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arXiv 2407.09712physics.ed-ph
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本科物理实验课程全球图景的构建

Development of a global landscape of undergraduate physics laboratory courses

Gayle Geschwind, Micol Alemani, Michael F. J. Fox, P. S. W. M. Logman, Eugenio Tufino, H. J. Lewandowski

AI总结:

为解决全球本科物理实验课程差异大、PER研究结果难比较的问题,研究者设计了覆盖41国的课程调查,采用定量定性结合的方法分析课程异同,为PER研究对比和教师课程改进提供支持。

摘要:

物理教育研究(Physics Education Research, PER)是一项全球性事业,全球各类机构都开展了大量相关工作。然而,由于本科物理实验课程存在广泛差异,相关研究结果往往难以进行比较。我们设计了一项调查来对这些课程进行分类,以便对其展开比较与对照,这将在两大关键工作中发挥作用:一是PER研究之间的横向比较,二是为希望改进课程的一线教师提供实用数据,从而为研究者和教师都提供相关信息。尽管我们仍在收集足够数据以构建完整的实验课程分类体系,但本文在此呈现调查设计本身的细节,以及对已收集数据的初步分析——这些数据覆盖了41个国家的实验课程,勾勒出了广阔的全球图景。我们采用定量与定性相结合的方法分析收集到的数据。部分研究结果显示了课程之间的共性,比如学生通常使用预先搭建好的实验装置,且教师都希望学生掌握实验技术技能;同时我们也发现了课程间的差异,比如课程目标的数量与类型不同,学生参与的实验活动也存在差异。

英文摘要:

Physics Education Research (PER) is a global endeavour, with a wealth of work performed at a variety of institutions worldwide. However, results from research into undergraduate physics laboratory courses is often difficult to compare due to the broad variations in courses. We have created a survey to help classify these courses to compare and contrast them, which will be useful in two key endeavours: comparisons between PER studies and providing useful data for individual instructors hoping to improve their courses, thus providing information relevant to both researchers and instructors. While we are still in the process of collecting sufficient data to create a full taxonomy of laboratory courses, we present here details of the survey creation itself, as well as a first look at the data collected, which includes a broad landscape of lab courses in 41 countries. We used both quantitative and qualitative methods in analyzing the data collected. Some of these results include similarities between courses, such as students often using pre-constructed apparatuses and that instructors hope for students to learn technical skills. We also find differences in courses, such as in the number and types of goals of the course, as well as the activities students participate in.

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。

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