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Anthony G. Picciano – Online Learning, 2024
Artificial intelligence (AI) has been evolving since the mid-twentieth-century when luminaries such as Alan Turing, Herbert Simon, and Marvin Minsky began developing rudimentary AI applications. For decades, AI programs remained pretty much in the realm of computer science and experimental game playing. This changed radically in the 2020s when…
Descriptors: Teacher Education, Seminars, Technology Uses in Education, Artificial Intelligence
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David R. Firth; Mason Derendinger; Jason Triche – Information Systems Education Journal, 2024
In this paper we describe a framework for teaching students when they should, or should not use generative AI such as ChatGPT. Generative AI has created a fundamental shift in how students can complete their class assignments, and other tasks such as building resumes and creating cover letters, and we believe it is imperative that we teach…
Descriptors: Cheating, Artificial Intelligence, Man Machine Systems, Natural Language Processing
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Mehdi Darban – Education and Information Technologies, 2024
This study advances the understanding of Artificial Intelligence (AI)'s role, particularly that of conversational agents like ChatGPT, in augmenting team-based knowledge acquisition in virtual learning settings. Drawing on human-AI teams and anthropomorphism theories and addressing the gap in the literature on human-AI collaboration within virtual…
Descriptors: Artificial Intelligence, Influence of Technology, Group Instruction, Electronic Learning
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Raj Sandu; Ergun Gide; Mahmoud Elkhodr – Discover Education, 2024
Artificial intelligence (AI) tools, notably ChatGPT, are increasingly recognised for their transformative potential in higher education. This study employs a detailed case study approach complemented by a survey, delving into ChatGPT's impact on pedagogical practices, student engagement, and academic performance. It involved 74 undergraduate and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Foreign Countries
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Anna Dillon; Geraldine Chell; Nusaibah Al Ameri; Nahla Alsayed; Yusra Salem; Moss Turner; Kay Gallagher – Journal of Educators Online, 2024
This paper shares the reflections of a small group of graduate students and faculty members in the United Arab Emirates (UAE) on the challenges and affordances of using large language model (LLM) tools to assist with academic writing in an English Medium Education (EME) context. The influence of interpretive grounded theory afforded the authors…
Descriptors: Academic Language, Artificial Intelligence, Man Machine Systems, Natural Language Processing
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Zhang, Ruofei; Zou, Di; Cheng, Gary – Innovation in Language Learning and Teaching, 2023
EFL learners generally have the problem of logical fallacies in EFL argumentative writings. Logical fallacies are errors in reasoning that can undermine EFL argumentative writing quality. Explicit training on logical fallacies may help learners deal with the problem and enhance their self-efficacy and proficiency in EFL argumentative writing,…
Descriptors: English (Second Language), Second Language Learning, Persuasive Discourse, Writing Instruction
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Stefan Küchemann; Steffen Steinert; Natalia Revenga; Matthias Schweinberger; Yavuz Dinc; Karina E. Avila; Jochen Kuhn – Physical Review Physics Education Research, 2023
The recent advancement of large language models presents numerous opportunities for teaching and learning. Despite widespread public debate regarding the use of large language models, empirical research on their opportunities and risks in education remains limited. In this work, we demonstrate the qualities and shortcomings of using ChatGPT 3.5…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Physics
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Charlotte N. Gunawardena; Yan Chen; Nick Flor; Damien Sánchez – Online Learning, 2023
Gunawardena et al.'s (1997) Interaction Analysis Model (IAM) is one of the most frequently employed frameworks to guide the qualitative analysis of social construction of knowledge online. However, qualitative analysis is time consuming, and precludes immediate feedback to revise online courses while being delivered. To expedite analysis with a…
Descriptors: Models, Learning Processes, Knowledge Level, Online Courses
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Fiebrink, Rebecca – ACM Transactions on Computing Education, 2019
This article aims to lay a foundation for the research and practice of machine learning education for creative practitioners. It begins by arguing that it is important to teach machine learning to creative practitioners and to conduct research about this teaching, drawing on related work in creative machine learning, creative computing education,…
Descriptors: Artificial Intelligence, Man Machine Systems, Population Groups, Creativity
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers