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Nathan Lowien; Damon P. Thomas – Australian Journal of Language and Literacy, 2025
Cognitive-informed reading education research utilises models that are underpinned by the notion that reading is a mental process of word recognition multiplied by language comprehension. Examples of these models include the Simple View of Reading, the Cognitive Foundations Framework, the Reading Rope and the Active Model of Reading. These models…
Descriptors: Reading Research, Reading Instruction, Reading Processes, Word Recognition
Bulut, Okan; Yildirim-Erbasli, Seyma Nur – International Journal of Assessment Tools in Education, 2022
Reading comprehension is one of the essential skills for students as they make a transition from learning to read to reading to learn. Over the last decade, the increased use of digital learning materials for promoting literacy skills (e.g., oral fluency and reading comprehension) in K-12 classrooms has been a boon for teachers. However, instant…
Descriptors: Reading Comprehension, Natural Language Processing, Artificial Intelligence, Automation
Dragos-Georgian Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Modeling reading comprehension processes is a critical task for Learning Analytics, as accurate models of the reading process can be used to match students to texts, identify appropriate interventions, and predict learning outcomes. This paper introduces an improved version of the Automated Model of Comprehension, namely version 4.0. AMoC has its…
Descriptors: Computer Software, Artificial Intelligence, Learning Analytics, Natural Language Processing
Dragos Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2023
Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…
Descriptors: Reading Comprehension, Models, Concept Mapping, Graphs
Chanyuan Gu; Samuel A. Nastase; Zaid Zada; Ping Li – npj Science of Learning, 2025
While evidence has accumulated to support the argument of shared computational mechanisms underlying language comprehension between humans and large language models (LLMs), few studies have examined this argument beyond native-speaker populations. This study examines whether and how alignment between LLMs and human brains captures the homogeneity…
Descriptors: Reading Comprehension, Native Language, Second Language Learning, Brain Hemisphere Functions
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
Hoeben Mannaert, Lara; Dijkstra, Katinka – International Journal of Behavioral Development, 2021
Over the past decade or so, developments in language comprehension research in the domain of cognitive aging have converged on support for resilience in older adults with regard to situation model updating when reading texts. Several studies have shown that even though age-related declines in language comprehension appear at the level of the…
Descriptors: Young Adults, Older Adults, Language Processing, Resilience (Psychology)
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2021
Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…
Descriptors: Computer Assisted Testing, Scoring, Natural Language Processing, Computer Software
Crossley, Scott A.; Skalicky, Stephen; Dascalu, Mihai – Journal of Research in Reading, 2019
Background: Advances in natural language processing (NLP) and computational linguistics have facilitated major improvements on traditional readability formulas that aim at predicting the overall difficulty of a text. Recent studies have identified several types of linguistic features that are theoretically motivated and predictive of human…
Descriptors: Natural Language Processing, Readability, Reading Comprehension, Reading Rate
Botarleanu, Robert-Mihai; Dascalu, Mihai; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2020
A key writing skill is the capability to clearly convey desired meaning using available linguistic knowledge. Consequently, writers must select from a large array of idioms, vocabulary terms that are semantically equivalent, and discourse features that simultaneously reflect content and allow readers to grasp meaning. In many cases, a simplified…
Descriptors: Natural Language Processing, Writing Skills, Difficulty Level, Reading Comprehension
Corlatescu, Dragos-Georgian; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2021
Reading comprehension is key to knowledge acquisition and to reinforcing memory for previous information. While reading, a mental representation is constructed in the reader's mind. The mental model comprises the words in the text, the relations between the words, and inferences linking to concepts in prior knowledge. The automated model of…
Descriptors: Reading Comprehension, Memory, Inferences, Syntax
Braasch, Jason L. G.; Kessler, Erica D. – Discourse Processes: A Multidisciplinary Journal, 2021
Comprehension substantially benefits from attending to, thinking about, and mentally representing the sources of any presented information. Such processes require mental effort and unfortunately people do not always engage in such activities. The current article presents a nascent, evolving model of discourse comprehension that formalizes…
Descriptors: Language Processing, Reading Comprehension, Discourse Analysis, Prediction
Paape, Dario; Avetisyan, Serine; Lago, Sol; Vasishth, Shravan – Cognitive Science, 2021
We present computational modeling results based on a self-paced reading study investigating number attraction effects in Eastern Armenian. We implement three novel computational models of agreement attraction in a Bayesian framework and compare their predictive fit to the data using k-fold cross-validation. We find that our data are better…
Descriptors: Computational Linguistics, Indo European Languages, Grammar, Bayesian Statistics
Marziyeh Khalilizadeh Ganjalikhani; Akbar Hesabi; Saeed Ketabi – International Journal of Multilingualism, 2024
Health translation has gotten considerable attention recently because language diversity in multilingual societies often leads to language barriers. The present study evaluates the linguistic comprehensibility of translations in the "Health Translations Website" from the Victorian Government of Australia using the patient-oriented and…
Descriptors: Health Services, Indo European Languages, Translation, English (Second Language)

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