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Showing 1 to 15 of 51 results Save | Export
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Li Nguyen; Oliver Mayeux; Zheng Yuan – International Journal of Multilingualism, 2024
Multilingualism presents both a challenge and an opportunity for Natural Language Processing, with code-switching representing a particularly interesting problem for computational models trained on monolingual datasets. In this paper, we explore how code-switched data affects the task of Machine Translation, a task which only recently has started…
Descriptors: Code Switching (Language), Vietnamese, English (Second Language), Second Language Learning
Boon, Ian Gregory – ProQuest LLC, 2022
It is standardly believed that some occurrences of expressions designate singularly, while other occurrences of expressions designate plurally. For instance, the singular expression the student may be used on an occasion to talk about one particular student, while the plural expression the students may be used on an occasion to talk about several…
Descriptors: Grammar, Morphemes, Language Usage, Essays
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Ramotowska, Sonia; Steinert-Threlkeld, Shane; Maanen, Leendert; Szymanik, Jakub – Cognitive Science, 2023
According to logical theories of meaning, a meaning of an expression can be formalized and encoded in truth conditions. Vagueness of the language and individual differences between people are a challenge to incorporate into the meaning representations. In this paper, we propose a new approach to study truth-conditional representations of vague…
Descriptors: Computation, Models, Semantics, Decision Making
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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
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
The ability to automatically assess the quality of paraphrases can be very useful for facilitating literacy skills and providing timely feedback to learners. Our aim is twofold: a) to automatically evaluate the quality of paraphrases across four dimensions: lexical similarity, syntactic similarity, semantic similarity and paraphrase quality, and…
Descriptors: Phrase Structure, Networks, Semantics, Feedback (Response)
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Monteiro, Kátia; Crossley, Scott; Botarleanu, Robert-Mihai; Dascalu, Mihai – Language Testing, 2023
Lexical frequency benchmarks have been extensively used to investigate second language (L2) lexical sophistication, especially in language assessment studies. However, indices based on semantic co-occurrence, which may be a better representation of the experience language users have with lexical items, have not been sufficiently tested as…
Descriptors: Second Language Learning, Second Languages, Native Language, Semantics
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Unger, Layla; Yim, Hyungwook; Savic, Olivera; Dennis, Simon; Sloutsky, Vladimir M. – Developmental Science, 2023
Recent years have seen a flourishing of Natural Language Processing models that can mimic many aspects of human language fluency. These models harness a simple, decades-old idea: It is possible to learn a lot about word meanings just from exposure to language, because words similar in meaning are used in language in similar ways. The successes of…
Descriptors: Natural Language Processing, Language Usage, Vocabulary Development, Linguistic Input
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Linh Huynh; Danielle S. McNamara – Grantee Submission, 2025
We conducted two experiments to assess the alignment between Generative AI (GenAI) text personalization and hypothetical readers' profiles. In Experiment 1, four LLMs (i.e., Claude 3.5 Sonnet; Llama; Gemini Pro 1.5; ChatGPT 4) were prompted to tailor 10 science texts (i.e., biology, chemistry, physics) to accommodate four different profiles…
Descriptors: Natural Language Processing, Profiles, Individual Differences, Semantics
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Jiang, Hang; Frank, Michael C.; Kulkarni, Vivek; Fourtassi, Abdellah – Cognitive Science, 2022
The linguistic input children receive across early childhood plays a crucial role in shaping their knowledge about the world. To study this input, researchers have begun applying distributional semantic models to large corpora of child-directed speech, extracting various patterns of word use/co-occurrence. Previous work using these models has not…
Descriptors: Caregivers, Caregiver Child Relationship, Linguistic Input, Semantics
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Almotairi, Maram; Fkih, Fethi – Journal of Education and e-Learning Research, 2022
The Question answering (QA) system plays a basic role in the acquisition of information and the e-learning environment is considered to be the field that is most in need of the question-answering system to help learners ask questions in natural language and get answers in short periods of time. The main problem in this context is how to understand…
Descriptors: Semantics, Natural Language Processing, Intelligent Tutoring Systems, Ambiguity (Semantics)
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Mengliyev, Bakhtiyor; Shahabitdinova, Shohida; Khamroeva, Shahlo; Gulyamova, Shakhnoza; Botirova, Adiba – Journal of Language and Linguistic Studies, 2021
This article is dedicated to the issue of morphological analysis and synthesis of word forms in a linguistic analyzer, which is a significant feature of corpus linguistics. The article discourses in detail the morphological analysis, the creation of artificial language, grammar and analyzer, the general scheme of the analysis program that…
Descriptors: Morphology (Languages), Computational Linguistics, Computer Software, Artificial Languages
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Crossley, Scott; Wan, Qian; Allen, Laura; McNamara, Danielle – Reading and Writing: An Interdisciplinary Journal, 2023
Synthesis writing is widely taught across domains and serves as an important means of assessing writing ability, text comprehension, and content learning. Synthesis writing differs from other types of writing in terms of both cognitive and task demands because it requires writers to integrate information across source materials. However, little is…
Descriptors: Writing Skills, Cognitive Processes, Essays, Cues
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Robert-Mihai Botarleanu; Micah Watanabe; Mihai Dascalu; Scott A. Crossley; Danielle S. McNamara – International Journal of Artificial Intelligence in Education, 2024
Age of Acquisition (AoA) scores approximate the age at which a language speaker fully understands a word's semantic meaning and represent a quantitative measure of the relative difficulty of words in a language. AoA word lists exist across various languages, with English having the most complete lists that capture the largest percentage of the…
Descriptors: Multilingualism, English (Second Language), Second Language Learning, Second Language Instruction
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Chopra, Harshita; Lin, Yiwen; Samadi, Mohammad Amin; Cavazos, Jacqueline G.; Yu, Renzhe; Jaquay, Spencer; Nixon, Nia – International Educational Data Mining Society, 2023
Exploring students' discourse in academic settings over time can provide valuable insight into the evolution of learner engagement and participation in online learning. In this study, we propose an analytical framework to capture topics and the temporal progression of learner discourse. We employed a Contextualized Topic Modeling technique on…
Descriptors: Semantics, Computer Mediated Communication, Pandemics, COVID-19
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