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Pauline Frizelle; Ana Buckley; Tricia Biancone; Anna Ceroni; Darren Dahly; Paul Fletcher; Dorothy V. M. Bishop; Cristina McKean – Journal of Child Language, 2024
This study reports on the feasibility of using the Test of Complex Syntax- Electronic (TECS-E), as a self-directed app, to measure sentence comprehension in children aged 4 to 5 ½ years old; how testing apps might be adapted for effective independent use; and agreement levels between face-to-face supported computerized and independent computerized…
Descriptors: Language Processing, Computer Software, Language Tests, Syntax
Erin Pacquetet – ProQuest LLC, 2024
This dissertation explores the relationship between language production processes and recorded typing behaviors among native speakers of English writing in their native language. Typing is quite prevalent in modern societies, as its use is becoming increasingly required in professional and personal settings but it remains largely understudied in…
Descriptors: English, Native Language, Writing (Composition), Word Processing
Daniel Sbastian; Gloria Putri Waang – Journal of English Teaching, 2025
Technological advances have made the ability to translate no longer exclusively belong to humans. Today, machine translation has turned into a tool with superior performance to convert text between languages without the need for human intervention. One of the translation research foci is the studies of causative translation, especially from…
Descriptors: Novels, Translation, Indonesian, English (Second Language)
Mahowald, Kyle; Kachergis, George; Frank, Michael C. – First Language, 2020
Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…
Descriptors: Models, Language Processing, Computational Linguistics, Language Acquisition
Liat Shklarski; Kathleen Ray – Journal of Teaching in Social Work, 2024
Artificial intelligence has evolved since its inception in the 1950s, resulting in the creation of large language models that are trained on extensive data sets to understand and generate content, such as OpenAI's ChatGPT, which launched in November 2022. Modern technology that is easy to access and free to use, like ChatGPT, is changing the…
Descriptors: Social Work, Counselor Training, Artificial Intelligence, Computer Software
Holly Robson; Harriet Thomasson; Matthew H. Davis – International Journal of Language & Communication Disorders, 2024
Background: The use of telepractice in aphasia research and therapy is increasing in frequency. Teleassessment in aphasia has been demonstrated to be reliable. However, neuropsychological and clinical language comprehension assessments are not always readily translatable to an online environment and people with severe language comprehension or…
Descriptors: Aphasia, Severity (of Disability), Videoconferencing, Comparative Analysis
Paul Meara; Imma Miralpeix – Vocabulary Learning and Instruction, 2025
This paper is part 5 of a series of workshops that examines the properties of some simple models of vocabulary networks. While previous workshops dealt with activating words in the network, this workshop focuses on vocabulary loss. We will simulate two possible ways of modelling attrition: (a) explicitly turning active words OFF, and (b) raising…
Descriptors: Vocabulary Development, Workshops, Models, Networks
King, Daniel; Gentner, Dedre – Cognitive Science, 2022
This paper explores the processes underlying verb metaphoric extension. Work on metaphor processing has largely focused on noun metaphor, despite evidence that verb metaphor is more common. Across three experiments, we collected paraphrases of simple intransitive sentences varying in semantic strain--for example, "The motor complained"…
Descriptors: Semantics, Verbs, Figurative Language, Phrase Structure
Masato Nakamura; Shota Momma; Hiromu Sakai; Colin Phillips – Cognitive Science, 2024
Comprehenders generate expectations about upcoming lexical items in language processing using various types of contextual information. However, a number of studies have shown that argument roles do not impact neural and behavioral prediction measures. Despite these robust findings, some prior studies have suggested that lexical prediction might be…
Descriptors: Diagnostic Tests, Nouns, Language Processing, Verbs
Bogdan Nicula; Mihai Dascalu; Tracy Arner; Renu Balyan; Danielle S. McNamara – Grantee Submission, 2023
Text comprehension is an essential skill in today's information-rich world, and self-explanation practice helps students improve their understanding of complex texts. This study was centered on leveraging open-source Large Language Models (LLMs), specifically FLAN-T5, to automatically assess the comprehension strategies employed by readers while…
Descriptors: Reading Comprehension, Language Processing, Models, STEM Education
Sinclair, Jeanne; Jang, Eunice Eunhee; Rudzicz, Frank – Journal of Educational Psychology, 2021
Advances in machine learning (ML) are poised to contribute to our understanding of the linguistic processes associated with successful reading comprehension, which is a critical aspect of children's educational success. We used ML techniques to investigate and compare associations between children's reading comprehension and 260 linguistic…
Descriptors: Prediction, Reading Comprehension, Natural Language Processing, Speech Communication

Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence
Sarah M. Avendano – ProQuest LLC, 2022
Early Expressive language exposure is associated with child language acquisition and advantageous long-term developmental outcomes. The measurement of expressive language in a child's immediate environment is critical to the early identification of children who are at risk of low expressive language exposure, such as children with language delays…
Descriptors: Autism Spectrum Disorders, Computer Software, Language Processing, Language Acquisition
Byung-Doh Oh – ProQuest LLC, 2024
Decades of psycholinguistics research have shown that human sentence processing is highly incremental and predictive. This has provided evidence for expectation-based theories of sentence processing, which posit that the processing difficulty of linguistic material is modulated by its probability in context. However, these theories do not make…
Descriptors: Language Processing, Computational Linguistics, Artificial Intelligence, Computer Software
Andrea Bruera; Yuan Tao; Andrew Anderson; Derya Çokal; Janosch Haber; Massimo Poesio – Cognitive Science, 2023
The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented…
Descriptors: Neurosciences, Brain Hemisphere Functions, Artificial Intelligence, Diagnostic Tests