. Our research utilized five diverse datasets that spanned various grade levels, demographic groups, collaboration settings, and curriculum units. We explored different model…

Deep learning models for text classification have been increasingly used in intelligent tutoring systems and educational writing assistants. However, the scarcity of data in many educational settings, as well as certain imbalances in counts among the annotated labels of educational datasets, limits the generalizability and expressiveness of…