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Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
Steffen Steinert; Karina E. Avila; Stefan Ruzika; Jochen Kuhn; Stefan Küchemann – Smart Learning Environments, 2024
Effectively supporting students in mastering all facets of self-regulated learning is a central aim of teachers and educational researchers. Prior research could demonstrate that formative feedback is an effective way to support students during self-regulated learning. In this light, we propose the application of Large Language Models (LLMs) to…
Descriptors: Formative Evaluation, Feedback (Response), Natural Language Processing, Artificial Intelligence
Kudzayi Savious Tarisayi – Cogent Education, 2024
As artificial intelligence proliferates, so do associated hopes and fears. This study explores such tensions within South African higher education following ChatGPT's launch, analyzing perceived threats alongside opportunities for responsibly harnessing benefits. Adopting a socio-technical framework recognizing technology's interdependence with…
Descriptors: Foreign Countries, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Leen Adel Gammoh – Journal of Further and Higher Education, 2024
ChatGPT, a user-friendly and accessible AI tool, offers a revolutionary approach to academic learning. In spite of its benefits, the implementation of ChatGPT into university assignments presents possible risks for students. While extensive global research has studied these risks from students' perspectives, a notable gap exists in comprehending…
Descriptors: Artificial Intelligence, Natural Language Processing, Risk, Barriers
Tianyuan Yang; Baofeng Ren; Chenghao Gu; Boxuan Ma; Shin 'ichi Konomi – International Association for Development of the Information Society, 2024
As education increasingly shifts towards a technology-driven model, artificial intelligence systems like ChatGPT are gaining recognition for their potential to enhance educational support. In university education and MOOC environments, students often select courses that align with their specific needs. During this process, access to information…
Descriptors: Concept Formation, Artificial Intelligence, Computer Uses in Education, MOOCs
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
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
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
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
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
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