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Chao Sun; Ye Tian; Richard Breheny – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
The phenomenon of scalar diversity refers to the well-replicated finding that different scalar expressions give rise to scalar implicatures (SIs) at different rates. Previous work has shown that part of the scalar diversity effect can be explained by theoretically motivated factors. Although the effect has been established only in controlled…
Descriptors: Pragmatics, Language Usage, Social Media, Form Classes (Languages)
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Teo Susnjak – International Journal of Artificial Intelligence in Education, 2024
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…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, At Risk Students
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Seamus Donnelly; Caroline Rowland; Franklin Chang; Evan Kidd – Cognitive Science, 2024
Prediction-based accounts of language acquisition have the potential to explain several different effects in child language acquisition and adult language processing. However, evidence regarding the developmental predictions of such accounts is mixed. Here, we consider several predictions of these accounts in two large-scale developmental studies…
Descriptors: Prediction, Error Patterns, Syntax, Priming
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Yanjun Liu; Feng Xiao – Journal of Psycholinguistic Research, 2024
Previous studies on L2 (i.e., second language) Chinese compound processing have focused on the relative efficiency of two routes: holistic processing versus combinatorial processing. However, it is still unclear whether Chinese compounds are processed with multilevel representations among L2 learners due to the hierarchical structure of the…
Descriptors: Bilingualism, Chinese, Orthographic Symbols, Phonological Awareness
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Albornoz-De Luise, Romina Soledad; Arevalillo-Herraez, Miguel; Arnau, David – IEEE Transactions on Learning Technologies, 2023
In this article, we analyze the potential of conversational frameworks to support the adaptation of existing tutoring systems to a natural language form of interaction. We have based our research on a pilot study, in which the open-source machine learning framework Rasa has been used to build a conversational agent that interacts with an existing…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Artificial Intelligence, Models
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Shin, Gyu-Ho; Mun, Seongmin – Developmental Science, 2023
This study investigates how neural networks address the properties of children's linguistic knowledge, with a focus on the "Agent-First" strategy in comprehension of an active transitive construction in Korean. We develop various neural-network models and measure their classification performance on the test stimuli used in a behavioural…
Descriptors: Brain, Child Language, Korean, Comprehension
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Jiang, Yu-Er; Liao, Xiao-Yu; Liu, Na – International Journal of Language & Communication Disorders, 2023
Background: Patients with anomic aphasia experience difficulties in narrative processing. General discourse measures are time consuming and require necessary skills. Core lexicon analysis has been proposed as an effort-saving approach but has not been developed in Mandarin discourse. Aims: This exploratory study was aimed (1) to apply core lexicon…
Descriptors: Aphasia, Narration, Language Processing, Mandarin Chinese
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Ted M. Clark – Journal of Chemical Education, 2023
The artificial intelligence chatbot ChatGPT was used to answer questions from final exams administered in two general chemistry courses, including questions with closed-response format and with open-response format. For closed-response questions, ChatGPT was very capable at identifying the concept even when the question included a great deal of…
Descriptors: Artificial Intelligence, Science Tests, Chemistry, Science Instruction
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Gani, Mohammed Osman; Ayyasamy, Ramesh Kumar; Sangodiah, Anbuselvan; Fui, Yong Tien – Education and Information Technologies, 2023
The automated classification of examination questions based on Bloom's Taxonomy (BT) aims to assist the question setters so that high-quality question papers are produced. Most studies to automate this process adopted the machine learning approach, and only a few utilised the deep learning approach. The pre-trained contextual and non-contextual…
Descriptors: Models, Artificial Intelligence, Natural Language Processing, Writing (Composition)
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Gerald Gartlehner; Leila Kahwati; Rainer Hilscher; Ian Thomas; Shannon Kugley; Karen Crotty; Meera Viswanathan; Barbara Nussbaumer-Streit; Graham Booth; Nathaniel Erskine; Amanda Konet; Robert Chew – Research Synthesis Methods, 2024
Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…
Descriptors: Data Collection, Evidence, Synthesis, Language Processing
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Ishanti Gangopadhyay; Daniel Fulford; Kathleen Corriveau; Jessica Mow; Pearl Han Li; Sudha Arunachalam – Cognitive Science, 2024
Understanding cognitive effort expended during assessments is essential to improving efficiency, accuracy, and accessibility within these assessments. Pupil dilation is commonly used as a psychophysiological measure of cognitive effort, yet research on its relationship with effort expended specifically during language processing is limited. The…
Descriptors: Vocabulary, Difficulty Level, Motor Reactions, Cognitive Ability
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Hei-Chia Wang; Yu-Hung Chiang; I-Fan Chen – Education and Information Technologies, 2024
Assessment is viewed as an important means to understand learners' performance in the learning process. A good assessment method is based on high-quality examination questions. However, generating high-quality examination questions manually by teachers is a time-consuming task, and it is not easy for students to obtain question banks. To solve…
Descriptors: Natural Language Processing, Test Construction, Test Items, Models
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Anke Grotlüschen; Gregor Dutz; Kristin Skowranek – International Journal of Lifelong Education, 2024
The International Literacy Day 2023 was the first after the launch the text generating artificial intelligence ChatGPT. This was the reason for a Literacy Promptathon that allows users to learn how to handle text and image generation. The International Literacy Day media coverage for the first time touched on the question of AI generated text. One…
Descriptors: Artificial Intelligence, Natural Language Processing, Critical Literacy, Misinformation
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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
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