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Showing 1 to 15 of 35 results Save | Export
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Mary Kalantzis; Bill Cope – Reading Research Quarterly, 2025
The latest mutation of Artificial Intelligence, Generative AI, is more than anything a technology of writing. It is a machine that can write. In a world-historical frame, the significance of this cannot be understated. This is a technology in which the unnatural language of code tangles with the natural language of everyday life. Its form of…
Descriptors: Artificial Intelligence, Natural Language Processing, Literacy Education, Technology Uses in Education
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Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
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Atharva Naik; Jessica Ruhan Yin; Anusha Kamath; Qianou Ma; Sherry Tongshuang Wu; R. Charles Murray; Christopher Bogart; Majd Sakr; Carolyn P. Rose – British Journal of Educational Technology, 2025
The relative effectiveness of reflection either through student generation of contrasting cases or through provided contrasting cases is not well-established for adult learners. This paper presents a classroom study to investigate this comparison in a college level Computer Science (CS) course where groups of students worked collaboratively to…
Descriptors: Cooperative Learning, Reflection, College Students, Computer Science Education
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Todd Cherner; Teresa S. Foulger; Margaret Donnelly – TechTrends: Linking Research and Practice to Improve Learning, 2025
The ethics surrounding the development and deployment of generative artificial intelligence (genAI) is an important topic as institutions of higher education adopt the technology for educational purposes. Concurrently, stakeholders from various organizations have reviewed the literature about the ethics of genAI and proposed frameworks about it.…
Descriptors: Artificial Intelligence, Natural Language Processing, Decision Making, Models
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Reese Butterfuss; Harold Doran – Educational Measurement: Issues and Practice, 2025
Large language models are increasingly used in educational and psychological measurement activities. Their rapidly evolving sophistication and ability to detect language semantics make them viable tools to supplement subject matter experts and their reviews of large amounts of text statements, such as educational content standards. This paper…
Descriptors: Alignment (Education), Academic Standards, Content Analysis, Concept Mapping
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Wali Khan Monib; Atika Qazi; Malissa Maria Mahmud – Education and Information Technologies, 2025
ChatGPT has emerged as a transformative technology with its remarkable ability to generate human-like responses, propelling its widespread adoption. While prior research has investigated the general landscape of AI-driven tools such as ChatGPT, the current study focuses specifically on exploring learners' experiences and perceptions regarding the…
Descriptors: Student Attitudes, Student Experience, Artificial Intelligence, Natural Language Processing
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Maria Ijaz Baig; Elaheh Yadegaridehkordi – International Journal of Educational Technology in Higher Education, 2025
Generative Artificial Intelligence (GenAI) tools hold significant promises for enhancing teaching and learning outcomes in higher education. However, continues usage behavior and satisfaction of educators with GenAI systems are still less explored. Therefore, this study aims to identify factors influencing academic staff satisfaction and…
Descriptors: Influences, College Faculty, Satisfaction, Technology Uses in Education
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Ngoc My Bui; Jessie S. Barrot – Education and Information Technologies, 2025
With the generative artificial intelligence (AI) tool's remarkable capabilities in understanding and generating meaningful content, intriguing questions have been raised about its potential as an automated essay scoring (AES) system. One such tool is ChatGPT, which is capable of scoring any written work based on predefined criteria. However,…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
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Sarah Levine; Sarah W. Beck; Chris Mah; Lena Phalen; Jaylen PIttman – Journal of Adolescent & Adult Literacy, 2025
Educators and researchers are interested in ways that ChatGPT and other generative AI tools might move beyond the role of "cheatbot" and become part of the network of resources students use for writing. We studied how high school students used ChatGPT as a writing support while writing arguments about topics like school mascots. We…
Descriptors: Natural Language Processing, Artificial Intelligence, Technology Uses in Education, Writing (Composition)
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Navreet Kaur Rana – Higher Education for the Future, 2025
The article is an exploratory study assessing the stance selected higher education institutes (HEIs) have adopted regarding the usage of generative artificial intelligence (AI) applications in academic research. The HEIs are selected based on purposive sampling in order to showcase different stances they have adopted to curb plagiarism and uphold…
Descriptors: Artificial Intelligence, Technology Uses in Education, Higher Education, Plagiarism
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Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
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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
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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
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Mark A. Flynn – Communication Teacher, 2025
This activity prompts students to go beyond the often reductionist responses to new technologies (e.g. technological determinism) by creating a media literacy-focused infographic about the role, uses, ethical concerns, and/or impact of generative AI (e.g. ChatGPT). Sample topics have included the role of AI in specific industries (e.g. film,…
Descriptors: Artificial Intelligence, Natural Language Processing, Media Literacy, Visual Aids
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Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
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