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GeoCode - Visualizing Geohazards and Risk with Code banner

Visualizing Geohazards and Risk with Code (GeoCode) integrates science practices and computational thinking practices in the study of geohazards for secondary students


With the advance in technologies embedded in satellites and science observatories, lots of high-quality data are continuously collected and are available to scientists who study geohazards, such as earthquakes, volcanoes, and tsunamis. How do scientists explore how hazards form? How do they think about impacts associated with the hazards? How do they determine the risks associated with the hazards?

Geohazards are not only scientifically important, they are also captivating to students. Recent images of lava flowing out of the Kilauea volcano in Hawaii are nothing short of remarkable. Geoscientists investigate the mechanisms that cause geohazards and the impacts associated with those hazards. Their work helps citizens make informed decisions and take appropriate actions by considering their local community’s vulnerability and exposure to the impending risk.

Much of geohazard research involves computational analyses and visualizations of large data sets. We make discoveries by finding meaningful patterns in data. Scientists frequently write programs to filter, sort, translate, and display data in novel ways that give rise to new theories and insights about what the data signifies. Arguably the field of geohazard science is rapidly changing to a point where discoveries and innovations are coming from practitioners who can write code that processes and displays data in insightful ways, and who can encode their hypotheses into algorithms.

Learning about hazards, therefore, offers an ideal context for students to experience integrated practices between science and computational thinking. The Next Generation Science Standards (NGSS) advocates for the inclusion of natural hazards content in Earth science classes in both middle school and high school. Specifically, NGSS suggests that students should analyze and interpret data on natural hazards, consider technologies to mitigate their effects, and use evidence to build student understanding.

GeoCode will engage students in problem-solving similar to practices of scientists who study real-world volcanic and seismic geohazards. Students will transform high-precision, scientific-grade, real-world GPS data into interpretable visualizations and use them as evidence to formulate scientific arguments about predicting the impact of geohazards. The project will develop a Scaffolded Visualization Programming (SVP) tool that will allow students to program spatially and temporally distributed visualizations. The project will also develop two curriculum modules that feature the SVP tool and computationally integrated inquiry-based activities in which students explore specific hazards and potential impacts of the hazards.

Goals & Objectives

Our goal is to develop a pedagogical model for integrating science practices with computational thinking (CT) germane to geoscientists’ inquiry into geohazards.

Core computational practices (CP) will occur in the construction, interpretation, and revision of computational visualizations forstudents to explain scientific phenomena, make predictions, and assess risks and potential impacts. Students engage in scientific argumentation by making claims about risks based on the computational visualizations as evidence then communicate them to the affected region.


Research on student learning is guided by the following questions:

  • How do students translate their understanding of a geohazard into an algorithmic model to create visualizations? How do students interpret data represented in visualizations to improve their understanding?
  • How do students use visualizations they create in formulating scientific arguments to assess risks related to a geohazard?
  • Does GeoCode’s curricular approach improve students’ understanding of geohazards and data-based scientific argumentation associated with risk assessment?

Project Funder: This material is based upon work supported by the National Science Foundation under Grant No. DRL-1841928. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Principal Investigators: Donna Chalevoix, Amy Pallant, Hee-Sun Lee, Noah Paessel, Jie Chao, Charles Conner

Project Partners: Concord Consortium; University of South Florida

Years Active: 2018-2021

Please visit the GeoCode homepage at Concord Consortium for more information.


Last modified: 2019-12-24  02:12:59  America/Denver