使用 Jupyter Notebook 在物理入门实验课程中培养计算技能与专业实践
Using Jupyter Notebooks to foster computational skills and professional practice in an introductory physics lab course
AI总结：
本研究在不改变课程结构的前提下，通过开发配有练习和示例的 Jupyter Notebook，将 Python 数据分析整合进一年级物理实验课，有效培养了学生的计算技能，并评估了其优势与挑战。
摘要：
本文详细介绍了将 Python 数据分析整合到一年级物理实验课程中的过程，这一任务在不显著改变现有课程结构的情况下完成。我们引入了量身定制的实验计算学习目标，并设计了相应的活动来达成这些目标。我们着重强调了 Jupyter Notebook 的开发与应用，这些 Notebook 配有练习和物理应用示例，旨在促进学生在实验环境中掌握数据分析编程技能。这些 Notebook 作为关键工具，引导学生在完成简单实验任务的同时，掌握 Python 中数据处理与分析的核心原理。对此干预措施的评价结果，为早期将计算技能融入实验课程的优势与挑战提供了见解，为物理教育领域的教育工作者提供了宝贵信息。本研究展示了将计算技能嵌入物理课程的一种实用且有效的方式，并为物理教育研究社区的持续努力做出了贡献。
英文摘要：
In this paper, we detail the integration of Python data analysis into a first-year physics laboratory course, a task accomplished without significant alterations to the existing course structure. We introduced tailored laboratory computational learning goals and designed activities to address them. We emphasise the development and application of Jupyter Notebooks, tailored with exercises and physics application examples, to facilitate students' mastery of data analysis programming within the laboratory setting. These Notebooks serve as a crucial tool in guiding students through the core principles of data handling and analysis in Python, while working on simple experimental tasks. The results of the evaluation of this intervention offer insights into the advantages and challenges associated with early integration of computational skills in laboratory courses, providing valuable information for educators in the field of physics education. This study demonstrates a practical and effective way of embedding computational skills into the physics curriculum, and contributes to the ongoing efforts of the physics education research community.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
