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)…

Open-text responses provide researchers and educators with rich, nuanced insights that multiple-choice questions cannot capture. When reliably assessed, such responses have the potential to enhance teaching and learning. However, scaling and consistently capturing these nuances remain significant challenges, limiting the widespread use of…

This study examines the effectiveness of artificial intelligence (AI) in psychological report writing by comparing reports generated by human psychologists with those produced by OpenAI's Generative Pre-trained Transformer Version 4 (ChatGPT-4). A total of 249 licensed psychologists evaluated the reports based on overall quality, readability,…

This study investigates the perspectives of 12 journal reviewers from diverse academic disciplines on using large language models (LLMs) in the peer review process. We identified key themes regarding integrating LLMs through qualitative data analysis of verbatim responses to an open-ended questionnaire. Reviewers noted that LLMs can automate tasks…

In this article, we discuss ethical issues related to using and disclosing artificial intelligence (AI) tools, such as ChatGPT and other systems based on large language models (LLMs), to write or edit scholarly manuscripts. Some journals, such as "Science," have banned the use of LLMs because of the ethical problems they raise concerning…

Young children can exploit the syntactic context of a novel word to narrow down its probable meaning. This is "syntactic bootstrapping." A learner that uses syntactic bootstrapping to foster lexical acquisition must first have identified the semantic information that a syntactic context provides. Based on the "semantic seed…

Decades of psycholinguistics research have shown that human sentence processing is highly incremental and predictive. This has provided evidence for expectation-based theories of sentence processing, which posit that the processing difficulty of linguistic material is modulated by its probability in context. However, these theories do not make…

The current study investigated the nuances among Qur'anic near-synonyms and the reflection of such semantic differences in English and French translations. Initially, it aimed to highlight the contextual meanings of the selected sets of Qur'anic near-synonyms in the light of the exegeses of the Holy Qur'an. Moreover, it explicated the nuances…

The present study used a repetition priming paradigm to investigate the basic morphological units stored in mental lexicon for Chinese as second language learners (L2) and Chinese native speakers (L1). Meanwhile, the modulation of Chinese morpheme property (bound or free) in lexical processing was examined. The results revealed that for…

Research examining rule formation and second language (L2) explicit knowledge during guided inductive instruction has focused on co-constructed metalanguage or depth of processing (DoP) using think-aloud protocols, but without analyzing rule features. Studies have not focused on the architecture of the rules that L2 learners create individually.…

Due to the increasing demand for efficient, effective, and profitable applications of Artificial Intelligence (AI) in various industries, there is an immense need for professionals with the right skills to meet this demand. As a result, several institutions have started to offer AI programs. Yet, there is a notable gap in academia: the absence of…

In an Intelligent Tutoring System (ITS), problem (or question) difficulty is one of the most critical parameters, directly impacting problem design, test paper organization, result analysis, and even the fairness guarantee. However, it is very difficult to evaluate the problem difficulty by organized pre-tests or by expertise, because these…

Rapid improvements in the capabilities of machine translation (MT) raise questions about possible increases in overreliance on MT among lower-proficiency or novice level language learners. This study investigated how such learners described their use of online MT for independent reading and writing tasks, and whether this included descriptions…

Providing timely feedback is crucial in promoting academic achievement and student success. However, for multifarious reasons (e.g., limited teaching resources), feedback often arrives too late for learners to act on the feedback and improve learning. Thus, automated feedback systems have emerged to tackle educational tasks in various domains,…

This research aims to address the current gaps in computer-assisted translation (CAT) courses offered in bachelor's and master's programmes in scientific and technical translation (STT). A multi-framework course design methodology is proposed to support CAT teachers from the computer engineering field, improve student engagement, and promote…