Computational models of infant word-finding typically operate over transcriptions of infant-directed speech corpora. It is now possible to test models of word segmentation on speech materials, rather than transcriptions of speech. We propose that such modeling efforts be conducted over the speech of the experimental stimuli used in studies…

A significant body of recent research in the field of Learning Analytics has focused on leveraging machine learning approaches for predicting at-risk students in order to initiate timely interventions and thereby elevate retention and completion rates. The overarching feature of the majority of these research studies has been on the science of…

Recent years have seen increased interests in applying the latest technological innovations, including artificial intelligence (AI) and machine learning (ML), to the field of education. One of the main areas of interest to researchers is the use of ML to assist teachers in assessing students' work on the one hand and to promote effective…

This study investigates the use of Large Language Models (LLMs) by undergraduates majoring in Instrumentation and Control Engineering (ICE) at University of Shanghai for Science and Technology. We conducted a questionnaire survey to assess the awareness and usage habits of these LLMs among ICE undergraduates in ICE courses, focusing on the model…

Over the past decade, social scientists have adapted computational methods for qualitative text analysis, with the hope that they can match the accuracy and reliability of hand coding. The emergence of GPT and open-source generative large language models (LLMs) has transformed this process by shifting from programming to engaging with models using…

This paper presents a thematic review of the anti-plagiarism instruction of content specialists as reported in a range of articles published in the decade of 2014-2023. A total of 28 articles were identified through systematic searching and a ChatGPT-assisted selection process based on a set of inclusion criteria. Specifically, we aimed to include…

The emergence of ChatGPT, and other generative AI (GenAI) tools, has elicited dystopian and utopian proclamations concerning their potential impact on education. This paper suggests that responses to GenAI are based on often-implicit perceptions of naturalness and artificiality. To examine the depiction and function of these concepts, Gideon…

Can metaphorical reasoning involving embodied experience--such as color perception--be learned from the statistics of language alone? Recent work finds that colorblind individuals robustly understand and reason abstractly about color, implying that color associations in everyday language might contribute to the metaphorical understanding of color.…

The aim of this paper is to provide tools to teachers for monitoring student work and understanding practices in order to help student and possibly adapt exercises in the future. In the context of an online programming learning platform, we propose to study the attempts (i.e., submitted programs) of the students for each exercise by using…

Generative AI like ChatGPT is transforming education and research rapidly. This study focuses on ethical considerations surrounding ChatGPT in academic research through a comprehensive bibliometric analysis of 245 research articles published between 2019-2024, collected from the Scopus database. The study uncovers a substantial surge in…

Background: Analyzing student short-answer written justifications to conceptually challenging questions has proven helpful to understand student thinking and improve conceptual understanding. However, qualitative analyses are limited by the burden of analyzing large amounts of text. Purpose: We apply dense and sparse Large Language Models (LLMs)…

Enemy items are two test items that should not be presented to a candidate on the same test. Identifying enemies is essential for personnel assessment, as they weaken the measurement precision and validity of a test. In this research, we examined the effectiveness of lexical and semantic natural language processing techniques for identifying enemy…

Background: People with neurological conditions such as Parkinson's Disease are at risk of speech and voice difficulties that impact volume, clarity of speech and intelligibility. Voice-assisted technology (VAT), such as Alexa, poorly recognises speech difficulties, and this often prompts people to change their speech to enable interaction. Aims:…

Machine learning-based automatic scoring faces challenges with imbalanced student responses across scoring categories. To address this, we introduce a novel text data augmentation framework that leverages GPT-4, a generative large language model specifically tailored for imbalanced datasets in automatic scoring. Our experimental dataset consisted…

This case study examines the development of a proof-of-concept (PoC) generative artificial intelligence (genAI) model inspired by OpenAI's ChatGPT®, implemented within the Office of Research Administration (ORA) at Emory University. Generative artificial intelligence (genAI) refers to AI models capable of producing human-like text. Specifically,…