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

IF 5.8 2区 物理与天体物理 Q1 OPTICS
Atakan Coban, David Dzsotjan, Stefan Küchemann, Jürgen Durst, Jochen Kuhn, Christoph Hoyer
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Abstract

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 necessary for continuous development. However, the abstract and complex nature of quantum physics makes the topic difficult to understand. Augmented reality (AR) allows otherwise invisible abstract concepts to be visualized and enables interactive learning, offering significant potential for improving quantum physics education in university lab courses. In addition, personalized feedback on challenging concepts can facilitate learning, and large language models (LLMs) like ChatGPT can effectively deliver such feedback. This study combines these two aspects and explores the impact of an AR-based quantum cryptography experiment with integrated ChatGPT-based feedback on university students’ learning outcomes and cognitive processes. The study involved 21 groups (11 Group A; 10 Group B) of students in a physics laboratory course at a German university and used four open-ended questions to measure learning outcomes and gaze data as a learning process assessment. Statistical analysis was used to compare scores between feedback and non-feedback questions, and the effect of ChatGPT feedback on eye-tracking data was examined. The results show that ChatGPT feedback significantly improved learning outcomes and affected gaze data. While the feedback on conceptual questions tended to direct attention to the visualizations of the underlying model, the feedback on questions about experimental procedures increased visual attention to the real experimental materials. Overall, the results show that AI-based feedback draws visual attention towards task-relevant factors and increases learning performance in general.

AI支持满足Alice和Bob的AR可视化:在物理实验室课程的AR量子密码实验中基于个人ChatGPT反馈的个性化学习
量子密码学是量子技术领域的核心课题,对安全通信尤为重要。培养这一领域的合格专家是持续发展的必要条件。然而,量子物理的抽象性和复杂性使得这个话题很难理解。增强现实(AR)可以将原本看不见的抽象概念可视化,并实现交互式学习,为改善大学实验课程中的量子物理教育提供了巨大的潜力。此外,针对具有挑战性的概念的个性化反馈可以促进学习,像ChatGPT这样的大型语言模型(llm)可以有效地提供这种反馈。本研究将这两个方面结合起来,探讨基于ar的量子密码学实验与基于chatgpt的集成反馈对大学生学习成果和认知过程的影响。研究共纳入21组(A组11组;对德国一所大学物理实验课程的学生进行了研究,并使用四个开放式问题来衡量学习成果,并将注视数据作为学习过程的评估。采用统计分析比较反馈和非反馈问题的得分,并检验ChatGPT反馈对眼动追踪数据的影响。结果表明,ChatGPT反馈显著改善了学习结果并影响了注视数据。概念性问题的反馈倾向于将注意力引向基础模型的可视化,而关于实验过程的问题的反馈则增加了对真实实验材料的视觉关注。总体而言,研究结果表明,基于人工智能的反馈将视觉注意力吸引到任务相关因素上,总体上提高了学习成绩。
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来源期刊
EPJ Quantum Technology
EPJ Quantum Technology Physics and Astronomy-Atomic and Molecular Physics, and Optics
CiteScore
7.70
自引率
7.50%
发文量
28
审稿时长
71 days
期刊介绍: Driven by advances in technology and experimental capability, the last decade has seen the emergence of quantum technology: a new praxis for controlling the quantum world. It is now possible to engineer complex, multi-component systems that merge the once distinct fields of quantum optics and condensed matter physics. EPJ Quantum Technology covers theoretical and experimental advances in subjects including but not limited to the following: Quantum measurement, metrology and lithography Quantum complex systems, networks and cellular automata Quantum electromechanical systems Quantum optomechanical systems Quantum machines, engineering and nanorobotics Quantum control theory Quantum information, communication and computation Quantum thermodynamics Quantum metamaterials The effect of Casimir forces on micro- and nano-electromechanical systems Quantum biology Quantum sensing Hybrid quantum systems Quantum simulations.
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