NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Policymakers1
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 50 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Suping Yi; Wayan Sintawati; Yibing Zhang – Journal of Computer Assisted Learning, 2025
Background: Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has…
Descriptors: Reflection, Feedback (Response), Cooperative Learning, Natural Language Processing
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Chelsea Chandler; Rohit Raju; Jason G. Reitman; William R. Penuel; Monica Ko; Jeffrey B. Bush; Quentin Biddy; Sidney K. D’Mello – International Educational Data Mining Society, 2025
We investigated methods to enhance the generalizability of large language models (LLMs) designed to classify dimensions of collaborative discourse during small group work. Our research utilized five diverse datasets that spanned various grade levels, demographic groups, collaboration settings, and curriculum units. We explored different model…
Descriptors: Artificial Intelligence, Models, Natural Language Processing, Discourse Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Owen Henkel; Zach Levoninan; Millie-Ellen Postle; Chenglu Li – International Educational Data Mining Society, 2024
For middle-school math students, interactive question-answering (QA) with tutors is an effective way to learn. The flexibility and emergent capabilities of generative large language models (LLMs) has led to a surge of interest in automating portions of the tutoring process--including interactive QA to support conceptual discussion of mathematical…
Descriptors: Middle School Mathematics, Questioning Techniques, Algebra, Geometry
Peer reviewed Peer reviewed
Direct linkDirect link
Alexandra S. Dylman; Marie-France Champoux-Larsson; Candice Frances – Educational Psychology, 2025
We report four experiments investigating the effect of prosody on listening comprehension in 11-13-year-old children. Across all experiments, participants listened to short object descriptions and answered content-based questions about said objects. In Experiments 1-3, the descriptions were read in an emotionally positive or neutral tone of voice.…
Descriptors: Intonation, Middle School Students, Foreign Countries, Listening Comprehension
Peer reviewed Peer reviewed
Direct linkDirect link
Kason Ka Ching Cheung; Jack K. H. Pun; Wangyin Li – Research in Science Education, 2024
ChatGPT becomes a prominent tool for students' learning of science when students "read" its scientific texts. Students read to learn about climate change misinformation using ChatGPT, while they develop critical awareness of the content, linguistic features as well as nature of AI and science to comprehend these texts. In this…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Secondary School Students
Peer reviewed Peer reviewed
Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Ali Rashed Ibraheam Almohesh – International Review of Research in Open and Distributed Learning, 2024
In education, the integration of artificial intelligence (AI) has presented opportunities to transform the dynamics of online learning. This study investigated the impact of an AI-powered application, namely ChatGPT, on the autonomy of Saudi Arabian primary students participating in online classes. It also explored how the implementation of Chat…
Descriptors: Artificial Intelligence, Natural Language Processing, Foreign Countries, Elementary Schools
Peer reviewed Peer reviewed
Direct linkDirect link
Eunhye Shin – Journal of Computer Assisted Learning, 2025
Background: Analysing classroom dialogue is a widely used approach for understanding students' learning, often requiring team-based collaborative research. This presents a challenge for single researchers due to the labour-intensive nature of the process. Emerging advancements in large language models (LLMs) such as ChatGPT, enhance qualitative…
Descriptors: Artificial Intelligence, Technology Uses in Education, Science Education, Coding
Peer reviewed Peer reviewed
Ha Tien Nguyen; Conrad Borchers; Meng Xia; Vincent Aleven – Grantee Submission, 2024
Intelligent tutoring systems (ITS) can help students learn successfully, yet little work has explored the role of caregivers in shaping that success. Past interventions to support caregivers in supporting their child's homework have been largely disjunct from educational technology. The paper presents prototyping design research with nine middle…
Descriptors: Middle School Mathematics, Intelligent Tutoring Systems, Caregivers, Caregiver Attitudes
Peer reviewed Peer reviewed
Direct linkDirect link
Marcel Mierwald – Journal of Educational Media, Memory and Society, 2024
Generative artificial intelligence (AI) offers new opportunities for history education, such as the ability to chat with historical figures. However, little is known about pupils' interaction with AI applications such as ChatGPT. A qualitative case study was conducted to explore how pupils (n = 21, year nine, fourteen years old) interacted with…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, History Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
C. H., Dhawaleswar Rao; Saha, Sujan Kumar – IEEE Transactions on Learning Technologies, 2023
Multiple-choice question (MCQ) plays a significant role in educational assessment. Automatic MCQ generation has been an active research area for years, and many systems have been developed for MCQ generation. Still, we could not find any system that generates accurate MCQs from school-level textbook contents that are useful in real examinations.…
Descriptors: Multiple Choice Tests, Computer Assisted Testing, Automation, Test Items
Peer reviewed Peer reviewed
Direct linkDirect link
Julia Lademann; Jannik Henze; Sebastian Becker-Genschow – Physical Review Physics Education Research, 2025
This work explores the integration of artificial intelligence (AI) custom chatbots in educational settings, with a particular focus on their applicability in the context of mathematics and physics. In view of the increasing deployment of AI tools such as ChatGPT in educational contexts, the present study explores their potential in generating…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Ching-Huei Chen; Ching-Ling Chang – Education and Information Technologies, 2024
This study aimed to investigate the effectiveness of using AI-assisted game-based learning on science learning outcomes, intrinsic motivation, cognitive load, and learning behavior. A total of 202 seventh graders were recruited and randomly assigned to the following three groups: (1) Game only (N = 70), (2) GameGPT (N = 63), and (3)…
Descriptors: Artificial Intelligence, Game Based Learning, Technology Uses in Education, Science Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Areej ElSayary – Journal of Computer Assisted Learning, 2024
Background: The widespread use of information and communication technology (ICT) has led to significant changes in societal aspects, resulting in the emergence of a "knowledge society." However, students and teachers have faced challenges in adapting to this digitalization. In the United Arab Emirates (UAE), transitioning to a…
Descriptors: Teacher Attitudes, Artificial Intelligence, Information Technology, Barriers
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4