Publication Date
| In 2026 | 0 |
| Since 2025 | 317 |
| Since 2022 (last 5 years) | 949 |
| Since 2017 (last 10 years) | 1256 |
| Since 2007 (last 20 years) | 1620 |
Descriptor
Source
Author
Publication Type
Education Level
Audience
| Teachers | 14 |
| Researchers | 11 |
| Administrators | 4 |
| Policymakers | 4 |
| Practitioners | 3 |
| Students | 3 |
| Counselors | 1 |
| Parents | 1 |
| Support Staff | 1 |
Location
| China | 47 |
| Australia | 30 |
| Germany | 27 |
| United Kingdom | 23 |
| Turkey | 21 |
| Canada | 20 |
| Spain | 20 |
| Taiwan | 19 |
| United States | 19 |
| Hong Kong | 15 |
| Pennsylvania | 14 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Yusuf Oc; Chahna Gonsalves; La Toya Quamina – Journal of Marketing Education, 2025
The integration of generative artificial intelligence (AI) tools is a paradigm shift in enhanced learning methodologies and assessment techniques. This study explores the adoption of generative AI tools in higher education assessments by examining the perceptions of 353 students through a survey and 17 in-depth interviews. Anchored in the Unified…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Zi Yang; Junjie Gavin Wu; Haoran Xie – Asia Pacific Journal of Education, 2025
The emergence of generative artificial intelligence (GAI) in the past two years is exerting profound effects throughout society. However, while this new technology undoubtedly promises substantial benefits, its disruptive nature also means that it poses a variety of challenges. The field of education is no exception. This position paper intends to…
Descriptors: Artificial Intelligence, Ethics, Technology Uses in Education, Natural Language Processing
Christopher Mah; Mei Tan; Lena Phalen; Alexa Sparks; Dorottya Demszky – Annenberg Institute for School Reform at Brown University, 2025
Effective writing feedback is a powerful tool for enhancing student learning, encouraging revision, and increasing motivation and agency. Yet, teachers face many challenges that prevent them from consistently providing effective writing feedback. Recent advances in generative artificial intelligence (AI) have led educators and researchers to…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Writing Evaluation
Sedat Yigit; Soner Berse; Ezgi Dirgar; Seçil Gülhan Güner – Innovations in Education and Teaching International, 2025
Artificial Intelligence (AI) has significantly impacted the field of education, particularly in health sciences, where tools such as ChatGPT are increasingly utilised. ChatGPT, powered by AI, presents both opportunities and challenges that warrant investigation. This qualitative study explored the perceptions, experiences, and expectations of…
Descriptors: Undergraduate Students, Student Attitudes, Allied Health Occupations Education, Artificial Intelligence
Deliang Wang; Gaowei Chen – British Journal of Educational Technology, 2025
Classroom dialogue is crucial for effective teaching and learning, prompting many professional development (PD) programs to focus on dialogic pedagogy. Traditionally, these programs rely on manual analysis of classroom practices, which limits timely feedback to teachers. To address this, artificial intelligence (AI) has been employed for rapid…
Descriptors: Classroom Communication, Artificial Intelligence, Technology Uses in Education, Models
Snekha, S.; Ayyanathan, N. – Shanlax International Journal of Education, 2023
An educational customer relationship management (CRM) Chatbot is a learner support service automation tool that enhances the human computer interaction and user experience in higher education institutions through effective online conversation and information exchange. The machine with embedded knowledge is trained to identify the sentences and…
Descriptors: Computer Software, Learning Management Systems, Educational Technology, Man Machine Systems
Dianova, Vera G.; Schultz, Mario D. – Industry and Higher Education, 2023
This comment builds on the example of chat generative pretrained transformer (ChatGPT) to discuss the implications of generative AI on industry and higher education, underlining the need for more transdisciplinary digital literacy education. The release of ChatGPT has generated significant academic and professional interest and instigated a…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Industry
Ryan Daniel Budnick – ProQuest LLC, 2023
The past thirty years have shown a rise in models of language acquisition in which the state of the learner is characterized as a probability distribution over a set of non-stochastic grammars. In recent years, increasingly powerful models have been constructed as earlier models have failed to generalize well to increasingly complex and realistic…
Descriptors: Grammar, Feedback (Response), Algorithms, Computational Linguistics
Fan Ouyang; Tuan Anh Dinh; Weiqi Xu – Journal for STEM Education Research, 2023
Artificial intelligence (AI), as an emerging technology, has been widely used in STEM education to promote the educational assessment. Although AI-driven educational assessment has the potential to assess students' learning automatically and reduce the workload of instructors, there is still a lack of review works to holistically examine the field…
Descriptors: Educational Assessment, Artificial Intelligence, STEM Education, Academic Achievement
Laura K. Allen; Arthur C. Grasser; Danielle S. McNamara – Grantee Submission, 2023
Assessments of natural language can provide vast information about individuals' thoughts and cognitive process, but they often rely on time-intensive human scoring, deterring researchers from collecting these sources of data. Natural language processing (NLP) gives researchers the opportunity to implement automated textual analyses across a…
Descriptors: Psychological Studies, Natural Language Processing, Automation, Research Methodology
Dragos Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2023
Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…
Descriptors: Reading Comprehension, Models, Concept Mapping, Graphs
Muhsin Menekse – Grantee Submission, 2023
Generative artificial intelligence (AI) technologies, such as large language models (LLMs) and diffusion model image and video generators, can transform learning and teaching experiences by providing students and instructors with access to a vast amount of information and create innovative learning and teaching materials in a very efficient way…
Descriptors: Educational Trends, Engineering Education, Artificial Intelligence, Technology Uses in Education
Debby R. E. Cotton; Peter A. Cotton; J. Reuben Shipway – Innovations in Education and Teaching International, 2024
The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of…
Descriptors: Integrity, Cheating, Artificial Intelligence, Man Machine Systems
Jin Mao; Baiyun Chen; Juhong Christie Liu – TechTrends: Linking Research and Practice to Improve Learning, 2024
The abrupt emergence and rapid advancement of generative artificial intelligence (AI) technologies, transitioning from research labs to potentially all aspects of social life, has brought a profound impact on education, science, arts, journalism, and every facet of human life and communication. The purpose of this paper is to recapitulate the use…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Electronic Learning
Huiying Cai; Xun Yan – Language Testing, 2024
Rater comments tend to be qualitatively analyzed to indicate raters' application of rating scales. This study applied natural language processing (NLP) techniques to quantify meaningful, behavioral information from a corpus of rater comments and triangulated that information with a many-facet Rasch measurement (MFRM) analysis of rater scores. The…
Descriptors: Natural Language Processing, Item Response Theory, Rating Scales, Writing Evaluation

Peer reviewed
Direct link
