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Dadang Sudana; Tri Indri Hardini; Mahardhika Zifana – International Journal of Language Education, 2024
A tension exists between rationalists and empiricists regarding the nature of knowledge: innate then activated/discovered (rationalists) or constructed then invented (empiricists). The assumption is that, to a certain extent, basic knowledge seems to be innate in our mind and develops through experience by thinking processes to construct meanings.…
Descriptors: Indonesian, Verbs, Teaching Methods, Semantics
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
Rodrigo A. Rodríguez-Fuentes; Valentina Concu – PROFILE: Issues in Teachers' Professional Development, 2025
This study examines the application of corpus linguistics in English language teaching (ELT) in Colombia, where its practical adoption remains limited compared to many developed countries. Data were gathered through a survey of English instructors at Colombian universities to assess their familiarity with corpus linguistics. Findings indicate…
Descriptors: Foreign Countries, Language Teachers, English (Second Language), Second Language Instruction
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
Gustavo Simas da Silva; Vânia Ribas Ulbricht – International Association for Development of the Information Society, 2023
ChatGPT and Bard, two chatbots powered by Large Language Models (LLMs), are propelling the educational sector towards a new era of instructional innovation. Within this educational paradigm, the present investigation conducts a comparative analysis of these groundbreaking chatbots, scrutinizing their distinct operational characteristics and…
Descriptors: Comparative Analysis, Teaching Methods, Computer Software, Artificial Intelligence
Rebeckah K. Fussell; Megan Flynn; Anil Damle; Michael F. J. Fox; N. G. Holmes – Physical Review Physics Education Research, 2025
Recent advancements in large language models (LLMs) hold significant promise for improving physics education research that uses machine learning. In this study, we compare the application of various models for conducting a large-scale analysis of written text grounded in a physics education research classification problem: identifying skills in…
Descriptors: Physics, Computational Linguistics, Classification, Laboratory Experiments
Clarence Green; Melania Pantelich; Michael Barrow; Daya Weerasinghe; Rachel Daniel – Australian Review of Applied Linguistics, 2024
There are few published estimates of vocabulary sizes amongst students in tertiary education. Research does not offer estimates of the vocabulary size tertiary students might be expected to possess, though estimates exist for K-12 education, some EFL contexts, and the general population. Such research is important. For reading comprehension during…
Descriptors: Intervention, Undergraduate Students, Vocabulary Development, Teaching Methods
Kaiying Lin – ProQuest LLC, 2024
The field of Linguistics has long been interested in the verb meanings of intransitive verbs and their argument structure, specifically the breakdown of intransitive verbs into unaccusative and unergative verb types. Despite extensive research, a universally applicable explanation for this breakdown remains elusive due in part to the variability…
Descriptors: Mandarin Chinese, Second Language Learning, Second Language Instruction, Semantics
Bitzenbauer, Philipp – Contemporary Educational Technology, 2023
Large language models, such as ChatGPT, have great potential to enhance learning and support teachers, but they must be used with care to tackle limitations and biases. This paper presents two easy-to-implement examples of how ChatGPT can be used in physics classrooms to foster critical thinking skills at the secondary school level. A pilot study…
Descriptors: Physics, Science Instruction, Teaching Methods, Computer Software
Temur, Turan; Sezer, Taner – International Electronic Journal of Elementary Education, 2023
Reading is one of the main skills to be learned and used in schools and through the entire life of an individual. Its crucial importance made reading one of the central topics in different academic disciplines such as education, psychology, linguistic and neuroscience. Advances in multidisciplinary approaches to and studies of reading gave us the…
Descriptors: Reading Teachers, Reading Instruction, Reading Skills, Computational Linguistics
Alberto Giretti; Dilan Durmus; Massimo Vaccarini; Matteo Zambelli; Andrea Guidi; Franco Ripa di Meana – International Association for Development of the Information Society, 2023
This paper provides a possible strategy for integrating large language artificial intelligence models (LLMs) in supporting students' education in artistic or design activities. We outline the methodological foundations concerning the integration of CHATGPT LLM in the educational approach aimed at enhancing artistic conception and design ideation.…
Descriptors: Art Education, Design, Artificial Intelligence, Computer Software
Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
Minkyoung Kim; Lauren Adlof – TechTrends: Linking Research and Practice to Improve Learning, 2024
ChatGPT, an artificial intelligence (AI) language model, holds significant promise for improving the quality and efficiency of teaching and learning. However, its potential challenges and disruptions in education systems require further investigation for a deeper understanding and mitigation. Given that ChatGPT is already being utilized and…
Descriptors: Computer Software, Computational Linguistics, Intelligent Tutoring Systems, Teaching Methods
Carla L. Hudson Kam; Emily Sadlier-Brown; Shannon Clark; Chelsea Jang; Carrie Demmans Epp; Jenny Thomson – First Language, 2024
Many studies have shown that morphological knowledge has effects on reading comprehension separate from other aspects of language knowledge. This has implications for reading instruction and assessment: it suggests that children could have reading comprehension difficulties that are due to a lack of morphological knowledge, and thus, that explicit…
Descriptors: Morphology (Languages), Language Acquisition, Metalinguistics, Accuracy
Gilquin, Gaëtanelle – Language Teaching, 2022
This paper considers the issue of the norm in the context of learner corpus research and its implications for foreign language teaching. It seeks to answer three main questions: Does learner corpus research require a native norm? What corpus-derived norms are available and how do we choose? What do we do with these norms in the classroom? The…
Descriptors: Computational Linguistics, Teaching Methods, Second Language Learning, Second Language Instruction