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Aaron Stoller; Chris Schacht – Education and Culture, 2024
The emergence of Large Language Models has exposed composition studies' long-standing commitment to Cartesian assumptions that position writing as a nonmaterial, distinctly human activity. This paper develops a naturalized theory of composition grounded in Deweyan pragmatic naturalism that dissolves the nature/culture dualism embedded in…
Descriptors: Writing (Composition), Artificial Intelligence, Natural Language Processing, Writing Processes
Nathan Lindberg – Writing Center Journal, 2025
In this essay, I suggest that we should embrace generative artificial intelligence (GenAI) writing tools, particularly chatbots (e.g., ChatGPT, Copilot, Claude), because they can enable linguistic equity by leveling the academic playing field for English as an additional language students. As writing experts, we can find ways to use this…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Zi Yang; Junjie Gavin Wu; Haoran Xie – Asia Pacific Journal of Education, 2025
The emergence of generative artificial intelligence (GAI) in the past two years is exerting profound effects throughout society. However, while this new technology undoubtedly promises substantial benefits, its disruptive nature also means that it poses a variety of challenges. The field of education is no exception. This position paper intends to…
Descriptors: Artificial Intelligence, Ethics, Technology Uses in Education, Natural Language Processing
Demuth, Katherine; Johnson, Mark – First Language, 2020
Exemplar-based learning requires: (1) a segmentation procedure for identifying the units of past experiences that a present experience can be compared to, and (2) a similarity function for comparing these past experiences to the present experience. This article argues that for a learner to learn a language these two mechanisms will require…
Descriptors: Comparative Analysis, Language Acquisition, Linguistic Theory, Grammar
McClelland, James L. – First Language, 2020
Humans are sensitive to the properties of individual items, and exemplar models are useful for capturing this sensitivity. I am a proponent of an extension of exemplar-based architectures that I briefly describe. However, exemplar models are very shallow architectures in which it is necessary to stipulate a set of primitive elements that make up…
Descriptors: Models, Language Processing, Artificial Intelligence, Language Usage
MacKenzie D. Sidwell; Landon W. Bonner; Kayla Bates-Brantley; Shengtian Wu – Intervention in School and Clinic, 2024
Oral reading fluency probes are essential for reading assessment, intervention, and progress monitoring. Due to the limited options for choosing oral reading fluency probes, it is important to utilize all available resources such as generative artificial intelligence (AI) like ChatGPT to create oral reading fluency probes. The purpose of this…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Oral Reading
Peer reviewedSharf, Richard S. – Journal of Counseling & Development, 1985
The ability of computers to understand phrases and sentences has implications for future trends in counseling. Examples of computer-person interaction are given. (Author)
Descriptors: Artificial Intelligence, Career Counseling, Computer Assisted Instruction, Computer Software
Peer reviewedTeodorescu, Ioana – Canadian Library Journal, 1987
Compares artificial intelligence and information retrieval paradigms for natural language understanding, reviews progress to date, and outlines the applicability of artificial intelligence to question answering systems. A list of principal artificial intelligence software for database front end systems is appended. (CLB)
Descriptors: Artificial Intelligence, Computer Software, Information Retrieval, Information Science
Peer reviewedKramsch, Claire; And Others – CALICO Journal, 1985
Details the current status, the future plans and the reasoning behind a five-year, campus-wide educational experiment for the integration of computers into the foreign language curriculum at MIT. The project is to use artificial intelligence in natural processing and to include interactive video and interactive audio components. (Author/SED)
Descriptors: Artificial Intelligence, Communicative Competence (Languages), Computer Assisted Instruction, Courseware
Matthiessen, Christian – 1987
Taking the lexicogrammatical resources (i.e. the vocabulary and syntax) of English as a starting point, this report explores the demands those resources put on the design of the part of a text generation system that supports the process of lexicogrammatical expression. The first section of the report notes that a reason for using the lexicogrammar…
Descriptors: Artificial Intelligence, Cognitive Processes, Cognitive Psychology, Computer Uses in Education
Russell, William J., Ed. – 1978
Four conference papers on discourse are included. In "How Context Contributes to the Interpretation of Temporal Expressions," Carlota S. Smith provides a summary analysis of the temporal interpretation of English sentences. Many sentences are shown to be semantically incomplete; it is argued that information from neighboring sentences is…
Descriptors: Artificial Intelligence, Case (Grammar), Child Language, Cognitive Processes
Peer reviewedDodigovic, Marina – CALICO Journal, 1998
In most computer-assisted-language-learning (CALL) projects, research forms an important part of the development process. However, this research frequently goes unnoticed by the academic community, and developers often fail to receive academic recognition for the research component imbedded in their development projects.(Author/ER)
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer Software Development, English (Second Language)

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