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Jiaqi Yin; Tiong-Thye Goh; Yi Hu – International Journal of Educational Technology in Higher Education, 2024
Educational chatbots (EC) have shown their promise in providing instructional support. However, limited studies directly explored the impact of EC on learners' emotional responses. This study investigated the induced emotions from interacting with micro-learning EC and how they impact learning motivation. In this context, the EC interactions…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Psychological Patterns
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Jessica D. Young; Lisa Dawood; Scott E. Lewis – Journal of Chemical Education, 2024
Instructors use of Artificial Intelligence (AI) language models (i.e., chatbots) as an educational resource will require an understanding of students' AI literacy, namely their ability to critically reflect on the relevance, trustworthiness, and quality of these tools in the context of chemistry. This study sought to describe students' AI literacy…
Descriptors: Chemistry, Science Instruction, Artificial Intelligence, Multiple Literacies
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Julia Lademann; Jannik Henze; Sebastian Becker-Genschow – Physical Review Physics Education Research, 2025
This work explores the integration of artificial intelligence (AI) custom chatbots in educational settings, with a particular focus on their applicability in the context of mathematics and physics. In view of the increasing deployment of AI tools such as ChatGPT in educational contexts, the present study explores their potential in generating…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Morgan J. Clark; Micke Reynders; Thomas A. Holme – Journal of Chemical Education, 2024
In the field of education, ChatGPT has become a topic of debate for its usefulness as a learning tool. This article focuses on non-science majors' (n = 29) perceptions of a ChatGPT enabled final exam, where, prior to the exam, students wrote papers on science and sustainability and, during the final exam, students were asked to compare their paper…
Descriptors: Student Experience, Artificial Intelligence, Natural Language Processing, Tests
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Manik R. Reddy; Nils G. Walter; Yulia V. Sevryugina – Journal of Chemical Education, 2024
The effective and responsible educational application of ChatGPT and other generative artificial intelligence (GenAI) tools constitutes an active area of exploration. This study describes and assesses the implementation of a structured, GenAI-assisted scientific essay writing assignment in nucleic acid biochemistry. Briefly, students created,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Writing Assignments, Biochemistry
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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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Michalenko, Joshua J.; Lan, Andrew S.; Waters, Andrew E.; Grimaldi, Philip J.; Baraniuk, Richard G. – International Educational Data Mining Society, 2017
An important, yet largely unstudied problem in student data analysis is to detect "misconceptions" from students' responses to "open-response" questions. Misconception detection enables instructors to deliver more targeted feedback on the misconceptions exhibited by many students in their class, thus improving the quality of…
Descriptors: Data Analysis, Misconceptions, Student Attitudes, Feedback (Response)
Tansomboon, Charissa – ProQuest LLC, 2017
Students studying complex science topics can benefit from receiving immediate, personalized guidance. Supporting students to revise their written explanations in science can help students to integrate disparate ideas and develop a coherent, generative account of complex scientific topics. Using natural language processing to analyze student…
Descriptors: Middle School Students, Secondary School Science, Science Education, Science Instruction
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Forbes-Riley, Kate; Litman, Diane – International Journal of Artificial Intelligence in Education, 2013
In this paper we investigate how student disengagement relates to two performance metrics in a spoken dialog computer tutoring corpus, both when disengagement is measured through manual annotation by a trained human judge, and also when disengagement is measured through automatic annotation by the system based on a machine learning model. First,…
Descriptors: Correlation, Learner Engagement, Oral Language, Computer Assisted Instruction
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis