Academic reading, a cornerstone of postgraduate education, often presents challenges, particularly for non-native English speakers. These include complex texts, extensive vocabulary, and integrating diverse sources. This study investigates the potential of ChatGPT as an academic reading tool for postgraduate students, emphasizing its usability,…

Purpose: Technology, such as artificial intelligence (AI), is transforming the way we work; however, it is yet to systemically transform learning at the workplace beyond augmentation of formal education's learning processes. This paper derives functional requirements for technologies that support workplace learning and assesses the suitability and…

Background: Large language models (LLMs) are increasingly deployed in educational contexts for content generation (Diwan et al., 2023), assessment (Ouyang et al., 2023), and tutoring support (Lin et al., 2023). Reasoning models represent an important development in LLM development (DeepSeek-AI et al., 2025; OpenAI et al., 2024), distinctively…

Analyzing the teaching and learning environment (TLE) through student feedback is essential for identifying curricular gaps and improving teaching practices. However, traditional feedback analysis methods, particularly for qualitative data, are often time-consuming and prone to human bias. Large Language Models (LLMs) offer a promising solution by…

Despite the increasing interest in artificial intelligence technologies in education, there is a gap in understanding the factors influencing the adoption of ChatGPT among Nigerian higher education students. Research has not comprehensively explored these factors in the Nigerian context, leaving a significant gap in understanding technology…

Recent meta-analyses indicate that learning with ChatGPT improves academic performance but reveals substantial heterogeneity in effect sizes. The present study sheds light on one theoretically plausible moderator of the benefits of learning with ChatGPT: the goal structure of the learning task. For this purpose, in an experiment, university…

How can we measure the resource mobilization (RM) efforts of social movements on Twitter? In this article, we create the first ever measure of social movements' RM efforts on a social media platform. To this aim, we create a four-conditional lexicon that can parse through tweets and identify those concerned with RM. We also create a simple RM…

This study explores the capability of academic staff assisted by the Turnitin Artificial Intelligence (AI) detection tool to identify the use of AI-generated content in university assessments. 22 different experimental submissions were produced using Open AI's ChatGPT tool, with prompting techniques used to reduce the likelihood of AI detectors…

In recent years, converging evidence has suggested that prediction plays a role in language comprehension, as it appears to do in information processing in a range of cognitive domains. Much of the evidence for this comes from the N400, a neural index of the processing of meaningful stimuli which has been argued to index the extent to which a word…

Purpose: A relevant aspect of listening is the effort required during speech processing, which can be assessed by pupillometry. Here, we assessed the pupil dilation response of normal-hearing (NH) and hard of hearing (HH) individuals during listening to clear sentences and masked or degraded sentences. We combined this assessment with functional…

The rise of Artificial Intelligence technology has raised concerns about the potential compromise of privacy due to the handling of personal data. Private AI prevents cybercrimes and falsehoods and protects human freedom and trust. While Federated Learning offers a solution by model training across decentralized devices or servers, thereby…

While a large body of work in sentence comprehension has explored how different types of linguistic information are used to guide syntactic parsing, less is known about the effect of discourse structure. This study investigates this question, focusing on the main and subordinate discourse contrast manifested in the distinction between restrictive…

Reading morphologically complex words requires analysis of their morphemic subunits (e.g., play + er); however, the positional constraints of morphemic processing are still little understood. The current study involved three unprimed lexical decision experiments to directly compare the positional encoding of stems and affixes during reading and to…

Recent investigations on how people derive meaning from language have focused on task-dependent shifts between two cognitive systems. The symbolic (amodal) system represents meaning as the statistical relationships between words. The embodied (modal) system represents meaning through neurocognitive simulation of perceptual or sensorimotor systems…

This study evaluates the ability of large language models (LLMs) to deliver criterion-based grading and examines the impact of prompt engineering with detailed criteria on grading. Using well-established human benchmarks and quantitative analyses, we found that even free LLMs achieve criterion-based grading with a detailed understanding of the…