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M. Anthony Machin; Tanya M. Machin; Natalie Gasson – Psychology Learning and Teaching, 2024
Progress in understanding students' development of psychological literacy is critical. However, generative AI represents an emerging threat to higher education which may dramatically impact on student learning and how this learning transfers to their practice. This research investigated whether ChatGPT responded in ways that demonstrated…
Descriptors: Psychology, Higher Education, Artificial Intelligence, Intelligent Tutoring Systems
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Tamar Mikeladze; Paulien C. Meijer; Roald P. Verhoeff – European Journal of Education, 2024
Recent literature underscores the need for teachers to develop AI competencies with a recognition of the current lack of well-defined competence frameworks. This critical review investigates teachers' Artificial Intelligence (AI) competence frameworks (AI CFTs), analysing their strengths, weaknesses and practical applications for researchers,…
Descriptors: Artificial Intelligence, Digital Literacy, Teacher Competencies, Faculty Development
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Ferrara, Steve; Qunbar, Saed – Journal of Educational Measurement, 2022
In this article, we argue that automated scoring engines should be transparent and construct relevant--that is, as much as is currently feasible. Many current automated scoring engines cannot achieve high degrees of scoring accuracy without allowing in some features that may not be easily explained and understood and may not be obviously and…
Descriptors: Artificial Intelligence, Scoring, Essays, Automation
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Cohausz, Lea – International Educational Data Mining Society, 2022
Despite calls to increase the focus on explainability and interpretability in EDM and, in particular, student success prediction, so that it becomes useful for personalized intervention systems, only few efforts have been undertaken in that direction so far. In this paper, we argue that this is mainly due to the limitations of current Explainable…
Descriptors: Success, Prediction, Social Sciences, Artificial Intelligence
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Stephen J. Lind – Journal of Workplace Learning, 2025
Purpose: This study aims to investigate the effectiveness of widely adopted but under-studied synthetic humanlike spokespersons (SHS) compared to organic human spokespersons in workplace training videos. The primary aim is to evaluate whether employees will rate training videos more negatively when they perceive their trainer to be synthetic such…
Descriptors: Job Training, Trainees, Artificial Intelligence, Video Technology
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Jiahong Su – Education and Information Technologies, 2025
Although artificial intelligence (AI) is becoming more commonly integrated into our everyday lives, homes, and schools, there needs to be more research regarding parental attitudes toward using AI technologies and AI literacy education to understand better and advance AI and AI literacy in kindergarten. To address this gap, this study explored…
Descriptors: Foreign Countries, Kindergarten, Young Children, Parent Attitudes
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Smriti Mathur; Vandana Anand; Durgansh Sharma; Sushant Kr. Vishnoi – International Journal of Information and Learning Technology, 2025
Purpose: ChatGPT, a cutting-edge language model, stands as an unparalleled, unmatched conversational ally, showcasing novel versatility and intelligence in its responses. This research delves into the incorporation of ChatGPT, a powerful generative AI tool, into professional communication. This study utilizes the information system success model…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, Influence of Technology
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Nguyen, Andy; Ngo, Ha Ngan; Hong, Yvonne; Dang, Belle; Nguyen, Bich-Phuong Thi – Education and Information Technologies, 2023
The advancement of artificial intelligence in education (AIED) has the potential to transform the educational landscape and influence the role of all involved stakeholders. In recent years, the applications of AIED have been gradually adopted to progress our understanding of students' learning and enhance learning performance and experience.…
Descriptors: Ethics, Artificial Intelligence, Educational Policy, Privacy
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Liang, Zibo; Mu, Lan; Chen, Jie; Xie, Qing – Education and Information Technologies, 2023
In recent years, online learning methods have gradually been accepted by more and more people. A large number of online teaching courses and other resources (MOOCs) have also followed. To attract students' interest in learning, many scholars have built recommendation systems for MOOCs. However, students need a variety of different learning…
Descriptors: MOOCs, Artificial Intelligence, Graphs, Educational Resources
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Belzak, William C. M. – Educational Measurement: Issues and Practice, 2023
Test developers and psychometricians have historically examined measurement bias and differential item functioning (DIF) across a single categorical variable (e.g., gender), independently of other variables (e.g., race, age, etc.). This is problematic when more complex forms of measurement bias may adversely affect test responses and, ultimately,…
Descriptors: Test Bias, High Stakes Tests, Artificial Intelligence, Test Items
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Kumar, Rahul – International Journal for Educational Integrity, 2023
This paper presents the case of an adjunct university professor to illustrate the dilemma of using artificial intelligence (AI) technology to grade student papers. The hypothetical case discusses the benefits of using a commercial AI service to grade student papers--including discretion, convenience, pedagogical merits of consistent feedback for…
Descriptors: College Faculty, Artificial Intelligence, Grading, Research Papers (Students)
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Ingrisone, Soo Jeong; Ingrisone, James N. – Educational Measurement: Issues and Practice, 2023
There has been a growing interest in approaches based on machine learning (ML) for detecting test collusion as an alternative to the traditional methods. Clustering analysis under an unsupervised learning technique appears especially promising to detect group collusion. In this study, the effectiveness of hierarchical agglomerative clustering…
Descriptors: Identification, Cooperation, Computer Assisted Testing, Artificial Intelligence
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Matthews, Benjamin; Shannon, Barrie; Roxburgh, Mark – International Journal of Art & Design Education, 2023
Digital automation is on the rise in a diverse range of industries. The technologies employed here often make use of artificial intelligence (AI) and its common form, machine learning (ML) to augment or replace the work completed by human agents. The recent emergence of a variety of design automation platforms inspired the authors to undertake a…
Descriptors: Artificial Intelligence, Automation, Design, Electronic Learning
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Kubsch, Marcus; Krist, Christina; Rosenberg, Joshua M. – Journal of Research in Science Teaching, 2023
Machine learning (ML) has become commonplace in educational research and science education research, especially to support assessment efforts. Such applications of machine learning have shown their promise in replicating and scaling human-driven codes of students' work. Despite this promise, we and other scholars argue that machine learning has…
Descriptors: Science Education, Educational Research, Artificial Intelligence, Models
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Albornoz-De Luise, Romina Soledad; Arevalillo-Herraez, Miguel; Arnau, David – IEEE Transactions on Learning Technologies, 2023
In this article, we analyze the potential of conversational frameworks to support the adaptation of existing tutoring systems to a natural language form of interaction. We have based our research on a pilot study, in which the open-source machine learning framework Rasa has been used to build a conversational agent that interacts with an existing…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Artificial Intelligence, Models
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