Simulated Biology. Real Learning.

While thinking about how to use constraints on questions and simulations in our Cyberlearning project, we realized that some of the same ideas could be useful for developing performance-based assessments. To explore this, we partnered with the Gardner Lab at Purdue University, and other biology education researchers, who maintain a body of work on students' skill with constructing graphs. The resulting GraphSmarts project is now on it’s second NSF grant aiming to build an assessment of graphing competencies that can be used throughout the undergraduate biology curriculum, and based on that data, to build graphing tutorials for biology students.

In the project, we first set out to define a set of practices that when mastered give one a high level of competence in constructing graphs. The set of 17 practices, called the Graph Construction Competency Model, include skills like choosing variables to plot that are appropriate to the question being asked, choosing a type of graph appropriate to the form of the data being plotted, and drawing conclusions that are justified by the data being shown.

GraphSmarts image
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The key technology in this project is GraphSmarts, a graphing tool purpose-built to determine student competence with graph construction. What makes GraphSmarts unique is that we built it with the graphing model in mind. This means that while students can make a large number of graphs from the data they are given, we specifically designed the features of the graphing tool to help us capture student competence in each of the graphing practices we try to measure. This means we can learn about student graphing through performance in an authentic task where students have lots of freedom to show both their skills and their confusion, yet have the results be auto-scored so that large numbers of students can be assessed.

We will be working on GraphSmarts under our latest NSF grant through 2025, and welcome classes that would like to participate. If you give the GraphSmarts assessment to your class, we will in turn provide data on the strengths and weaknesses of your students making graphs. Write to us at to learn more.

You can also see papers resulting from this project, including:

This material is based upon work partially supported by the National Science Foundation under Grant No. 1726180 and 2111150. 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.