A Primer in Monte Carlo Integration Using Mathcad

Hoyer, Chad E.; Kegerreis, Jeb S.

doi:10.1021/ed400013d

Cited by 3 publications

(4 citation statements)

References 15 publications

(18 reference statements)

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“…Mathcad uses the built in random number generator (rnd) to produce random numbers. 32 If the ratio is higher than the random value, the number of molecules of a given substance is decreased in one unity. Otherwise, the number of molecules of such a substance remains the same.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

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Using Stochastic Approaches for Teaching Mass Transfer Unit Operations: The Monte Carlo Method

2020

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Mass transfer separations are of extreme importance to professionals working in the chemical industry. For this reason, chemical engineering and industrial chemistry students are both taught these unit operations at the final years of their study programs. The traditional way of carrying out their design is based on the use of deterministic models, most often involving ordinary differential equations. However, the macroscopic result of many existing chemical processes is due to the effect of statistical molecular motion. Hence, the use of stochastic or random approaches enables the issue to be addressed with just basic probability concepts aided by computer software. Based on these ideas, this article explores the implementation of Monte Carlo simulations for addressing two case studies related to mass transfer processes (batch distillation and gas membrane separation) and presents a comparative evaluation with respect to traditional deterministic methods. The easiness and accuracy of the method allow the conclusion that Monte Carlo simulations may facilitate understanding and add another dimension to students’ computational skills without detriment to the result’s quality. The case studies presented may also enrich the instructors’ educational competence, providing them with an alternative view of the matter.

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Section: ■ Results and Discussionmentioning

confidence: 99%

“…Such ratios are then compared with random numbers between 0 and 1. Mathcad uses the built in random number generator (rnd) to produce random numbers . If the ratio is higher than the random value, the number of molecules of a given substance is decreased in one unity.…”

Section: Results and Discussionmentioning

confidence: 99%

Using Stochastic Approaches for Teaching Mass Transfer Unit Operations: The Monte Carlo Method

2020

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“…We can leverage our existing communication pathways to move beyond knowledge dissemination toward knowledge mobilization. ,− The Journal of Chemical Education (JCE) publishes reviews and meta-analyses, which can be directed at educators − or curriculum developers but are most often directed at researchers. − JCE regularly publishes primers to facilitate chemistry content knowledge development − or improve researchers’ methodological knowledge. − However, primers that support domain-specific pedagogical development, such as the laboratory design primer by Neiles and Arnett (2021), are rare and can be difficult to find. In comparison, CBELife Sciences Education’s Current Insights feature curates and translates cross-disciplinary knowledge about teaching and learning in biology.…”

Section: Potential Avenues For Overcoming These Challengesmentioning

confidence: 99%

Toward Collaborative Dialogue: Unpacking the Researcher–Educator Divide to Advance Chemistry Education

James,

McKenna,

Mishra

2024

J. Chem. Educ.

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Researchers, educators, and students have different roles in the chemistry education community and are subject to distinct evaluation criteria that inform how they approach their work. In this commentary, we leverage our experience as individuals positioned at the researcher−educator−student interface to describe how we consider these evaluation criteria to incentivize different priorities. These priorities often align synergistically but sometimes conflict. We argue that conflicts between priorities can lead to divisions among community members that undermine the achievement of our shared goals. Based on this understanding, we suggest examples of how the community might overcome these challenges by facilitating education research knowledge mobilization, expanding representation of chemistry education at the undergraduate level, and engaging in collaborative dialogue.

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“…14 An activity that teaches students how to use R for data visualization and statistical analysis in analytical chemistry and quantitative analysis has been presented at the ACS National Meeting, 15,16 although the lesson has not yet been reported in a publication (as of June 2022). Activities have been reported regarding teaching students of chemistry to use LabView, 17 Maple, 18 Mathcad, 19 and the Unix terminal 20 for discipline-specific tasks. The COVID-19 pandemic necessitated distance learning and led to the development of innovative remote approaches for teaching coding in Mathematica, 21 Python programming for structural bioinformatics, 22 and the use of spreadsheets and Jupyter notebooks to generate simulated HPLC data, 23 among others.…”

Section: Introduction Background and Problem Identificationmentioning

confidence: 99%

Activity: Teaching Coding in R through Discipline-Focused Problem-Solving in an Analytical Chemistry Course

2022

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Students completing undergraduate majors in chemistry are not typically required to undergo formal training in computer programming or coding. As a result, many chemistry students are graduating without skills in understanding, writing, or manipulating computer code. This skills gap places students at a disadvantage, considering the widespread and ever-increasing use of computers to acquire, analyze, and present data in chemical industry and research. We hypothesized the following: (1) we could introduce coding to the analytical chemistry curriculum in an accessible and discipline-focused manner and (2) tasks based on adapting existing code would be accessible even to novice coders. Presented here is an activity that teaches students to use R, a widely used programming language designed for data analysis and statistics, within the user-friendly RStudio integrated development environment. The activity uses peptide charge as a motivating bioanalytical chemistry topic. The origin and importance of peptide charge are discussed in the four modules that comprise the activity. Applications relevant to chromatography and mass spectrometry are discussed. Students complete tasks of increasing difficulty, with earlier modules supporting later ones. The activity has been taught to advanced undergraduate and first-semester graduate students. In all iterations, anonymous survey data collected using a Likert-scale questionnaire reflected that most students were not familiar with R or coding generally before completing the activity. Students reported finding the activity enjoyable, efficient, effective, and easy to use. The majority reported that they would use R/ RStudio as a scientific tool in both chemistry and nonchemistry projects in the future. The activity is freely available at https:// weaversd.github.io/R_with_peptides_Project/index.html.

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A Primer in Monte Carlo Integration Using Mathcad

Cited by 3 publications

References 15 publications

Using Stochastic Approaches for Teaching Mass Transfer Unit Operations: The Monte Carlo Method

Using Stochastic Approaches for Teaching Mass Transfer Unit Operations: The Monte Carlo Method

Toward Collaborative Dialogue: Unpacking the Researcher–Educator Divide to Advance Chemistry Education

Activity: Teaching Coding in R through Discipline-Focused Problem-Solving in an Analytical Chemistry Course

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