🏷️ physics-education
13 pages tagged with physics-education(11 articles, 2 concepts)
📄 Studying Circular Motion with an AI-Generated Smartphone Physics Lab
> **Synthesis:** Suñer et al. (2026) show that a fully customized, browser-based rotation laboratory can be generated entirely through natural-language prompting of an AI assistant, with no manual cod…
2026-08-13 · mobile-learning, generative-ai, content-generation, stem-education, personalized-learning
📄 Embodied Inquiry with AI as Facilitator: An Exploratory Case Study
> **Synthesis:** Tufino & Damiani (2026) explore where a language-based AI can stand within an inquiry activity without displacing embodied experience, using a Master's-level physics education course …
📄 From Prompt to Embodied Simulation: Using Generative AI to Create AR Physics Learning Tools
> **Synthesis:** Levy et al. (2026) show how a structured natural-language prompt can generate a browser-based, hand-controlled **augmented-reality (AR) physics simulation** — spread your thumb and in…
📄 Students' Epistemological Beliefs and their Chatbot Preferences in AI-mediated Physics Learning
> **Synthesis:** Sirnoorkar & Mamidpalliwar (2026) investigate the association between introductory physics students' preferences for chatbot behavior and their epistemological beliefs, using a custom…
📄 A Bottom-Up Taxonomy of Student Discourse with a Socratic AI Physics Tutor
> **Synthesis:** Large language model (LLM) tutors are being deployed in introductory physics courses at a scale that produces transcript corpora far larger than traditional qualitative coding can abs…
🏷️ Physics Education
> **Physics Education** — the study of how students learn physics and how to teach it more effectively, spanning Socratic AI tutoring, computational thinking assessment, student trust and AI adoption …
🏷️ STEM Education and AI
> **STEM Education** — science, technology, engineering, and mathematics education is the most common domain for AI in education research in the wiki. STEM's structured knowledge, clear right/wrong an…
📄 Pragmatic users and skeptical nonusers: A qualitative typology of ChatGPT adoption in physics education
> **Synthesis:** Becker, Bauer, Schrader, Bitzenbauer & Veith (2026) analyze 1,189 survey responses from physics students using qualitative content analysis and latent class analysis, identifying two …
📄 Trust-utility gap in introductory physics education: Students' adoption, domain-specific skepticism, and preferences for AI integration
> **Synthesis:** Fouad & Bentley (2026) survey 81 introductory physics students and find a striking 50-percentage-point trust-utility gap: 91% use AI for coursework but only 41% trust AI physics expla…
📄 Using LLMs to Detect Growth in Computational Thinking in Introductory Physics
> **Synthesis:** Savage, Shanker, Michlitsch & Rebello (2026) investigate using LLMs to evaluate students' written explanations of computational physics problems at scale. Establishing a human-coded b…
📄 A multi-agent AI classroom based on dual-process reasoning hazards: a pilot with prospective physics teachers
> **Synthesis:** Tufino (2026) pilots a simulated multi-agent AI classroom where five AI students each enact distinct dual-process theory (DPT) reasoning hazards, giving prospective physics teachers r…
📄 AI-based scoring systematically underestimates conceptual understanding of linguistically weak students' explanations in physics
> **Authors:** Markus S. Feser, Paul L. Tschisgale (Leibniz Institute for Science and Mathematics Education, Kiel, Germany)…
📄 Analyzing Undergraduate Problem-Solving in Physics Through Interaction With an AI Chatbot
> **Synthesis:** A custom Socratic AI chatbot deployed in a large-enrollment introductory mechanics course with 150 first-year STEM majors, demonstrating that AI-driven Socratic dialogue can foster ex…