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Javad Keyhan – International Journal of Technology in Education and Science, 2025
In recent years, remarkable advancements in artificial intelligence technology have created new opportunities for transforming educational systems and enhancing student learning. This study focuses on designing a model for an AI-based intelligent assistant to provide a personalized learning experience in higher education. A qualitative approach…
Descriptors: Individualized Instruction, Artificial Intelligence, Models, Higher 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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Habeeb Yusuf; Arthur Money; Damon Daylamani-Zad – Educational Technology Research and Development, 2025
The ever-changing global educational landscape, coupled with the advancement of Web3, is seeing rapid changes in the ways pedagogical artificially intelligent conversational agents are being developed and used to advance teaching and learning in higher education. Given the rapidly evolving research landscape, there is a need to establish what the…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Higher Education
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Muhammad Bilal Saqib; Saba Zia – Journal of Applied Research in Higher Education, 2025
Purpose: The notion of using a generative artificial intelligence (AI) engine for text composition has gained excessive popularity among students, educators and researchers, following the introduction of ChatGPT. However, this has added another dimension to the daunting task of verifying originality in academic writing. Consequently, the market…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Evaluation
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Valentine Joseph Owan; Ibrahim Abba Mohammed; Ahmed Bello; Tajudeen Ahmed Shittu – Contemporary Educational Technology, 2025
Despite the increasing interest in artificial intelligence technologies in education, there is a gap in understanding the factors influencing the adoption of ChatGPT among Nigerian higher education students. Research has not comprehensively explored these factors in the Nigerian context, leaving a significant gap in understanding technology…
Descriptors: Student Behavior, Foreign Countries, Artificial Intelligence, Natural Language Processing
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Michel C. Desmarais; Arman Bakhtiari; Ovide Bertrand Kuichua Kandem; Samira Chiny Folefack Temfack; Chahé Nerguizian – International Educational Data Mining Society, 2025
We propose a novel method for automated short answer grading (ASAG) designed for practical use in real-world settings. The method combines LLM embedding similarity with a nonlinear regression function, enabling accurate prediction from a small number of expert-graded responses. In this use case, a grader manually assesses a few responses, while…
Descriptors: Grading, Automation, Artificial Intelligence, Natural Language Processing
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Shamola Pramjeeth; Priya Ramgovind – New Directions for Teaching and Learning, 2025
While AI has the potential to streamline assessment development in higher education, there are concerns about its reliability, fairness, and potential to perpetuate bias. This study sought to understand the perceptions of academics and teaching and learning (T&L) specialists on the use of AI tools and large language models on assessment…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Educational Assessment
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Berrin Cefa; Felicitas Macgilchrist; Hebatullah ElGamal; John Y. H. Bai; Olaf Zawacki-Richter; Frank S. Loglo – Open Praxis, 2025
Immediately after its public launch in November 2022, ChatGPT quickly gained widespread attention across various research fields, including education. The excitement surrounding ChatGPT is not an isolated event as education experienced other innovations that heralded the novelty as a potential game-changer in learner support and teaching. Open,…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Darius Hennekeuser; Daryoush Daniel Vaziri; David Golchinfar; Dirk Schreiber; Gunnar Stevens – International Journal of Artificial Intelligence in Education, 2025
Large Language Models (LLMs) are rapidly gaining attention across the open-source and commercial fields, bolstered by their constantly growing capabilities. While such models have a vast array of applications, their integration into higher education--as supportive tools for lecturers--has been largely unexplored. Exploring this area entails…
Descriptors: Lecture Method, College Instruction, Higher Education, College Faculty
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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; Constanze Richters; Amadeus J. Pickal; Moritz Klippert; Michael Sailer; Matthias Stadler – British Journal of Educational Technology, 2025
This study explores whether AI-generated adaptive feedback or static feedback is favourable for student interest and performance outcomes in learning statistics in a digital learning environment. Previous studies have favoured adaptive feedback over static feedback for skill acquisition, however, without investigating the outcome of students'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Feedback (Response), Statistics Education
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Juan-Manuel Aguado-García; Sara Alonso-Muñoz; Carmen De-Pablos-Heredero – SAGE Open, 2025
Artificial intelligence plays an important role in higher education, helping to manage centres and students' educational pathways, and acting as a valuable tool for both professors and scholars. However, its use in education is still at an early stage of development. Despite the notable increase in the number of publications and the growing…
Descriptors: Artificial Intelligence, Higher Education, Technology Uses in Education, Educational Research
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Fiachra Long – Studies in Philosophy and Education, 2025
Conversation of a particular sort holds the key to learning. I argue here that peer to peer conversation promotes two features that are essential to progressive learning, namely 'contestation' and 'communication.' Traditional learning is principally concerned with whether students have reached a standard of knowledge and skill prescribed by some…
Descriptors: Artificial Intelligence, Natural Language Processing, Intelligent Tutoring Systems, Peer Relationship
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Victor-Alexandru Padurean; Tung Phung; Nachiket Kotalwar; Michael Liut; Juho Leinonen; Paul Denny; Adish Singla – International Educational Data Mining Society, 2025
The growing need for automated and personalized feedback in programming education has led to recent interest in leveraging generative AI for feedback generation. However, current approaches tend to rely on prompt engineering techniques in which predefined prompts guide the AI to generate feedback. This can result in rigid and constrained responses…
Descriptors: Automation, Student Writing Models, Feedback (Response), Programming
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Mickie De Wet; Margarita Oja Da Silva; René Bohnsack – Innovations in Education and Teaching International, 2025
This study explores the use of large language models (LLMs) to generate feedback on essay-type assignments in Higher Education. Drawing on a seminal feedback framework, it examines the pedagogical and psychological effectiveness of LLM-generated feedback across three cohorts of MBA, MSc, and undergraduate students. Methods included linguistic…
Descriptors: Higher Education, College Students, Artificial Intelligence, Writing Evaluation
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