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Drisko, James W. – Journal of Social Work Education, 2023
Plagiarism is a continuing and growing concern in higher education and in academic publishing. Educating to avoid plagiarism requires ongoing efforts at all levels and clear policies that explain the several types of plagiarism and potential consequences when it is found. Identifying plagiarism requires complex judgments and is not a simple matter…
Descriptors: Plagiarism, Computer Software, Identification, Computational Linguistics
Jack B. Joyce; Tom Douglass; Bethan Benwell; Catrin S. Rhys; Ruth Parry; Richard Simmons; Adrian Kerrison – International Journal of Social Research Methodology, 2023
Over the last 30 years, there has been substantial debate about the practical, ethical and epistemological issues uniquely associated with qualitative data sharing. In this paper, we contribute to these debates by examining established data sharing practices in Conversation Analysis (CA). CA is an approach to the analysis of social interaction…
Descriptors: Ethics, Epistemology, Discourse Analysis, Research Methodology
Sadler-Smith, Eugene; Akstinaite, Vita – Journal of Creative Behavior, 2022
Insight and intuition are important concepts in creativity research and creative behavior with applications in a wide variety of professional and business domains. Understanding and articulating their similarities and differences is important theoretically and practically. Researchers and practitioners can benefit from the application of new…
Descriptors: Identification, Intuition, Discourse Analysis, Computational Linguistics
Pablo E. Requena – Language Learning and Development, 2024
The well-known sampling limitation of most longitudinal corpus data can be even more consequential in the study of morphosyntactic variation in child language. An analysis of caregiver input suggests that variable use in overlapping contexts may be hard to find by solely relying on corpus data collected under the sampling procedures that are…
Descriptors: Morphology (Languages), Syntax, Language Acquisition, Language Variation
Cheng-Yu Hsieh; Marco Marelli; Kathleen Rastle – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
Most printed Chinese words are compounds built from the combination of meaningful characters. Yet, there is a poor understanding of how individual characters contribute to the recognition of compounds. Using a megastudy of Chinese word recognition (Tse et al., 2017), we examined how the lexical decision of existing and novel Chinese compounds was…
Descriptors: Semantics, Orthographic Symbols, Chinese, Reading Processes
Adrian Kirwan – Irish Educational Studies, 2024
Since its arrival in late 2022, ChatGPT has occupied the minds of academics, administrators and students. Reactions to the emergence of Large Language Models (LLMs) have varied but significant anxieties about their impact on assessment have arisen. To address these concerns, this article serves three purposes; firstly, it seeks to gauge the…
Descriptors: Integrity, Computational Linguistics, Artificial Intelligence, Technology Uses in Education
Jimmy Tobin; Phillip Nelson; Bob MacDonald; Rus Heywood; Richard Cave; Katie Seaver; Antoine Desjardins; Pan-Pan Jiang; Jordan R. Green – Journal of Speech, Language, and Hearing Research, 2024
Purpose: This study examines the effectiveness of automatic speech recognition (ASR) for individuals with speech disorders, addressing the gap in performance between read and conversational ASR. We analyze the factors influencing this disparity and the effect of speech mode--specific training on ASR accuracy. Method: Recordings of read and…
Descriptors: Foreign Countries, Speech Impairments, Computational Linguistics, Artificial Intelligence
Towards Automatic Question Generation Using Pre-Trained Model in Academic Field for Bahasa Indonesia
Derwin Suhartono; Muhammad Rizki Nur Majiid; Renaldy Fredyan – Education and Information Technologies, 2024
Exam evaluations are essential to assessing students' knowledge and progress in a subject or course. To meet learning objectives and assess student performance, questions must be themed. Automatic Question Generation (AQG) is our novel approach to this problem. A comprehensive process for autonomously generating Bahasa Indonesia text questions is…
Descriptors: Foreign Countries, Computational Linguistics, Computer Software, Questioning Techniques
Samer A. Nour Eddine – ProQuest LLC, 2024
In this thesis, I use a combination of simulations and empirical data to demonstrate that a small set of structural and functional principles - the basic tenets of predictive coding theory - succinctly accounts for a very wide range of properties in the language processing system. Predictive coding approximates hierarchical Bayesian inference via…
Descriptors: Semantics, Simulation, Psycholinguistics, Bayesian Statistics
Dadi Ramesh; Suresh Kumar Sanampudi – European Journal of Education, 2024
Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…
Descriptors: Scoring, Essays, Writing Evaluation, Memory
Videep Venkatesha; Abhijnan Nath; Ibrahim Khebour; Avyakta Chelle; Mariah Bradford; Jingxuan Tu; James Pustejovsky; Nathaniel Blanchard; Nikhil Krishnaswamy – International Educational Data Mining Society, 2024
In the realm of collaborative learning, extracting the beliefs shared within a group is paramount, especially when navigating complex tasks. Inherent in this problem is the fact that in naturalistic collaborative discourse, the same propositions may be expressed in radically different ways. This difficulty is exacerbated when speech overlaps and…
Descriptors: Cooperative Learning, Dialogs (Language), Language Usage, Artificial Intelligence
Frank, Stefan L. – Language Learning, 2021
Although computational models can simulate aspects of human sentence processing, research on this topic has remained almost exclusively limited to the single language case. The current review presents an overview of the state of the art in computational cognitive models of sentence processing, and discusses how recent sentence-processing models…
Descriptors: Multilingualism, Language Processing, Computational Linguistics, Psycholinguistics
Siqi Yi; Soo Young Rieh – Information and Learning Sciences, 2025
Purpose: This paper aims to critically review the intersection of searching and learning among children in the context of voice-based conversational agents (VCAs). This study presents the opportunities and challenges around reconfiguring current VCAs for children to facilitate human learning, generate diverse data to empower VCAs, and assess…
Descriptors: Literature Reviews, Children, Childrens Attitudes, Artificial Intelligence
Andreea Dutulescu; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2025
The assessment of student responses to learning-strategy prompts, such as self-explanation, summarization, and paraphrasing, is essential for evaluating cognitive engagement and comprehension. However, manual scoring is resource-intensive, limiting its scalability in educational settings. This study investigates the use of Large Language Models…
Descriptors: Scoring, Computational Linguistics, Computer Software, Artificial Intelligence
Andreea Dutulescu; Stefan Ruseti; Mihai Dascalu; Danielle McNamara – International Educational Data Mining Society, 2025
The assessment of student responses to learning-strategy prompts, such as self-explanation, summarization, and paraphrasing, is essential for evaluating cognitive engagement and comprehension. However, manual scoring is resource-intensive, limiting its scalability in educational settings. This study investigates the use of Large Language Models…
Descriptors: Scoring, Computational Linguistics, Computer Software, Artificial Intelligence

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