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Hinano Iida; Kimi Akita – Cognitive Science, 2024
Iconicity is a relationship of resemblance between the form and meaning of a sign. Compelling evidence from diverse areas of the cognitive sciences suggests that iconicity plays a pivotal role in the processing, memory, learning, and evolution of both spoken and signed language, indicating that iconicity is a general property of language. However,…
Descriptors: Japanese, Cognitive Science, Language Processing, Memory
Clinton Chidiebere Anyanwu; Pauline Ndidi Ononiwu; Grace Ngozi Isiozor – Education and Information Technologies, 2024
In contemporary society, information and communication technology permeates every aspect of human life, including education. This study investigates the impact of WhatsApp chatbot technology and Glaser's teaching approaches on the academic performance of economics education students in tertiary institutions. Grounded in activity theory, the study…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Teaching Methods
Fábio Albuquerque; Paula Gomes Dos Santos – Cogent Education, 2024
Using a quasi-experimental method and content analysis as a technique, this study tests ChatGPT, in its version 4, by assessing its textual characteristics and overall understanding regarding the recognition criteria of provisions under International Accounting Standards (IAS) 37, as issued by the International Accounting Standards Board (IASB).…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Accounting
Jeya Amantha Kumar; Min Zhuang; Stephen Thomas – Natural Sciences Education, 2024
Chat Generative Pre-Trained Transformer (ChatGPT) has emerged as a powerful artificial intelligence (AI) tool with an aptitude to transform course design in higher education significantly. While ChatGPT's applications in education are substantially growing, its role in natural sciences, particularly in course planning and content generation among…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Natural Sciences
Maki Kubota; Jorge González Alonso; Merete Anderssen; Isabel Nadine Jensen; Alicia Luque; Sergio Miguel Pereira Soares; Yanina Prystauka; Øystein A. Vangsnes; Jade Jørgen Sandstedt; Jason Rothman – Language Learning, 2024
The current study investigated gender (control) and number (target) agreement processing in Northern and non-Northern Norwegians living in Northern Norway. Participants varied in exposure to Northern Norwegian (NN) dialect(s), where number marking differs from most other Norwegian dialects. In a comprehension task involving reading NN dialect…
Descriptors: Norwegian, Dialects, Grammar, Language Processing
David Baidoo-Anu; Daniel Asamoah; Isaac Amoako; Inuusah Mahama – Discover Education, 2024
This study examined the perspectives of Ghanaian higher education students on the use of ChatGPT. The Students' ChatGPT Experiences Scale (SCES) was developed and validated to evaluate students' perspectives of ChatGPT as a learning tool. A total of 277 students from universities and colleges participated in the study. Through exploratory factor…
Descriptors: Student Attitudes, Artificial Intelligence, Higher Education, Foreign Countries
Du Gan; Kanokporn Numtong; Hao Li; Songyu Jiang – Eurasian Journal of Applied Linguistics, 2024
This study applies the Apriori algorithm to analyse patterns, syntactic structures, and thematic clusters in Chinese studies data from various genres. This study aims to identify recurring linguistic elements in order to shed light on the dynamic nature of the Chinese language across different contexts and time periods. The Apriori algorithm is…
Descriptors: Chinese, Applied Linguistics, Algorithms, Computational Linguistics
David R. Firth; Mason Derendinger; Jason Triche – Information Systems Education Journal, 2024
In this paper we describe a framework for teaching students when they should, or should not use generative AI such as ChatGPT. Generative AI has created a fundamental shift in how students can complete their class assignments, and other tasks such as building resumes and creating cover letters, and we believe it is imperative that we teach…
Descriptors: Cheating, Artificial Intelligence, Man Machine Systems, Natural Language Processing
Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
Matthew Landers – Higher Education for the Future, 2025
This article presents a brief overview of the state-of-the-art in large language models (LLMs) like ChatGPT and discusses the difficulties that these technologies create for educators with regard to assessment. Making use of the 'arms race' metaphor, this article argues that there are no simple solutions to the 'AI problem'. Rather, this author…
Descriptors: Ethics, Cheating, Plagiarism, Artificial Intelligence
Sghaier Guizani; Tehseen Mazhar; Tariq Shahzad; Wasim Ahmad; Afsha Bibi; Habib Hamam – Discover Education, 2025
Artificial intelligence-driven Chatbots, especially large language models (LLMs) like GPT-4, represent significant progress in digital education. These models excel in mimicking human-like text and transforming learning and teaching methods. This study examines the development, application, and impact of LLMs in education. It highlights their role…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
Evelien Mulder; Marco van de Ven; Eliane Segers; Alexander Krepel; Elise H. de Bree; Peter F. de Jong; Ludo Verhoeven – Journal of Research in Reading, 2024
Background: Word-to-text integration (WTI) can be challenging for second-language (L2) learners, although it can positively contribute to reading comprehension. The present study examined the role of WTI, after controlling for decoding, vocabulary and morphosyntactic awareness, in predicting English as an L2 reading comprehension development in…
Descriptors: Reading Comprehension, English (Second Language), Second Language Learning, Semantics
Sungbong Bae; Hye K. Pae; Kwangoh Yi – Reading and Writing: An Interdisciplinary Journal, 2024
While the theoretical models of morphological processing in Roman alphabets indicate prelexical activation, a model established in Korean suggests postlexical activation. To extend the model of Korean morphological processing, this study examined within-scriptal (Hangul-Hangul prime-target pairs) and cross-scriptal (Hanja-Hangul prime-target…
Descriptors: Korean, Word Recognition, Morphology (Languages), Written Language
Jiayu Liu; Junjuan Gu; Chen Feng; Weiting Shi; Chris Biemann; Xingshan Li – Scientific Studies of Reading, 2024
Purpose: This study was designed to distinguish the degree of sharing of representations between different modalities by investigating whether a word encountering experience in one modality impacts word processing in another modality. Method: In three experiments, participants experienced some words frequently in the auditory modality (Experiment…
Descriptors: Foreign Countries, Learning Modalities, Chinese, Form Classes (Languages)
Debby R. E. Cotton; Peter A. Cotton; J. Reuben Shipway – Innovations in Education and Teaching International, 2024
The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of…
Descriptors: Integrity, Cheating, Artificial Intelligence, Man Machine Systems