通过 OpenHPI 的 MOOC 向更广泛的受众介绍量子信息和计算

IF 5.8 2区 物理与天体物理 Q1 OPTICS EPJ Quantum Technology Pub Date : 2024-09-13 DOI:10.1140/epjqt/s40507-024-00270-w
Gerhard Hellstern, Jörg Hettel, Bettina Just
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引用次数: 0

摘要

量子计算是一个令人兴奋的领域,具有巨大的颠覆潜力,但却很难进入。因此,全世界正在开发许多量子计算教学方法。这总是会引发关于教学理念、实际教授内容以及如何衡量教学理念成功与否的问题。在2022年和2023年,作者在哈索-普拉特纳研究所的OpenHPI平台上总共讲授了9门为期两周的MOOC(大规模开放在线课程),并提供了不同的学习路径。该平台的目的是向所有人免费提供计算机科学教育。九门量子课程构成了一个独立的课程体系。目前已有约 7400 名自然人参加了 17000 多门课程的学习,这一数字还在不断上升。本文介绍了该课程的概念,并对有关学员背景、在课程中的表现以及学习成功率的匿名数据进行了评估。本文首次分析了如此庞大的基于 MOOC 的量子计算教育数据集。总结的结果是,学员的个人背景各不相同,偏向于 IT 专业人士,大多数人遵循教学建议,而且成功率很高,这与遵循教学建议密切相关。来自如此庞大的量子计算学习者群体的大量数据为量子计算教育领域的进一步研究提供了许多途径。分析表明,MOOC 是进入量子计算领域的低门槛概念。它深受参与者的欢迎。这一概念可以作为量子计算课程设计的切入点和指南。
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Introducing quantum information and computation to a broader audience with MOOCs at OpenHPI

Quantum computing is an exciting field with high disruptive potential, but very difficult to access. For this reason, many approaches to teaching quantum computing are being developed worldwide. This always raises questions about the didactic concept, the content actually taught, and how to measure the success of the teaching concept. In 2022 and 2023, the authors taught a total of nine two-week MOOCs (massive open online courses) with different possible learning paths on the Hasso Plattner Institute’s OpenHPI platform. The purpose of the platform is to make computer science education available to everyone free of charge. The nine quantum courses form a self-contained curriculum. A total of more than 17,000 course attendances have been taken by about 7400 natural persons, and the number is still rising. This paper presents the course concept and evaluates the anonymized data on the background of the participants, their behaviour in the courses, and their learning success. This paper is the first to analyze such a large dataset of MOOC-based quantum computing education. The summarized results are a heterogeneous personal background of the participants biased towards IT professionals, a majority following the didactic recommendations, and a high success rate, which is strongly correlatated with following the didactic recommendations. The amount of data from such a large group of quantum computing learners provides many avenues for further research in the field of quantum computing education. The analyses show that the MOOCs are a low-threshold concept for getting into quantum computing. It was very well received by the participants. The concept can serve as an entry point and guide for the design of quantum computing courses.

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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.
期刊最新文献
Generation of phonon quantum states and quantum correlations among single photon emitters in hexagonal boron nitride Teaching quantum information science to secondary school students with photon polarization and which-path encoding A computational study and analysis of Variational Quantum Eigensolver over multiple parameters for molecules and ions Quantum data encoding: a comparative analysis of classical-to-quantum mapping techniques and their impact on machine learning accuracy A methodology to select and adjust quantum noise models through emulators: benchmarking against real backends
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