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Ruthie E. Knight; Michaela J. Ritter; Diane F. Loeb – Communication Disorders Quarterly, 2025
The purpose of this narrative review was to examine the linguistic and classroom strategies used by young adults with dyslexia. Studies investigating evidence about university students' use of strategies were compiled from four databases, including Academic Search Complete, APA PyscINFO, Education Research Complete, and Medline. Among the 117…
Descriptors: Dyslexia, Students with Disabilities, College Students, Learning Strategies
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Kadir Karakaya – Asian Journal of Distance Education, 2025
This article explores human-AI interaction with large language models or conversational agents in complex information tasks with a focus on prompt engineering strategies. The paper reviews the current literature on the use of artificial intelligence (AI) for complex information tasks that are often nonlinear and entail interpretation,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Man Machine Systems, Interaction
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Brian Heseung Kim; Julie J. Park; Pearl Lo; Dominique Baker; Nancy Wong; Stephanie Breen; Huong Truong; Jia Zheng; Kelly Rosinger; OiYan A. Poon – Research in Higher Education, 2025
Letters of recommendation from school counselors are required to apply to most selective universities. We use cutting-edge natural language processing techniques to algorithmically analyze a national dataset of over 600,000 student applications and counselor recommendation letters submitted through the Common Application. We examine how the length…
Descriptors: Letters (Correspondence), Advocacy, School Counselors, High Schools
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Qixuan Wu; Hyung Jae Chang; Long Ma – Journal of Advanced Academics, 2025
It is very important to identify talented students as soon as they are admitted to college so that appropriate resources are provided and allocated to them to optimize and excel in their education. Currently, this process is labor-intensive and time-consuming, as it involves manual reviews of each student's academic record. This raises the…
Descriptors: Electronic Learning, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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Arzu Atasoy; Saieed Moslemi Nezhad Arani – Education and Information Technologies, 2025
There is growing interest in the potential of Artificial Intelligence (AI) to assist in various educational tasks, including writing assessment. However, the comparative efficacy of human and AI-powered systems in this domain remains a subject of ongoing exploration. This study aimed to compare the accuracy of human raters (teachers and…
Descriptors: Writing (Composition), Writing Evaluation, Student Evaluation, Artificial Intelligence
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Karen Singer-Freeman; Kristi Verbeke; Betsy Barre – Higher Learning Research Communications, 2025
Objectives: The present study investigated the extent to which AI use and opinions about its use will vary by academic stage and academic task in ways that align with Budwig's (2013) developmental stages. Methods: We surveyed 1,259 students from different academic stages (first-year students, sophomores, juniors, seniors, and graduate students) at…
Descriptors: Undergraduate Students, Graduate Students, Educational Technology, Educational Policy
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Lisa Marie Ripoll Y Schmitz; Philipp Sonnleitner – Large-scale Assessments in Education, 2025
Background: The increasing capabilities of generative artificial intelligence (AI), exemplified by OpenAI's transformer-based language model GPT-4 (ChatGPT), have drawn attention to its application in educational contexts. This study evaluates the potential of such models in generating German reading comprehension texts for educational large-scale…
Descriptors: Artificial Intelligence, Technology Uses in Education, Man Machine Systems, Written Language
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Amanda Light Dunbar; Sandra Chang-Kredl – Changing English: Studies in Culture and Education, 2025
Long before ChatGPT, it was an open secret that students did not always read the books they were assigned in their English Language Arts (ELA) classes, relying instead on online study guides like SparkNotes. Via a retrospective survey, our exploratory study examined (1) the rate of SparkNotes use among high-school ELA students; (2) why students…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Language Arts
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Takumi Kosaka – Reading and Writing: An Interdisciplinary Journal, 2025
This study examines context effects on lexical processing by low-proficiency Japanese learners of English during sentence comprehension, and the role of individual differences in verbal working memory (WM). Thirty Japanese learners of English as a second language (L2) and 27 speakers of English as a first language (L1) were recruited for a…
Descriptors: Second Language Learning, English (Second Language), Foreign Countries, Lexicology
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Lei Cao; Kien Tsong Chau; Wan Ahmad Jaafar Wan Yahaya – International Journal of Game-Based Learning, 2025
In cultural relic restoration learning, developing both knowledge proficiency and self-efficacy is essential for academic success and professional competency. However, conventional learning methods often lack interactive elements that support cognitive engagement and skill acquisition. To address this limitation, this study introduced a…
Descriptors: Game Based Learning, Artificial Intelligence, Acoustics, Technology Uses in Education
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Wesley Morris; Scott Crossley; Langdon Holmes; Chaohua Ou; Mihai Dascalu; Danielle McNamara – International Journal of Artificial Intelligence in Education, 2025
As intelligent textbooks become more ubiquitous in classrooms and educational settings, the need to make them more interactive arises. An alternative is to ask students to generate knowledge in response to textbook content and provide feedback about the produced knowledge. This study develops Natural Language Processing models to automatically…
Descriptors: Formative Evaluation, Feedback (Response), Textbooks, Artificial Intelligence
Tsiola, Anna – ProQuest LLC, 2021
Naturalistic language learning is contextually grounded. When people learn their first (L1) and often their second (L2) language, they do so in various contexts. In this dissertation I examine the effect of various contexts on language development. Part 1 describes the effects of textual, linguistic context in reading. I employed an eye-tracking…
Descriptors: Natural Language Processing, Second Language Learning, Language Processing, Language Acquisition
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Günther, Fritz; Marelli, Marco – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
Effects of semantic transparency, reflected in processing differences between semantically transparent ("teabag") and opaque ("ladybird") compounds, have received considerable attention in the investigation of the role of constituents in compound processing. However, previous studies have yielded inconsistent results. In the…
Descriptors: Semantics, Language Processing, Vocabulary, Definitions
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Brundage, Shelley B.; Bernstein Ratner, Nan – Topics in Language Disorders, 2022
Purpose: Although commonly defined as a speech disorder, stuttering interacts with the language production system in important ways. Our purpose is to summarize research findings on linguistic variables that influence stuttering assessment and treatment. Method and Results: Numerous topics are summarized. First, we review research that has…
Descriptors: Stuttering, Language Fluency, Speech Communication, Language Processing
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Felser, Claudia; Drummer, Janna-Deborah – Journal of Psycholinguistic Research, 2022
Pronouns can sometimes covary with a non c-commanding quantifier phrase (QP). To obtain such 'telescoping' readings, a semantic representation must be computed in which the QP's semantic scope extends beyond its surface scope. Non-native speakers have been claimed to have more difficulty than native speakers deriving such non-isomorphic…
Descriptors: Form Classes (Languages), Native Language, Second Languages, Sentences
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