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Exploring the Application of Large Language Models in Instrumentation and Control Engineering Education: A Questionnaire Survey and Examination Performance Analysis
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Wu Xu; Zhang Wei; Peng Yan – European Journal of Education, 2025
This study investigates the use of Large Language Models (LLMs) by undergraduates majoring in Instrumentation and Control Engineering (ICE) at University of Shanghai for Science and Technology. We conducted a questionnaire survey to assess the awareness and usage habits of these LLMs among ICE undergraduates in ICE courses, focusing on the model…
Descriptors: Artificial Intelligence, Natural Language Processing, Engineering Education, Majors (Students)
Measuring the Expressive Language and Vocabulary of Latino English Learners Using Hand Transcribed Speech Data and Automated Scoring
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Sano, Makoto; Baker, Doris Luft; Collazo, Marlen; Le, Nancy; Kamata, Akihito – Grantee Submission, 2020
Purpose: Explore how different automated scoring (AS) models score reliably the expressive language and vocabulary knowledge in depth of young second grade Latino English learners. Design/methodology/approach: Analyze a total of 13,471 English utterances from 217 Latino English learners with random forest, end-to-end memory networks, long…
Descriptors: English Language Learners, Hispanic American Students, Elementary School Students, Grade 2
Vectorial Representations of Meaning for a Computational Model of Language Comprehension
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Wu, Stephen Tze-Inn – ProQuest LLC, 2010
This thesis aims to define and extend a line of computational models for text comprehension that are humanly plausible. Since natural language is human by nature, computational models of human language will always be just that--models. To the degree that they miss out on information that humans would tap into, they may be improved by considering…
Descriptors: Comprehension, Semantics, Syntax, Short Term Memory
Handbook of Latent Semantic Analysis
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Landauer, Thomas K., Ed.; McNamara, Danielle S., Ed.; Dennis, Simon, Ed.; Kintsch, Walter, Ed. – Routledge, Taylor & Francis Group, 2007
"The Handbook of Latent Semantic Analysis" is the authoritative reference for the theory behind Latent Semantic Analysis (LSA), a burgeoning mathematical method used to analyze how words make meaning, with the desired outcome to program machines to understand human commands via natural language rather than strict programming protocols.…
Descriptors: Semantics, Natural Language Processing, Philosophy, Artificial Intelligence
What's So Hard about Understanding Language?
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Read, Walter; And Others – 1988
A discussion of the application of artificial intelligence to natural language processing looks at several problems in language comprehension, involving semantic ambiguity, anaphoric reference, and metonymy. Examples of these problems are cited, and the importance of the computational approach in analyzing them is explained. The approach applies…
Descriptors: Ambiguity, Artificial Intelligence, Comprehension, Epistemology
Artificial Intelligence, Language and the Study of Knowledge.
Goldstein, Ira; And Others – 1975
This paper studies the relationship of artificial intelligence (AI) to the study of language and the representation of the underlying knowledge that supports the comprehension process. It develops the view that intelligence is based on the ability to use large amounts of diverse kinds of knowledge in procedural ways, rather than on the possession…
Descriptors: Artificial Intelligence, Cognitive Processes, Communication (Thought Transfer), Comprehension