Exploring Data and Models

Concepts on this page were derived from participant presentations, discussions, and breakout groups at the 2015 Teaching Geoscience with MATLAB workshop and benefitted from the editing of Andrew Fischer, University of Tasmania

Working with real-world data has always been an important part of learning in Geoscience. Increasingly, being able to find and import and make sense of data of varying types from a broad range of sources are skills employers are seeking. Students also need to be able to visualize data, perform statistical analyses, and understand how their data manipulations change interpretations and results. Pedagogical techniques such as using contextualized examples, working with authentic data and providing hands-on experience can increase student engagement. Faculty are aided by technical and pedagogical support in teaching these skills.

Potential data and modeling goals include:
  • Making sense of data (e.g. summarizing, visualizing, and synthesizing)
  • Relating separate types of data/integrating data of varying data types through advanced statistical techniques (e.g.multivariate analysis)
  • Developing interfaces using real world data from scientific repositories
  • Basic graph interpretation skills (MATLAB helps plot functions and see how they change)
  • Contextualized examples to increase engagement
  • Comparing output of different numerical/analytical approaches
  • Examining simple cause and effect relationships in Geoscience datasets to help motivate student learning
  • Using "big data"- Geological data incorporates all types of data across temporal and spatial scales, as well as physical and numerical models. MATLAB provides a platform aggregate, analyze and visualize disparate datasets
« Back to Teaching with MATLAB® page

Why use MATLAB?

In addition to the overarching benefits of MATLAB, there are specific benefits of exploring data and models using MATLAB, including:

  • Data manipulation with minimal coding skills
  • An interface that allows for comparison of the data to the visual
  • Simultaneously processing and displaying many types of data
  • Large online technical and scientific support community

Approaches to Getting Students Started

Many students have previous programming experience using other software, such as Microsoft Excel, or from other contexts, such as a computer science course. This background can be built on, transitioning students to the more complex quantitative analyses using MATLAB. Class instruction may include structured activities such as modeling fundamental Earth Science formulas such as heat flow through oceanic lithosphere, or collecting data in lab and using MATLAB to load, plot, and analyze their data. Using MATLAB's advanced and "easy-to-learn/use" analytical and visualization functions and toolboxes, provides students with a more comprehensive and holistic learning experience. Students benefit from having independent access to MATLAB on their own computers, allowing them to gain familiarity through regular practice and working on their own outside of class.

More on teaching data analysis with MATLAB » More on teaching modeling with MATLAB »

Resources

Activities

Courses

  • Course: Quantitative Data Analysis, Scott Marshall. The main goal of this course is to provide a computational and quantitative skill set relevant for processing, filtering, analyzing, and visualizing quantitative Earth science data efficiently and accurately.
  • Course: Data Analysis, David Heslop. The aim of this course is to provide an introduction to statistical and numerical techniques that are useful in the analysis and characterization of geological data.

Other

Advertisement