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Mohamed Ali Nagy Elmaadaway; Mohamed Elsayed El-Naggar; Mohamed Radwan Ibrahim Abouhashesh – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence (AI) made substantial progress with language recognition. Proficiency in spoken English reading is a prerequisite for fluency in written English. However, research on its use, especially for non-native speakers, is lacking despite increased usage. Objectives: This study aimed to enhance the oral reading fluency…
Descriptors: Artificial Intelligence, Reading Fluency, Elementary School Students, Oral Reading
Owen Henkel; Libby Hills; Bill Roberts; Joshua McGrane – International Journal of Artificial Intelligence in Education, 2025
Formative assessment plays a critical role in improving learning outcomes by providing feedback on student mastery. Open-ended questions, which require students to produce multi-word, nontrivial responses, are a popular tool for formative assessment as they provide more specific insights into what students do and do not know. However, grading…
Descriptors: Artificial Intelligence, Grading, Reading Comprehension, Natural Language Processing
Jessie S. Barrot – Technology, Knowledge and Learning, 2025
Research shows that students often struggle with understanding complex academic texts, conducting comprehensive literature reviews, and adhering to the precise requirements of academic writing. One emerging tool that has the potential to address these challenges is SciSpace, an AI-powered platform designed to enhance the academic writing process…
Descriptors: Writing (Composition), Academic Language, Artificial Intelligence, Writing Processes
Kendall Willems; Susan J. Loveall; J. Marc Goodrich; Danika Lang – Language, Speech, and Hearing Services in Schools, 2025
Purpose: Autistic individuals often exhibit poorer emergent literacy skills (e.g., phonological awareness, print knowledge, oral language) relative to their non-autistic peers. Although emergent literacy skills are known to impact future reading success in typical development, their relationship with word recognition and reading comprehension in…
Descriptors: Emergent Literacy, Reading Skills, Young Children, Autism Spectrum Disorders
Sun-Joo Cho; Goodwin Amanda; Jorge Salas; Sophia Mueller – Grantee Submission, 2025
This study incorporates a random forest (RF) approach to probe complex interactions and nonlinearity among predictors into an item response model with the goal of using a hybrid approach to outperform either an RF or explanatory item response model (EIRM) only in explaining item responses. In the specified model, called EIRM-RF, predicted values…
Descriptors: Item Response Theory, Artificial Intelligence, Statistical Analysis, Predictor Variables
Huili Zhang; Guoliang Xu – International Journal of Web-Based Learning and Teaching Technologies, 2025
The process of building a teaching platform for contemporary Chinese literature poses many challenges. Based on big data research, this study was conducted using diversified intelligent analysis technology and theory. Through a fuzzy analytic hierarchy process method and relevant steps regarding intelligent parameter improvement, this study…
Descriptors: Multiple Intelligences, Foreign Countries, Chinese, Literature
Chih-Chung Lin; Tzu-Hsuan Lin; Chi-Kay Tang – Journal of Computer Assisted Learning, 2025
Background: The integration of generative artificial intelligence (Gen-AI) into second language (L2) education has opened new possibilities for personalized and adaptive instruction. While Gen-AI has shown promise in supporting language production skills, its application in reading, particularly in pre-reading scaffolding, remains underexplored.…
Descriptors: Reading Comprehension, English (Second Language), Second Language Learning, College Freshmen
Mary Ehrenworth; Philip Seyfried – ASCD, 2025
The relationship between AI and literacy education isn't simple. Every tool that makes work more efficient also requires careful consideration. In this measured look at the powerful capabilities of artificial intelligence, literacy experts Mary Ehrenworth and Philip Seyfried take K-12 teachers on a tour of what's possible when AI tools are…
Descriptors: Artificial Intelligence, Technology Uses in Education, Literacy Education, Elementary Secondary Education
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
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
Nikolaos Pellas – Journal of Educational Computing Research, 2026
Despite the increasing integration of generative Artificial Intelligence (GenAI) in education, a significant research gap exists in its comparative effectiveness against traditional instructor-led guidance in specialized humanities like philology. This quasi-experimental study compares an experimental group (EG, n = 26), using GenAI chatbots for…
Descriptors: Artificial Intelligence, Technology Uses in Education, Feedback (Response), Computer Mediated Communication
Layes Smail; Gharaibeh Mahmoud; Djeribiai Adel – Reading Psychology, 2025
This study examined the independent contribution of morphological awareness and orthographic awareness in reading comprehension, controlling for working memory and reading fluency in Arabic-speaking children. Participants (N = 244) from grades four and five, were classified into typical comprehenders (n = 207) and poor comprehenders (n = 37). All…
Descriptors: Morphology (Languages), Orthographic Symbols, Reading Comprehension, Arabic
Muhammad Mooneeb Ali; Ahmed M. Alaa; Wael Alharbi; Issa Al Qurashi – International Journal of Technology in Education, 2025
Machine and prompt-based Artificial Intelligence (AI) learning has made significant evolution profusely. In education, it has revitalized researchers and educators to scout out subsequent advantages for optimizing learning results. Chiefly, Generative AI has exhibited substantial potential as a tool for language augmentation. This study aims to…
Descriptors: Foreign Countries, Grade 10, Artificial Intelligence, Natural Language Processing
Eduardo Davalos; Yike Zhang; Namrata Srivastava; Jorge Alberto Salas; Sara McFadden; Sun-Joo Cho; Gautam Biswas; Amanda Goodwin – Grantee Submission, 2025
Reading assessments are essential for enhancing students' comprehension, yet many EdTech applications focus mainly on outcome-based metrics, providing limited insights into student behavior and cognition. This study investigates the use of multimodal data sources -- including eye-tracking data, learning outcomes, assessment content, and teaching…
Descriptors: Natural Language Processing, Learning Analytics, Reading Tests, Reading Comprehension
Aydin Bulut – European Journal of Education, 2025
The present study employs a systematic thematic analysis of the extant academic literature on the subject of 'technology in reading' to explore its conceptual evolution and educational implications. The PRISMA framework was used to analyse 6081 peer-reviewed articles published between 1944 and July 2025 through bibliometric methods. The findings…
Descriptors: Literature Reviews, Bibliometrics, Meta Analysis, Reading Materials
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