NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 166 to 180 of 1,551 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Aaron Stoller; Chris Schacht – Education and Culture, 2024
The emergence of Large Language Models has exposed composition studies' long-standing commitment to Cartesian assumptions that position writing as a nonmaterial, distinctly human activity. This paper develops a naturalized theory of composition grounded in Deweyan pragmatic naturalism that dissolves the nature/culture dualism embedded in…
Descriptors: Writing (Composition), Artificial Intelligence, Natural Language Processing, Writing Processes
Peer reviewed Peer reviewed
Direct linkDirect link
Kristin Dutcher Mann – History Teacher, 2025
Historians sometimes view teaching and community engagement as peripheral to research. Self-reflection on the design of assignments, pedagogy techniques, and students' work aids teachers as they refine their teaching, and it can also inform research questions and methods. Teaching, research, and community engagement do not have to be separate…
Descriptors: Community Involvement, Authentic Learning, History Instruction, Teaching Methods
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Mengqian Wang; Wenge Guo – ECNU Review of Education, 2025
This review compares generative artificial intelligence with five representative educational technologies in history and concludes that AI technology can become a knowledge producer and thus can be utilized as educative AI to enhance teaching and learning outcomes. From a historical perspective, each technological breakthrough has affected…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, History
West Virginia Department of Education, 2025
This guidance centers around the users of artificial intelligence (AI) in various roles throughout West Virginia PK-12 schools. It is designed to assist individuals such as superintendents, district staff, educators, and support staff in the appropriate and effective use of AI, particularly generative AI technologies, within West Virginia schools.…
Descriptors: Technology Uses in Education, Elementary Secondary Education, Artificial Intelligence, Man Machine Systems
Peer reviewed Peer reviewed
Direct linkDirect link
Brian W. Stone – Teaching of Psychology, 2025
Background: Students in higher education are using generative artificial intelligence (AI) despite mixed messages and contradictory policies. Objective: This study helps answer outstanding questions about many aspects of AI in higher education: familiarity, usage, perceptions of peers, ethical/social views, and AI grading. Method: I surveyed 733…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Peer reviewed Peer reviewed
Direct linkDirect link
Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
Peer reviewed Peer reviewed
Direct linkDirect link
Kevin Peyton; Saritha Unnikrishnan; Brian Mulligan – Discover Education, 2025
Within the university sector, student recruitment and enrolment are key strategies as institutions strive to attract, retain and engage students. This strategy is underpinned by the provision of services, applications and technologies that facilitate lecturing and support staff. Universities that offer online learning have a particular incentive…
Descriptors: Universities, Artificial Intelligence, Computer Mediated Communication, College Students
Peer reviewed Peer reviewed
Direct linkDirect link
Ayse Merzifonluoglu; Habibe Gunes – European Journal of Education, 2025
Artificial intelligence (AI) is significantly shaping education and currently influencing pre-service teachers' academic and professional journeys. To explore this influence, the present study examines 389 Generation Z pre-service teachers' attitudes towards AI and its impact on educational decision-making at two state universities, using an…
Descriptors: Decision Making, Artificial Intelligence, Teacher Attitudes, Age Groups
Peer reviewed Peer reviewed
Direct linkDirect link
Siqi Yi; Soo Young Rieh – Information and Learning Sciences, 2025
Purpose: This paper aims to critically review the intersection of searching and learning among children in the context of voice-based conversational agents (VCAs). This study presents the opportunities and challenges around reconfiguring current VCAs for children to facilitate human learning, generate diverse data to empower VCAs, and assess…
Descriptors: Literature Reviews, Children, Childrens Attitudes, Artificial Intelligence
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Hui Wen Chua; Nagaletchimee Annamalai – International Journal of Technology in Education, 2025
The role of AI chatbots is undergoing a transformation, where it was firstly used for English native language learning; later, it shifted to the use for learning English as a second language (ESL) and English as a foreign language learning. Lastly, it is used to learn foreign languages. Hence, due to the changes in AI chatbots' role, there is a…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, English (Second Language)
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Shimmei, Machi; Matsuda, Noboru – International Educational Data Mining Society, 2023
We propose an innovative, effective, and data-agnostic method to train a deep-neural network model with an extremely small training dataset, called VELR (Voting-based Ensemble Learning with Rejection). In educational research and practice, providing valid labels for a sufficient amount of data to be used for supervised learning can be very costly…
Descriptors: Artificial Intelligence, Training, Natural Language Processing, Educational Research
Peer reviewed Peer reviewed
Direct linkDirect link
Huawei, Shi; Aryadoust, Vahid – Education and Information Technologies, 2023
Automated writing evaluation (AWE) systems are developed based on interdisciplinary research and technological advances such as natural language processing, computer sciences, and latent semantic analysis. Despite a steady increase in research publications in this area, the results of AWE investigations are often mixed, and their validity may be…
Descriptors: Writing Evaluation, Writing Tests, Computer Assisted Testing, Automation
Peer reviewed Peer reviewed
Direct linkDirect link
Suire, Cyrille; Sidère, Nicolas; Doucet, Antoine – Education for Information, 2023
In this article, we introduce an Open Education Resource (OER) on digital historical research with historical newspapers, intended to give students the means to understand the induced risks in working with large collections of digitised documents, as well as the keys to benefit from the advances of natural language processing over large…
Descriptors: Open Educational Resources, Newspapers, Electronic Publishing, Natural Language Processing
Peer reviewed Peer reviewed
Direct linkDirect link
Wang, Wei; Zhao, Yongyong; Wu, Yenchun Jim; Goh, Mark – International Journal of Science Education, Part B: Communication and Public Engagement, 2023
This study analyzed the influence of rhetoric in the endorsement text on the willingness of the crowd to participate in citizen science projects. Four categories of endorsers were studied: professors, students, industrial researchers, and amateur researchers. Using 1243 endorsement texts from 543 citizen science projects as the corpus, the effects…
Descriptors: Citizen Participation, Science Education, Rhetoric, Scientific Research
Peer reviewed Peer reviewed
Direct linkDirect link
Qiao, Chen; Hu, Xiao – IEEE Transactions on Learning Technologies, 2023
Free text answers to short questions can reflect students' mastery of concepts and their relationships relevant to learning objectives. However, automating the assessment of free text answers has been challenging due to the complexity of natural language. Existing studies often predict the scores of free text answers in a "black box"…
Descriptors: Computer Assisted Testing, Automation, Test Items, Semantics
Pages: 1  |  ...  |  8  |  9  |  10  |  11  |  12  |  13  |  14  |  15  |  16  |  ...  |  104