Publication Date
| In 2026 | 0 |
| Since 2025 | 4 |
| Since 2022 (last 5 years) | 12 |
| Since 2017 (last 10 years) | 16 |
| Since 2007 (last 20 years) | 21 |
Descriptor
| Computer Software | 24 |
| Reading Comprehension | 24 |
| Artificial Intelligence | 21 |
| Teaching Methods | 9 |
| Foreign Countries | 7 |
| Intelligent Tutoring Systems | 7 |
| Natural Language Processing | 7 |
| Technology Integration | 7 |
| Technology Uses in Education | 7 |
| Computational Linguistics | 6 |
| Models | 6 |
| More ▼ | |
Source
Author
| Danielle S. McNamara | 3 |
| April Murphy | 2 |
| Arthur C. Graesser | 2 |
| Benjamin D. Nye | 2 |
| Dascalu, Mihai | 2 |
| Husni Almoubayyed | 2 |
| Kole A. Norberg | 2 |
| Kyle Weldon | 2 |
| Logan De Ley | 2 |
| McNamara, Danielle S. | 2 |
| Mihai Dascalu | 2 |
| More ▼ | |
Publication Type
Education Level
| Higher Education | 5 |
| Postsecondary Education | 5 |
| Elementary Secondary Education | 4 |
| Elementary Education | 2 |
| Grade 4 | 2 |
| Intermediate Grades | 2 |
| Middle Schools | 2 |
| Secondary Education | 2 |
| Adult Education | 1 |
| Grade 5 | 1 |
| Grade 6 | 1 |
| More ▼ | |
Audience
| Researchers | 2 |
| Students | 1 |
| Teachers | 1 |
Location
| Turkey | 2 |
| Australia | 1 |
| Brazil | 1 |
| Malaysia | 1 |
| Netherlands | 1 |
| South Korea | 1 |
| South Korea (Seoul) | 1 |
| Thailand | 1 |
| Uruguay | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| Raven Progressive Matrices | 1 |
| Wechsler Intelligence Scale… | 1 |
What Works Clearinghouse Rating
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
Linh Huynh; Danielle S. McNamara – Grantee Submission, 2025
We conducted two experiments to assess the alignment between Generative AI (GenAI) text personalization and hypothetical readers' profiles. In Experiment 1, four LLMs (i.e., Claude 3.5 Sonnet; Llama; Gemini Pro 1.5; ChatGPT 4) were prompted to tailor 10 science texts (i.e., biology, chemistry, physics) to accommodate four different profiles…
Descriptors: Natural Language Processing, Profiles, Individual Differences, Semantics
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
Nuchsara C. Thongsan; Neil J. Anderson – LEARN Journal: Language Education and Acquisition Research Network, 2025
This study investigates the integration of ChatGPT, a generative AI tool, into critical reading instruction for university-level EFL learners. Recognizing the importance of higher-order reading skills such as evaluating arguments, recognizing bias, synthesizing information, and generating counterarguments, the research explores how AI-supported…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Technology Integration
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
Xizhe Wang; Yihua Zhong; Changqin Huang; Xiaodi Huang – IEEE Transactions on Learning Technologies, 2024
Reading comprehension is a widely adopted method for learning English, involving reading articles and answering related questions. However, the reading comprehension training typically focuses on the skill level required for a standardized learning stage, without considering the impact of individual differences in linguistic competence. This…
Descriptors: Reading Comprehension, Artificial Intelligence, Computer Software, Synchronous Communication
Ferdi Çelik; Ceylan Yangin Ersanli; Goshnag Arslanbay – International Review of Research in Open and Distributed Learning, 2024
This experimental study investigates the impact of ChatGPT-simplified authentic texts on university students' reading comprehension, inferencing, and reading anxiety levels. A within-subjects design was employed, and 105 undergraduate English as a foreign language (EFL) students engaged in both original and ChatGPT-simplified text readings,…
Descriptors: Foreign Countries, Reading Comprehension, Artificial Intelligence, English (Second Language)
Dennis Murphy Odo – Language Learning & Technology, 2025
There is currently limited investigation of readers' comprehension of AI simplified text from the perspective of educators, but such research can help to more effectively address the specific needs and perspectives of language teachers and learners regarding the comprehensibility of AI simplified text. Therefore, the purpose of this study was to…
Descriptors: Reading Comprehension, Artificial Intelligence, Computer Software, Technology Integration
Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – International Journal of Artificial Intelligence in Education, 2025
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Tam Duc Dinh – International Journal of Information and Learning Technology, 2024
Purpose: The advent of ChatGPT has fundamentally changed the way people approach and access information. While we are encouraged to embrace the tool for its various benefits, it is yet to be known how to drive people to adopt this technology, especially to improve their life skills. Using implicit self-theories, the current research delineated the…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Technology Integration
Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
Maggie A. Mosher; Lisa A. Dieker; Rebecca Hines – Journal of Special Education Preparation, 2024
The use of artificial intelligence (AI) is not a new concept. Still, the press, the worry, and the hype around the potential benefits and limitations of the explosion of these tools in this field is a current topic in teacher education. In this article, the authors summarize the past use of AI, present easily adaptable tools in teacher education,…
Descriptors: Teacher Education Programs, Futures (of Society), Artificial Intelligence, Computer Software
Andreas Gegenfurtner, Editor; Ingo Kollar, Editor – New Perspectives on Learning and Instruction, 2024
Bringing together the research of leading international scholars in the field of digital learning, "Designing Effective Digital Learning Environments" discusses cutting-edge advancements in digital technology and presents an evidence-informed summary of best practices for effective design principles and implementation within educational…
Descriptors: Instructional Design, Best Practices, Information Technology, Technology Integration
Varol, Burcu; Erçetin, Gülcan – Computer Assisted Language Learning, 2021
This study explores the role of glosses and working memory capacity (WM) in second language (L2) learners' recall and comprehension in electronic reading. Glosses were investigated in terms of the type of information they provided (lexical versus topic-level) and their location on the screen (pop-up window versus separate window). One…
Descriptors: Reading Processes, Short Term Memory, Reading Comprehension, Recall (Psychology)
Previous Page | Next Page »
Pages: 1 | 2
Peer reviewed
Direct link
