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20232026
most citedPhysics task development of prospective physics teachers using ChatGPT

117 citations · 274 across the 18 of their papers we have counts for

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15 papers · 1 filter

physics.ed-ph2026

AI-Augmented Inquiry and Regulation in Hybrid Systems: A Control Allocation Architecture for Preserving Epistemic Agency in Hybrid Human-AI Cognition

Jochen Kuhn, Peter Gerjets, Ulrich Trautwein +4

Generative artificial intelligence (genAI) systems are increasingly integral to epistemic processes such as hypothesis generation, explanation construction, and decision-making. Al…

physics.ed-ph2026★ 1 cited

AI-based Verbal and Visual Scaffolding in a Serious Game: Effects on Learning and Cognitive Load

Caroline Wermann, Karina E. Avila, Sebastian André +8

Due to their interactive nature, serious games offer valuable opportunities for supporting learning in educational contexts. Recent advances in large language models (LLMs) have fu…

physics.ed-ph2026

Personalized Multimodal Feedback Using Multiple External Representations: Strategy Profiles and Learning in High School Physics

Natalia Revenga-Lozano, Karina E. Avila, Steffen Steinert +4

Multiple external representations (MERs) and personalized feedback support physics learning, yet evidence on how personalized feedback can effectively integrate MERs remains limite…

physics.ed-ph2026

It's Not the Tool, It's the Task: A Framework for Cognitively Activated AI Augmentation in Physics Instruction

Jochen Kuhn, Stefan Küchemann, Dave Rakestraw +1

Generative artificial intelligence (AI) systems can now reliably solve many standard tasks used in introductory physics courses, producing correct equations, graphs, and explanatio…

physics.ed-ph2025

AI-Supported Mini-Labs: Combining Smartphone-Based Experiments and Multimodal AI

Jochen Kuhn, David J. Rakestraw, Stefan Küchemann +1

This paper presents the concept of AI-supported Mini-Labs, combining smartphone-based experiments with multimodal large language models (MLLMs). Smartphones, with their integrated…

physics.ed-ph2025

Comparing Visual Qubit Representations in Quantum Education: The Bloch sphere Enhances Task Efficiency

Linda Qerimi, Sarah Malone, Eva Rexigel +2

Visual-graphical qubit representations offer a means to introduce abstract quantum concepts - such as quantum state, superposition, or measurement - in an accessible manner, partic…

physics.ed-ph2025

Visualization enhances Problem Solving in multi-Qubit Systems

Jonas Bley, Eva Rexigel, Alda Arias +7

Quantum Information Science (QIS) is a vast, diverse, and abstract field. In consequence, learners face many challenges. Science, Technology, Engineering, and Mathematics (STEM) ed…

physics.ed-ph2025

Hands-on Experiment Supported by Augmented Reality Smartglasses for Learning the Lorentz Force

Max Warkentin, Kristin Altmeyer, Yajie Liang +6

Previous research has shown that inquiry-based learning through hands-on experiments, as well as learning with multiple, external representations (MERs) can promote the understandi…

physics.ed-ph2024

AI Support Meets AR Visualization for Alice and Bob: Personalized Learning Based on Individual ChatGPT Feedback in an AR Quantum Cryptography Experiment for Physics Lab Courses

Atakan Coban, David Dzsotjan, Stefan Küchemann +3

Quantum cryptography is a central topic in the quantum technology field that is particularly important for secure communication. The training of qualified experts in this field is…

physics.ed-ph2024★ 1 cited

Quantum cryptography visualized: assessing visual attention on multiple representations with eye tracking in an AR-enhanced quantum cryptography student experiment

David Dzsotjan, Atakan Coban, Christoph Hoyer +4

With the advent and development of real-world quantum technology applications, a practically-focused quantum education including student quantum experiments are gaining increasing…

physics.ed-ph2023★ 55 cited

Harnessing Large Language Models to Enhance Self-Regulated Learning via Formative Feedback

Steffen Steinert, Karina E. Avila, Stefan Ruzika +2

Effectively supporting students in mastering all facets of self-regulated learning is a central aim of teachers and educational researchers. Prior research could demonstrate that f…

physics.ed-ph2023★ 57 cited

Unreflected Acceptance -- Investigating the Negative Consequences of ChatGPT-Assisted Problem Solving in Physics Education

Lars Krupp, Steffen Steinert, Maximilian Kiefer-Emmanouilidis +5

Large language models (LLMs) have recently gained popularity. However, the impact of their general availability through ChatGPT on sensitive areas of everyday life, such as educati…

physics.ed-ph2023★ 2 cited

Educational data augmentation in physics education research using ChatGPT

Fabian Kieser, Peter Wulff, Jochen Kuhn +1

Generative AI technologies such as large language models show novel potentials to enhance educational research. For example, generative large language models were shown to be capab…

physics.ed-ph2023

Newspaper Story Problems and Other Tasks for Context Based Physics Education: A Research Based report on classroom practice

Jochen Kuhn, Andreas Müller, Patrik Vogt

Background: Context Based Science Education (CBSE) has a long-standing tradition and is discussed as a highly promising approach in science education. It is supposed that CBSE can…

physics.ed-ph2023★ 117 cited

Physics task development of prospective physics teachers using ChatGPT

Stefan Küchemann, Steffen Steinert, Natalia Revenga +4

The recent advancement of large language models presents numerous opportunities for teaching and learning. Despite widespread public debate regarding the use of large language mode…