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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
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
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
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
Szymanik, Jakub; Kochari, Arnold; Bremnes, Heming Strømholt – Cognitive Science, 2023
One approach to understanding how the human cognitive system stores and operates with quantifiers such as "some," "many," and "all" is to investigate their interaction with the cognitive mechanisms for estimating and comparing quantities from perceptual input (i.e., nonsymbolic quantities). While a potential link…
Descriptors: Cognitive Processes, Symbols (Mathematics), Numbers, Mathematical Concepts
Diane Rak – ProQuest LLC, 2023
Ambiguity is a natural part of language and in studying the comprehension and resolution of ambiguity in a second language (L2), we must consider the influence of the native language. This dissertation examines L2 processing of the lexical semantic ambiguities, homonyms and polysemes. These are words that share the same form but have different…
Descriptors: Second Language Learning, Semantics, Ambiguity (Semantics), Language Processing
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
Sofia Fernandez – ProQuest LLC, 2023
This dissertation delves into second language acquisition, sociophonetic variation, and speech perception, investigating how prior linguistic experiences and exposure to regional variations in a second language influence the decoding of dialectal linguistic cues. It aims to enhance the understanding of words pronounced with different phones and…
Descriptors: Second Language Learning, Spanish, Language Styles, Dialects
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
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)
Jacobus Ignatius DeBruyn – ProQuest LLC, 2024
This study explored the role of artificial intelligence (AI)-powered conversational agents in human-computer interaction, particularly in the post-coronavirus (COVID-19) era, where digital technologies are central to healthcare, customer service, and education sectors. The research investigated the disruption of context continuity when users…
Descriptors: Artificial Intelligence, Computer Mediated Communication, Man Machine Systems, Dialogs (Language)
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
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
A Method for Generating Course Test Questions Based on Natural Language Processing and Deep Learning
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
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