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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
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
Shraddha Govind Barke – ProQuest LLC, 2024
The dream of intelligent assistants to enhance programmer productivity has now become a concrete reality, with rapid advances in artificial intelligence. Large language models (LLMs) have demonstrated impressive capabilities in various domains based on the vast amount of data used to train them. However, tasks which require structured reasoning or…
Descriptors: Artificial Intelligence, Symbolic Learning, Programming, Programming Languages
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)
Zhao Wanli; Tang Youjun; Ma Xiaomei – SAGE Open, 2025
Deeper learning (DL) is firmly rooted in learning science and computer science. However, a dearth of review studies has probed its trajectory in DL in foreign languages (DLFL). Utilizing SSCI from the Web of Science Core Collection, we employ Citespace and Vosviewer to analyze the scientific knowledge graph of DLFL literature. Our analysis…
Descriptors: Bibliometrics, Second Language Learning, Computer Science, Educational Research
Sarah K. Cox; Elizabeth Hughes – School Science and Mathematics, 2025
Students with autism spectrum disorder (ASD) are included in the general education classroom more often than ever before. Despite mathematical strengths and early success, these students experience poor outcomes (academic and employment) compared to their typically developing peers. The language of mathematics increases in complexity, use, and…
Descriptors: Students with Disabilities, Autism Spectrum Disorders, Inclusion, Mathematics Instruction
Reese Butterfuss; Harold Doran – Educational Measurement: Issues and Practice, 2025
Large language models are increasingly used in educational and psychological measurement activities. Their rapidly evolving sophistication and ability to detect language semantics make them viable tools to supplement subject matter experts and their reviews of large amounts of text statements, such as educational content standards. This paper…
Descriptors: Alignment (Education), Academic Standards, Content Analysis, Concept Mapping