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Abdullah Al-Abri – Education and Information Technologies, 2025
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…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Intelligent Tutoring Systems
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Oscar Stuhler; Cat Dang Ton; Etienne Ollion – Sociological Methods & Research, 2025
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…
Descriptors: Artificial Intelligence, Sociology, Social Science Research, Natural Language Processing
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Chelsea Chandler; Rohit Raju; Jason G. Reitman; William R. Penuel; Monica Ko; Jeffrey B. Bush; Quentin Biddy; Sidney K. D’Mello – International Educational Data Mining Society, 2025
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…
Descriptors: Artificial Intelligence, Models, Natural Language Processing, Discourse Analysis
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Seyed Parsa Neshaei; Richard Lee Davis; Paola Mejia-Domenzain; Tanya Nazaretsky; Tanja Käser – International Educational Data Mining Society, 2025
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…
Descriptors: Artificial Intelligence, Classification, Natural Language Processing, Technology Uses in Education
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Afza Diyana Abdullah; Xiaoting Qiu; Huan Li; Muhammad Kamarul Kabilan – Reading Research Quarterly, 2025
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,…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Graduate Students
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Valentine Joseph Owan; Ibrahim Abba Mohammed; Ahmed Bello; Tajudeen Ahmed Shittu – Contemporary Educational Technology, 2025
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…
Descriptors: Student Behavior, Foreign Countries, Artificial Intelligence, Natural Language Processing
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Amir Abdul Reda; Semuhi Sinanoglu; Mohamed Abdalla – Sociological Methods & Research, 2024
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…
Descriptors: Social Media, Social Action, Natural Language Processing, Politics
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Mike Perkins; Jasper Roe; Darius Postma; James McGaughran; Don Hickerson – Journal of Academic Ethics, 2024
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…
Descriptors: Artificial Intelligence, Student Evaluation, Identification, Natural Language Processing
James A. Michaelov – ProQuest LLC, 2024
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…
Descriptors: Prediction, Language Processing, Brain Hemisphere Functions, Linguistic Input
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Adriana A. Zekveld; Sophia E. Kramer; Dirk J. Heslenfeld; Niek J. Versfeld; Chris Vriend – Journal of Speech, Language, and Hearing Research, 2024
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…
Descriptors: Foreign Countries, Motor Reactions, Hearing Impairments, Speech Communication
Mengjiao Zhang – ProQuest LLC, 2024
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…
Descriptors: Privacy, Cooperative Learning, Natural Language Processing, Learning Processes
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Sanghee J. Kim; Ming Xiang – Cognitive Science, 2024
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…
Descriptors: Language Processing, Discourse Analysis, Phrase Structure, Syntax
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Jasmine Spencer; Hasibe Kahraman; Elisabeth Beyersmann – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
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…
Descriptors: Morphemes, Suffixes, Word Recognition, College Students
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John Hollander; Andrew Olney – Cognitive Science, 2024
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…
Descriptors: Verbs, Symbolic Language, Language Processing, Semantics
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Da-Wei Zhang; Melissa Boey; Yan Yu Tan; Alexis Hoh Sheng Jia – npj Science of Learning, 2024
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…
Descriptors: Artificial Intelligence, Natural Language Processing, Criterion Referenced Tests, Grading
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