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Direct linkWei Li; Jia-Wei Ji; Judy C. R. Tseng; Cheng-Ye Liu; Ji-Yi Huang; Hai-Ying Liu; Mo Zhou – Educational Technology & Society, 2025
Education is an important way to achieve global Sustainable Development Goals (SDGs), while classroom engagement and collective efficacy are key factors that influence SDG learning outcomes. However, students' in-depth thinking could be limited when they apply to search engines such as Google to support their learning of SDG-related topics. Large…
Descriptors: Learner Engagement, Self Efficacy, Critical Thinking, Artificial Intelligence
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
Download full textAlbacete, Patricia; Jordan, Pamela; Katz, Sandra; Chounta, Irene-Angelica; McLaren, Bruce M. – Grantee Submission, 2019
This paper describes an initial pilot study of Rimac, a natural-language tutoring system for physics. Rimac uses a student model to guide decisions about "what content to discuss next" during reflective dialogues that are initiated after students solve quantitative physics problems, and "how much support to provide" during…
Descriptors: Natural Language Processing, Teaching Methods, Educational Technology, Technology Uses in Education
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)
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
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
