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Kun Sun; Rong Wang – Cognitive Science, 2025
The majority of research in computational psycholinguistics on sentence processing has focused on word-by-word incremental processing within sentences, rather than holistic sentence-level representations. This study introduces two novel computational approaches for quantifying sentence-level processing: sentence surprisal and sentence relevance.…
Descriptors: Reading Rate, Reading Comprehension, Sentences, Computation
Eleni Tsaprouni; Christina Manouilidou – Journal of Psycholinguistic Research, 2025
Deverbal formations in Greek, e.g. "mi'razo" 'to distribute' < "'mirazma" 'distributing' are considered morphologically complex lexical items. Previous psycholinguistic studies in Greek and English already highlighted the importance of lexical category and argument structure of the base verb in the processing of deverbal…
Descriptors: Language Processing, Word Processing, Greek, Psycholinguistics
Michaela Socolof; Timothy J. O'Donnell; Michael Wagner – Cognitive Science, 2025
It has been repeatedly found that idioms are processed faster than syntactically matched literal phrases, in both comprehension and production. This has led to debate about whether idioms are accessed as chunks or built compositionally, with different studies attempting to measure the effect of compositionality on processing, with differing…
Descriptors: Language Patterns, Sentences, Reading Comprehension, Language Processing
Allie Michael; Abdullah O. Akinde – Assessment Update, 2024
Open-ended responses to surveys can be highly beneficial to higher education institutions, providing clarity and context that quantitative data can sometimes lack. However, analyzing open-ended responses typically takes time and manpower most institutional assessment offices do not have to spare. This study focused on finding a potential solution…
Descriptors: Artificial Intelligence, Natural Language Processing, Student Surveys, Feedback (Response)
Ani Grubišic; Ines Šaric-Grgic; Angelina Gašpar; Branko Žitko – Journal of Computer Assisted Learning, 2025
Background: Adaptive educational systems have gained increasing attention due to their ability to personalise educational content based on individual learner progress. Prior research highlights that intelligent tutoring systems (ITSs) and adaptive courseware models improve learning outcomes by dynamically adjusting instructional materials.…
Descriptors: Usability, Courseware, Natural Language Processing, Intelligent Tutoring Systems
Christopher Adamson – New Directions for Teaching and Learning, 2025
This chapter responds to the recent crisis surrounding developments in large language models (LLMs) and generative AI with a relational view of education informed by the emerging world-centered approach to education and a synthesis of personalist character formation with feminist care ethics. It proposes that the instinct to manage student use of…
Descriptors: Artificial Intelligence, Natural Language Processing, Automation, Feminism
Frank Lee; Alex Algarra – Information Systems Education Journal, 2025
This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop…
Descriptors: Labor Turnover, Data Analysis, Natural Language Processing, Employees
Brian Clements; Tamirat T. Abegaz; Bryson Payne – Information Systems Education Journal, 2025
The rise of artificial intelligence (AI) has made life and work easier; however, AI has also made it almost impossible to determine whether the information we consume is legitimate, AI-generated, or AI-manipulated. This paper examines how the use of artificial intelligence, specifically GPT-4, Gemini Advanced, and Claude Opus, can aid a user in…
Descriptors: Artificial Intelligence, Perception, Man Machine Systems, Natural Language Processing
Luis Eduardo Muñoz Guerrero; Yony Fernando Ceballos; Luis David Trejos Rojas – Contemporary Educational Technology, 2025
Recent progress made in conversational AI lays emphasis on the need for development of language models that possess solid logical reasoning skills and further extrapolated capabilities. An examination into this phenomenon investigates how well the Capybara dataset can improve one's ability to reason using language-based systems. Multiple…
Descriptors: Artificial Intelligence, Logical Thinking, Models, Natural Language Processing
Michael J. Parker; Caitlin Anderson; Claire Stone; YeaRim Oh – International Journal of Artificial Intelligence in Education, 2025
This paper assesses the potential for the large language models (LLMs) GPT-4 and GPT-3.5 to aid in deriving insight from education feedback surveys. Exploration of LLM use cases in education has focused on teaching and learning, with less exploration of capabilities in education feedback analysis. Survey analysis in education involves goals such…
Descriptors: Artificial Intelligence, Natural Language Processing, Surveys, Feedback (Response)
Stanojevic, Miloš; Brennan, Jonathan R.; Dunagan, Donald; Steedman, Mark; Hale, John T. – Cognitive Science, 2023
To model behavioral and neural correlates of language comprehension in naturalistic environments, researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFGs), yet such formalisms are not…
Descriptors: Correlation, Language Processing, Brain Hemisphere Functions, Natural Language Processing
Gesa Fee Komar; Laura Mieth; Axel Buchner; Raoul Bell – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
The animacy effect refers to the memory advantage of words denoting animate beings over words denoting inanimate objects. Remembering animate beings may serve important evolutionary functions, but the cognitive mechanism underlying the animacy effect has remained elusive. According to the richness-of-encoding account, animate words stimulate…
Descriptors: Foreign Countries, Cognitive Processes, Memory, Recall (Psychology)
Moshe Poliak; Rachel Ryskin; Mika Braginsky; Edward Gibson – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
Under the noisy-channel framework of language comprehension, comprehenders infer the speaker's intended meaning by integrating the perceived utterance with their knowledge of the language, the world, and the kinds of errors that can occur in communication. Previous research has shown that, when sentences are improbable under the meaning prior…
Descriptors: Russian, Ambiguity (Semantics), Sentence Structure, Inferences
Q. Feltgen; G. Cislaru – Discourse Processes: A Multidisciplinary Journal, 2025
The broader aim of this study is the corpus-based investigation of the written language production process. To this end, temporal markers have been keylog recorded alongside the writing processes to exploit pauses to segment the speech product into linear units of performance. However, identifying these pauses requires selecting the relevant…
Descriptors: Writing Processes, Writing Skills, Written Language, Intervals
Crossing the Boundary: No Catastrophic Limits on Infants' Capacity to Represent Linguistic Sequences
Natalia Reoyo-Serrano; Anastasia Dimakou; Chiara Nascimben; Tamara Bastianello; Daniela Lucangeli; Silvia Benavides-Varela – Developmental Science, 2025
The boundary effect, namely the infants' failures to compare small and large numerosities, is well documented in studies using visual stimuli. The prevailing explanation is that the numerical system used to process sets up to 3 is incompatible with the system employed for numbers >3. This study investigates the boundary effect in 10-month-old…
Descriptors: Infants, Language Acquisition, Speech Communication, Language Processing

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