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Linh Huynh; Danielle S. McNamara – Grantee Submission, 2025
We conducted two experiments to assess the alignment between Generative AI (GenAI) text personalization and hypothetical readers' profiles. In Experiment 1, four LLMs (i.e., Claude 3.5 Sonnet; Llama; Gemini Pro 1.5; ChatGPT 4) were prompted to tailor 10 science texts (i.e., biology, chemistry, physics) to accommodate four different profiles…
Descriptors: Natural Language Processing, Profiles, Individual Differences, Semantics
Ursula Holzmann; Sulekha Anand; Alexander Y. Payumo – Advances in Physiology Education, 2025
Generative large language models (LLMs) like ChatGPT can quickly produce informative essays on various topics. However, the information generated cannot be fully trusted, as artificial intelligence (AI) can make factual mistakes. This poses challenges for using such tools in college classrooms. To address this, an adaptable assignment called the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Thinking Skills
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
Alexis Buzzell; Timothy J. Atherton; Ramón Barthelemy – Physical Review Physics Education Research, 2025
[This paper is part of the Focused Collection in Investigating and Improving Quantum Education through Research.] The modern physics course is a crucial gateway for physics majors as it provides an introduction to concepts beyond the scope of the K-12 education. This study collected 167 modern physics syllabi from 127 U.S. research-intensive…
Descriptors: Physics, Course Content, Science Instruction, Required Courses
Xiaoming Zhai, Editor; Joseph Krajcik, Editor – Oxford University Press, 2025
In the age of rapid technological advancements, the integration of Artificial Intelligence (AI), machine learning (ML), and large language models (LLMs) in Science, Technology, Engineering, and Mathematics (STEM) education has emerged as a transformative force, reshaping pedagogical approaches and assessment methodologies. "Uses of AI in STEM…
Descriptors: Artificial Intelligence, STEM Education, Technology Uses in Education, Educational Technology