An Instrument Assembly and Data Science Lab for Early Undergraduate Education
An Instrument Assembly and Data Science Lab for Early Undergraduate Education
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用于早期本科教育的仪器组装和数据科学实验室
DOI：
10.1021/acs.jchemed.2c01072
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发表时间：
2023
影响因子：
3
通讯作者：
Gruebele, Martin
中科院分区：
文献类型：
--
作者：
Wallum, Alison;Liu, Zetai;Lee, Joy;Chatterjee, Subhojyoti;Tauzin, Lawrence;Barr, Christopher D.;Browne, Amberle;Landes, Christy F.;Nicely, Amy L.;Gruebele, Martin
随着数据科学和仪器仪表成为从医学到农业科学等常见职业中的关键实践，化学作为一门核心入门课程，必须尽早向学生介绍这些主题，并使其达到可理解的水平。先进的数据采集和数据科学通常需要昂贵的精密仪器和大量的计算，即使是高水平的本科实验室课程，也往往达不到。与此同时，新一代负担得起的DIY仪器为将侧重于仪器设计和计算的课程纳入新生课程提供了机会。我们提出了一个新的实验室，用于集成到现有课程中，从动手构建光谱仪开始，转移到数据收集，最后介绍一种先进的数据科学技术-奇异值分解，在适当的水平上以最低的计算要求。所使用的硬件和软件都是模块化的，而且价格低廉。该实验室在两个学期的时间里在三个社区大学的普通化学部分进行了测试。以前，学习这些课程的学生在决定是否攻读学士学位之前，通常不会看到高级量化化学课程。本实验允许学生练习数据收集和组织技能，使用预先编写的执行高级数据分析的Jupyter笔记本，并获得演示技能。学生完成的多波评估强调了在单个实验室中整合多个高级主题(涉及仪器设计、数据收集和分析技术)的成功和困难。
As data science and instrumentation become key practices in common careers ranging from medicine to agriscience, chemistry as a core introductory course must introduce such topics to students early and at an accessible level. Advanced data acquisition and data science generally require expensive precision instrumentation and massive computation, often out-of-reach even for upper-level undergraduate laboratory courses. At the same time, a new generation of affordable do-it-yourself instruments presents an opportunity for incorporation of curricula focused on instrument design and computation into freshman-level courses. We present a new lab for integration into existing courses that starts with hands-on spectrometer building, moves to data collection, and finally introduces an advanced data science technique, singular value decomposition, at an appropriate level with minimal computing requirements. The hardware and software used are modular and inexpensive. The lab was tested in three community college general chemistry sections over two semesters. Previously, students taking these courses did not typically see advanced quantitative chemistry curricula before deciding whether to pursue a bachelor’s degree. This lab allowed students to practice data collection and organization skills, use prewritten Jupyter notebooks that perform advanced data analysis, and gain presentation skills. A multiwave assessment completed by students highlights both successes and difficulties associated with incorporating multiple advanced topics involving instrument design, data collection, and analysis techniques in a single lab.
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