Theoretical phonology has at its heart the assumption of two separate levels of speech sound representations: one less abstract, phonetic, 'surface' level, and one more abstract, phonological, 'underlying' level. Descriptions of phonological neutralisation processes such as German final devoicing hinge on the mappings between these two levels, as…

To build an Artificial Intelligence system that can assist us in daily lives, the ability to understand the world around us through visual input is essential. Prior studies train visual perception models by defining concept vocabularies and annotate data against the fixed vocabulary. It is hard to define a comprehensive set of everything, and thus…

To learn the meaning of a new word, or to recognize the meaning of a known one, both children and adults benefit from surrounding words, or the sentential context. Most of the evidence from children is based on their accuracy and efficiency when listening to speech in their familiar native accent: they successfully use the words they know to…

Recent studies reported a differential multisensory integration (MSI) in autism spectrum disorder (ASD). Much of the research on MSI differences has focused on how visual stimuli influence speech processing. The present study takes a reverse perspective. We investigated if speech processing can affect the construction of low-level visual…

Generative artificial intelligence (GenAI) models, such as ChatGPT, Gemini, and BingAI, have become integral to educational sciences, bringing about significant transformations in the education system and the processes of knowledge production. These advancements have facilitated new methods of teaching, learning, and information dissemination.…

In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…

The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…

The ethics surrounding the development and deployment of generative artificial intelligence (genAI) is an important topic as institutions of higher education adopt the technology for educational purposes. Concurrently, stakeholders from various organizations have reviewed the literature about the ethics of genAI and proposed frameworks about it.…

This systematic review, conducted in accordance with PRISMA (2020) guidelines, analysed the consequences of gender stereotypes on language processing from 2012 to 2023. This review investigates the impact of stereotypical beliefs on the interpretation and understanding of language, including words, phrases, discourse, perceptions of professional…

The advancement of large language model-based generative artificial intelligence (LLM-based GenAI) has sparked significant interest in its potential to address challenges in computational thinking (CT) education. CT, a critical problem-solving approach in the digital age, encompasses elements such as abstraction, iteration, and generalisation.…

Most, if not all, journals require the use of Large Language Models (LLMs), such as ChatGPT, to be acknowledged. This article argues that current guidelines do not go far enough as the use of an LLM may be acknowledged but the reviewers, and future readers, do not know which parts of the article were generated with AI (Artificial Intelligence)…

The growing demand for microcredentials in education and workforce development necessitates scalable, accurate, and fair assessment systems for both soft and hard skills based on students' lived experience narratives. Existing approaches struggle with the complexities of hierarchical credentialing and the mitigation of algorithmic bias related to…

Combining adjective meaning with the modified noun is particularly challenging for children under three years. Previous research suggests that in processing noun-adjective phrases children may over-rely on noun information, delaying or omitting adjective interpretation. However, the question of whether this difficulty is modulated by semantic…

This study aims to analyze the bibliometric trends of research articles on applying Artificial Intelligence (AI) technology in individuals with Autism Spectrum Disorder (ASD). Within the scope of this study, bibliometric data from 1345 articles published in the Web of Science database between 2014 and 2024 were examined. The analysis revealed a…

Numerous developmental findings suggest that infants and toddlers engage predictive processing during language comprehension. However, a significant limitation of this research is that associative (bottom-up) and predictive (top-down) explanations are not readily differentiated. Following adult studies that varied predictiveness relative to…