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Mike Perkins; Jasper Roe; Darius Postma; James McGaughran; Don Hickerson – Journal of Academic Ethics, 2024
This study explores the capability of academic staff assisted by the Turnitin Artificial Intelligence (AI) detection tool to identify the use of AI-generated content in university assessments. 22 different experimental submissions were produced using Open AI's ChatGPT tool, with prompting techniques used to reduce the likelihood of AI detectors…
Descriptors: Artificial Intelligence, Student Evaluation, Identification, Natural Language Processing
Mengjiao Zhang – ProQuest LLC, 2024
The rise of Artificial Intelligence technology has raised concerns about the potential compromise of privacy due to the handling of personal data. Private AI prevents cybercrimes and falsehoods and protects human freedom and trust. While Federated Learning offers a solution by model training across decentralized devices or servers, thereby…
Descriptors: Privacy, Cooperative Learning, Natural Language Processing, Learning Processes
Da-Wei Zhang; Melissa Boey; Yan Yu Tan; Alexis Hoh Sheng Jia – npj Science of Learning, 2024
This study evaluates the ability of large language models (LLMs) to deliver criterion-based grading and examines the impact of prompt engineering with detailed criteria on grading. Using well-established human benchmarks and quantitative analyses, we found that even free LLMs achieve criterion-based grading with a detailed understanding of the…
Descriptors: Artificial Intelligence, Natural Language Processing, Criterion Referenced Tests, Grading
Beatriz Carbajal-Carrera – Australian Review of Applied Linguistics, 2024
The growing implementation of Generative AI (GenAI) in education has implications on the representation of knowledge and identity across languages. In a context where content biases have been reported in AI-generated content, it becomes relevant to interrogate the ways in which AI technologies represent different linguistic identities. This…
Descriptors: Artificial Intelligence, Sociolinguistics, Language Usage, Bias
Li Chen; Gen Li; Boxuan Ma; Cheng Tang; Masanori Yamada – International Association for Development of the Information Society, 2024
This paper proposes a three-step approach to develop knowledge graphs that integrate textbook-based target knowledge graph with student dialogue-based knowledge graphs. The study was conducted in seventh-grade STEM classes, following a collaborative problem solving process. First, the proposed approach generates a comprehensive target knowledge…
Descriptors: Concept Mapping, Graphs, Cooperative Learning, Problem Solving
Mishra, Swaroop – ProQuest LLC, 2023
Humans have the remarkable ability to solve different tasks by simply reading textual instructions that define the tasks and looking at a few examples. Natural Language Processing (NLP) models built with the conventional machine learning paradigm, however, often struggle to generalize across tasks (e.g., a question-answering system cannot solve…
Descriptors: Natural Language Processing, Models, Readability, Mathematical Logic
Debora Weber-Wulff; Alla Anohina-Naumeca; Sonja Bjelobaba; Tomáš Foltýnek; Jean Guerrero-Dib; Olumide Popoola; Petr Šigut; Lorna Waddington – International Journal for Educational Integrity, 2023
Recent advances in generative pre-trained transformer large language models have emphasised the potential risks of unfair use of artificial intelligence (AI) generated content in an academic environment and intensified efforts in searching for solutions to detect such content. The paper examines the general functionality of detection tools for…
Descriptors: Artificial Intelligence, Identification, Man Machine Systems, Accuracy
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
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
Gamze Türkmen – Journal of Educational Computing Research, 2025
Explainable Artificial Intelligence (XAI) refers to systems that make AI models more transparent, helping users understand how outputs are generated. XAI algorithms are considered valuable in educational research, supporting outcomes like student success, trust, and motivation. Their potential to enhance transparency and reliability in online…
Descriptors: Artificial Intelligence, Natural Language Processing, Trust (Psychology), Electronic Learning
Phil Seok Oh; Gyeong-Geon Lee – Science & Education, 2025
How and why science education scholars and practitioners might use artificial intelligence (AI) in the classroom has been a controversial agenda for decades. ChatGPT, a state-of-the-art (SOTA) AI released in November 2022, has attracted global interest for its exceptionally high performance in generating human-like natural language answers to…
Descriptors: Science Education, Artificial Intelligence, Cognitive Processes, Affective Behavior
Pierre-Alexandre Balland; Olesya Grabova; J. Scott Marcus; Robert Praas; Andrea Renda – European Union, 2025
This report examines the burgeoning generative artificial intelligence (GenAI) and foundation models landscape within the European Union, and analyses its impact, technological advancements, and regulatory implications. It details the GenAI value chain, identifying key players and investment trends, revealing a significant US dominance. The report…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Industry
Helen Crompton; Diane Burke – TechTrends: Linking Research and Practice to Improve Learning, 2024
ChatGPT was released to the public in November 30, 2022. This study examines how ChatGPT can be used by educators and students to promote learning and what are the challenges and limitations. This study is unique in providing one of the first systematic reviews using peer review studies to provide an early examination of the field. Using PRISMA…
Descriptors: Artificial Intelligence, Barriers, Technology Uses in Education, Natural Language Processing
Gloria Gagliardi – International Journal of Language & Communication Disorders, 2024
Background: In the past few years there has been a growing interest in the employment of verbal productions as digital biomarkers, namely objective, quantifiable behavioural data that can be collected and measured by means of digital devices, allowing for a low-cost pathology detection, classification and monitoring. Numerous research papers have…
Descriptors: Natural Language Processing, Language Research, Pathology, Aging (Individuals)
Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction