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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
Susan Shurden; Mike Shurden – Journal of Instructional Pedagogies, 2024
Artificial Intelligence (AI) is taking the world by storm. Higher education is not immune to this phenomenon and has many challenges in embracing AI. Much has been written lately concerning the typical application of AI in higher education, as well as in the classroom itself. The purpose of this paper is to gather information from students to…
Descriptors: Artificial Intelligence, Higher Education, College Students, Student Attitudes
Taskeen Hasrod; Yannick B. Nuapia; Hlanganani Tutu – Journal of Chemical Education, 2024
In order to improve the accessibility and user friendliness of an accurately pretrained stacking ensemble machine learning regressor used to predict sulfate levels (mg/L) in Acid Mine Drainage (AMD), a Graphical User Interface (GUI) was developed using Python by combining human input with ChatGPT and deployed in the Jupyter Notebook environment.…
Descriptors: Artificial Intelligence, Natural Language Processing, Educational Technology, Computer Software
Dadi Ramesh; Suresh Kumar Sanampudi – European Journal of Education, 2024
Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…
Descriptors: Scoring, Essays, Writing Evaluation, Memory
Videep Venkatesha; Abhijnan Nath; Ibrahim Khebour; Avyakta Chelle; Mariah Bradford; Jingxuan Tu; James Pustejovsky; Nathaniel Blanchard; Nikhil Krishnaswamy – International Educational Data Mining Society, 2024
In the realm of collaborative learning, extracting the beliefs shared within a group is paramount, especially when navigating complex tasks. Inherent in this problem is the fact that in naturalistic collaborative discourse, the same propositions may be expressed in radically different ways. This difficulty is exacerbated when speech overlaps and…
Descriptors: Cooperative Learning, Dialogs (Language), Language Usage, Artificial Intelligence
Wenhao Wang; Etsuko Kumamoto; Chengjiu Yin – International Educational Data Mining Society, 2024
The e-book system, widely used in learning and teaching, has generated a large amount of log data over time. Researchers analyzing these data have discovered the existence of student's jump back behavior, which is positively correlated with academic achievement. However, they also found that this behavior has the disadvantage of low efficiency. To…
Descriptors: Electronic Books, Natural Language Processing, Artificial Intelligence, Reading
R., Akila Devi T.; Sathick, K. Javubar; Khan, A. Abdul Azeez; Raj, L. Arun – International Journal of Web-Based Learning and Teaching Technologies, 2021
Non-Factoid Question Answering (QA) is the next generation of textual QA systems, which gives passage level summaries for a natural language query, posted by the user. The main issue lies in the appropriateness of the generated summary. This paper proposes a framework for non-factoid QA system, which has three main components: (1) a deep neural…
Descriptors: Natural Language Processing, Artificial Intelligence, Classification, Responses
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
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
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
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
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
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
Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
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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