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Hosseini, Mohammad; Resnik, David B.; Holmes, Kristi – Research Ethics, 2023
In this article, we discuss ethical issues related to using and disclosing artificial intelligence (AI) tools, such as ChatGPT and other systems based on large language models (LLMs), to write or edit scholarly manuscripts. Some journals, such as "Science," have banned the use of LLMs because of the ethical problems they raise concerning…
Descriptors: Ethics, Artificial Intelligence, Computational Linguistics, Natural Language Processing
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Mayer, Christian W. F.; Ludwig, Sabrina; Brandt, Steffen – Journal of Research on Technology in Education, 2023
This study investigates the potential of automated classification using prompt-based learning approaches with transformer models (large language models trained in an unsupervised manner) for a domain-specific classification task. Prompt-based learning with zero or few shots has the potential to (1) make use of artificial intelligence without…
Descriptors: Prompting, Classification, Artificial Intelligence, Natural Language Processing
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Botelho, Anthony; Baral, Sami; Erickson, John A.; Benachamardi, Priyanka; Heffernan, Neil T. – Journal of Computer Assisted Learning, 2023
Background: Teachers often rely on the use of open-ended questions to assess students' conceptual understanding of assigned content. Particularly in the context of mathematics; teachers use these types of questions to gain insight into the processes and strategies adopted by students in solving mathematical problems beyond what is possible through…
Descriptors: Natural Language Processing, Artificial Intelligence, Computer Assisted Testing, Mathematics Tests
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Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
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Émilie Laplante; Valérie Geraghty; Emalie Hendel; René-Pierre Sonier; Dominic Guitard; Jean Saint-Aubin – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
When readers are asked to detect a target letter while reading for comprehension, they miss it more frequently when it is embedded in a frequent function word than in a less frequent content word. This missing-letter effect has been used to investigate the cognitive processes involved in reading. A similar effect, called the missing-phoneme effect…
Descriptors: Auditory Perception, Written Language, Phonemes, Morphology (Languages)
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Ali, Farhan; Choy, Doris; Divaharan, Shanti; Tay, Hui Yong; Chen, Wenli – Learning: Research and Practice, 2023
Self-directed learning and self-assessment require student responsibility over learning needs, goals, processes, and outcomes. However, this student-led learning can be challenging to achieve in a classroom limited by a one-to-many teacher-led instruction. We, thus, have designed and prototyped a generative artificial intelligence chatbot…
Descriptors: Independent Study, Self Evaluation (Individuals), Artificial Intelligence, Man Machine Systems
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Andrew M. Olney – Grantee Submission, 2023
Multiple choice questions are traditionally expensive to produce. Recent advances in large language models (LLMs) have led to fine-tuned LLMs that generate questions competitive with human-authored questions. However, the relative capabilities of ChatGPT-family models have not yet been established for this task. We present a carefully-controlled…
Descriptors: Test Construction, Multiple Choice Tests, Test Items, Algorithms
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Johannes Cronjé – Electronic Journal of e-Learning, 2023
This paper describes the results of an archival desk-study that analyzed worksheets produced by four students using ChatGPT as a coach. ChatGPT is a Generative Pre-Trained Large Language model that can write comprehensively in various languages and styles. It was discovered that it could pass university level physics exams and perform at the level…
Descriptors: Natural Language Processing, Research Proposals, Artificial Intelligence, Research Methodology
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Stephen J. McElroy; Kristi Girdharry – Business and Professional Communication Quarterly, 2024
Drawing upon a framework of "assemblage thinking," this article offers an approach to considering artificial intelligence (AI) and ethics that seeks to think relationally across the positions occupied as educators and students at a business school. To complement discussions of assemblage and examinations of ethics in the AI era, we draw…
Descriptors: Ethics, Artificial Intelligence, Undergraduate Students, Undergraduate Study
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Omar Albaloul; Risto Marttinen; Chad Killian – Journal of Physical Education, Recreation & Dance, 2024
The recent emergence of artificial intelligence (AI) tools has significantly influenced different fields, including education. One notable example is ChatGPT, an AI-driven large language model (LLM) developed by OpenAI. This tool holds potential for supporting both teachers and students in the teaching and learning process. While some fields of…
Descriptors: Physical Education, Artificial Intelligence, Natural Language Processing, Man Machine Systems
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Ali Rashed Ibraheam Almohesh – International Review of Research in Open and Distributed Learning, 2024
In education, the integration of artificial intelligence (AI) has presented opportunities to transform the dynamics of online learning. This study investigated the impact of an AI-powered application, namely ChatGPT, on the autonomy of Saudi Arabian primary students participating in online classes. It also explored how the implementation of Chat…
Descriptors: Artificial Intelligence, Natural Language Processing, Foreign Countries, Elementary Schools
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Lingyao Li; Zihui Ma; Lizhou Fan; Sanggyu Lee; Huizi Yu; Libby Hemphill – Education and Information Technologies, 2024
The rapid advancements in generative AI models present new opportunities in the education sector. However, it is imperative to acknowledge and address the potential risks and concerns that may arise with their use. We analyzed Twitter data to identify critical concerns related to the use of ChatGPT in education. We employed BERT-based topic…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Social Media
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Gyeong-Geon Lee; Xiaoming Zhai – IEEE Transactions on Learning Technologies, 2024
While ongoing efforts have continuously emphasized the integration of ChatGPT with science teaching and learning, there are limited empirical studies exploring its actual utility in the classroom. This study aims to fill this gap by analyzing the lesson plans developed by 29 pre-service elementary teachers and assessing how they integrated ChatGPT…
Descriptors: Artificial Intelligence, Natural Language Processing, Science Education, Preservice Teachers
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Safaa M. Abdelhalim – Journal of Computer Assisted Learning, 2024
Background: Introducing new technologies in education sparks debates, disrupting traditional practices, and requiring teacher adaptation. ChatGPT is an example. Research explores its benefits and concerns in education, with recommendations for classroom use. Nevertheless, limited evidence supports ChatGPT as a tool for supporting English as a…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Second Language Learning
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Seyedahmad Rahimi; Justice T. Walker; Lin Lin-Lipsmeyer; Jinnie Shin – Creativity Research Journal, 2024
Digital sandbox games such as "Minecraft" can be used to assess and support creativity. Doing so, however, requires an understanding of what is deemed creative in this game context. One approach is to understand how Minecrafters describe creativity in their communities, and how much those descriptions overlap with the established…
Descriptors: Creativity, Video Games, Computer Games, Evaluation Methods
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