Following closely on the release of the first learning pathway from the Data Science in Biotechnology cluster earlier this month, LabXchange is excited to announce that the Data Science–Driven Science Education (DSDSE) project has published another new learning pathway, Data Visualization, which explores the fundamentals of accurately representing and interpreting data.

Aimed at high school educators and learners, the resources within this pathway have been carefully designed to align to Next Generation Science Standards (NGSS) and AP standards, ensuring that they are highly relevant to secondary school curricula across the United States and beyond.

Below, learn more about the new pathway and check out a handful of the new learning resources that feature in it.

Data Visualization

From choosing a visualization type to labeling axes and intervals, the new Data Visualization pathway covers the fundamentals of communicating and interpreting data through graphs and charts. Have you ever seen a graph on the news and found it difficult to interpret on the fly? Have you ever created or been given a dataset in class and wondered what type of graph is best for representing it? Interpreting and communicating data through visualizations is an incredibly valuable skill in today’s world!

Learning Objectives

In this pathway, students will learn to:

1. Describe fundamental principles of data visualization (Tufte’s principles) and apply them in the creation of their own figures.
2. Describe the elements of each type of graph (bar graph, scatter plot, histogram or boxplot).
3. Illustrate a given dataset using the most relevant type of graph.
4. Use verbal and mathematical descriptors to characterize the rate at which a dependent variable is changing at different points in a line graph.

Note: Learning resources about boxplots and spreadsheet analysis are coming soon!

Featured Resources

This pathway includes a variety of learning resources, including texts, infographics, interactives of various types, a simulation, and a question set. In addition, two resources within this pathway are accompanied by our newest resource type, the worksheet, which gives educators direct access to a printable worksheet designed to enhance students' engagement and learning with each resource.

Introduction to Data Visualization (text + images)

This resource introduces the topic of visualizing data and touches on some of the principles involved in faithful visual depiction of data. It also discusses some of the history of, and key people in, the data science field’s development.

How to Make a Histogram (scrollable interactive)

How do we describe data accurately? This scrollable interactive walks you through how to construct a major component of data visualization, the histogram.

Interpolation in Line Graphs (interactive widget + worksheet)

In this interactive widget, learn about interpolation and try plotting line graphs for the data that results from different sampling schedules to see the possible effect of interpolation.

Data Visualization Summary and Decision Tree (text + infographic)

This text and infographic summarize the topic of visualizing data and take the learner through a decision tree for choosing a suitable chart type.

About the Data Science–Driven Science Education Project

With generous support from the U.S. Department of Defense (DoD) STEM, the DSDSE project was launched in 2023 as an ambitious initiative aimed at educating the next generation of learners on the the incredible real-world importance of data science and data literacy.

The project will provide sustainable, long-term data science resources for high school students and educators that will augment national digital literacy by integrating data science with existing high school STEM curricula and building educator capacity to confidently lead students in data science explorations.

Learn more in the initial DSDSE project announcement and visit the DSDSE project page to stay up to date on what's coming next.