Why Teach Computation?

Content on this page is derived from participant presentations, discussions, and breakout groups at the 2015,2016, and2017Teaching Computation in the Sciences workshops.

Computation and modeling are pillars of many STEM fields. As such, successful STEM curricula must provide students with the skills and tools to use computation and modeling. In addition, the growing importance of parallel/high-performance computing and Big Data in STEM makes imparting these skills all the more important. Participants of the 2015, 2016, and 2017 workshops echoed this idea that undergraduate STEM curricula must incorporate computational thinking in order to adequately prepare students for their careers. These computational skills can help students reinforce and improve their math skills and gain a deeper understanding of foundational scientific principles.

Building computational skills can help students develop:

  • Computational confidence and self-efficacy
  • Problem solving skills
  • Logic and reasoning when dealing with big data and models
  • Dirt (data collection) to desktop - transform raw collected data to the program so it can be read
  • Data control - the opposite of a black box
  • Science communication
  • Reproducible research practices

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Computation and Modeling in STEM

At the 2017 Teaching Computation in the Sciences workshop, participants representing a variety of STEM disciplines discussed how computation and modeling are used in their fields and key concepts that can be explored using MATLAB in courses.

In Geoscience

  • Computation is used demonstrate the importance of quantitative data and calculations in understanding Earth processes and evolution

Key concepts that can be explored:

  • Understanding the Earth and how it works quantitatively
  • Linking time and space with geological evolution
  • Modeling and imaging sub-surface processes
  • Understanding processes on other planets

In Engineering

  • Computation is used to model, design, and analyze physical systems

Key concepts that can be explored:

  • Modeling of dynamic, thermodynamic, heat transfer, chemical, and structural systems
  • Literature and data mining
  • Data analysis, statistics
  • Matrix algebra, calculus

In Mathematics

  • Computation forms the core of the discipline, while modeling makes conceptual mathematics less abstract

Key concepts that can be explored:

  • Linear algebra, differential equations
  • Problem-solving (e.g. predator-prey, economics)
  • Computing and programming skills and language

In Physics

Key concepts that can be explored:

  • Predicting behavior and exploring behavioral space
  • Linearizing and extracting information
  • Demystifying equations by thinking through proofs and mechanisms

Why MATLAB for Teaching Computation?

Workshop participants discussed the importance of teaching computation and highlighted why MATLAB is a uniquely useful tool for achieving computational learning goals and preparing students:

  • MATLAB (compared to similar software and programming languages) is user friendly and has a relatively low "activation energy" to begin using.
  • Users can interact with MATLAB via multiple platforms (computers, smartphones, and online).
  • The diverse functionality of MATLAB (beyond basic programming) makes it a powerful tool for research and discovery.
  • The visualization, analysis, programming, and project management capabilities of MATLAB make it possible to combine and analyze disparate data formats.
  • MATLAB is used in a wide variety of fields and licenses are available at many institutions.
  • There is an active community of MATLAB users who make their insights and tools available to others.


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