Implementation of a Python Program to Simulate Sampling

Dickson‐Karn, Nicole M.; Orosz, Steven

doi:10.1021/acs.jchemed.1c00597

Cited by 9 publications

(7 citation statements)

References 36 publications

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“…The game generation code was developed in R , as the main code writer had most experience in this language. R has been used by others successfully for chemical education applications, but other languages such as Python could also be used. , Our annotated R scripts (Supporting Information) provide an explanation of each step. These can be used to replicate the session or adapt it for other experiments.…”

Section: Discussionmentioning

confidence: 99%

A Murder Mystery Gamification Session to Consolidate Analytical Biochemical Techniques Learning

Hill,

Harmer

2023

J. Chem. Educ.

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Gamification has a strong track record of improving student engagement and learning in the chemical sciences. Metaanalyses of different approaches to gamification have highlighted that providing a game fiction, encouraging students to work in teams, and breaking games into smaller "quests" are particularly effective. Here, we aimed to increase students' engagement and learning with four analytical biochemistry techniques (high-performance liquid chromatography, sodium dodecyl sulfate polyacrylamide gel electrophoresis, Western blot, and mass spectrometry) by creating a game that required them to use every method to solve a "murder mystery". Our game was based on the popular games "Mafia" and "Among Us" and introduced an original game fiction relevant to our setting. Students attending the formative gamified session gave highly positive feedback. They indicated that they enjoyed the session and increased confidence in the methods involved. Free text comments praised many of the elements deliberately introduced into the game. To our surprise, the main criticism was that the session was not challenging enough. We developed a revised session that required students to undertake more detailed data interpretation, which students reported gave the expected increase in difficulty. All materials and code for running our session and generating new mysteries with original data are available online.

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Section: Discussionmentioning

confidence: 99%

A Murder Mystery Gamification Session to Consolidate Analytical Biochemical Techniques Learning

Hill,

Harmer

2023

J. Chem. Educ.

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“…Nowadays, programming software such as MATLAB, Phyton, Octave, and R project have been used for intricate statistical calculations. − These programs do not offer a “pretty face”, and students must type a series of command lines to run statistical tests …”

Section: Experimental Overviewmentioning

confidence: 99%

Iron Quantification in Dietary Supplements using Four Colorimetric Assays

Filgueiras

Borges

2022

J. Chem. Educ.

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Students determine the iron mass in dietary supplements using four colorimetric assays. These colorimetric assays were selective for Fe3+. It was complexed by thiocyanide, salicylate, gallic acid, and Fe(CN)6 4–, forming blood-red, red, violet, and blue complexes, respectively. The λmax of these complexes were 447, 480, 570, and 700 nm, respectively. These assays were scaled-down, where 1 mL of chromogenic reagent was mixed with 0.1 mL of sample. Salicylic acid, gallic acid, and K4[Fe(CN)6] were harmless and cheap chromogenic reagents that could be used instead of traditional chromogenic reagents such as KSCN and phenanthroline. Quantitative analysis was carried out using absorbance measured at λmax of each assay (standard method) and 96-well-plate digital images obtained with a desktop scanner (proposed method). The matrix effect was investigated by comparing the standard addition curves with the external calibration curves, where no matrix effect was found. Results obtained using the four assays were compared using hypothesis tests such as one-way ANOVA, post-hoc tests, and plots. Investigation of interactions between samples and assays was carried out using two-way ANOVA. Statistical tests were carried out using open-source and graphical user interface programs (JASP and R Commander). The student learning goals of this experiment include comparing multiple assays using hypothesis tests. Learn about the principles of green chemistry, method scale-down, and matrix effect.

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“…The modern workforce and academic research have become more intensively data-science-driven, requiring skills ranging from fluency in spreadsheets at the most basic level to Python programming or high-throughput data science tools. , Upper division chemistry curricula have responded with coursework in instrumentation and advanced data analysis, , often associated with an analytical, physical, or biochemistry lab . With advanced analysis and computational skills now critical in a variety of fields, there is a growing need to find affordable ways to introduce these skills earlier than the junior and senior years in college. , …”

Section: Introductionmentioning

confidence: 99%

An Instrument Assembly and Data Science Lab for Early Undergraduate Education

et al. 2023

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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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Implementation of a Python Program to Simulate Sampling

Cited by 9 publications

References 36 publications

A Murder Mystery Gamification Session to Consolidate Analytical Biochemical Techniques Learning

A Murder Mystery Gamification Session to Consolidate Analytical Biochemical Techniques Learning

Iron Quantification in Dietary Supplements using Four Colorimetric Assays

An Instrument Assembly and Data Science Lab for Early Undergraduate Education

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