How to Read a Graph: A Simple Data Literacy Framework for K-12 Classrooms (PPSTT)
A practical approach to teaching real data literacy
In the Information Age, data literacy is literacy. Students see graphs everywhere in class, in the doctor’s office, when trying to make healthcare or financial decisions. Yet there are big gaps in the way students are prepared to make informed decisions and flourish in a flood of data.
One of the most important skills is learning how to read a graph. From elementary classrooms to high school and beyond, students need to be able to interpret graphs, analyze patterns, and make sense of data.
However, many students struggle with reading graphs and developing strong data interpretation skills. What students need is a clear, consistent process for what to do when they encounter a graph.
This is where a simple data literacy framework can make all the difference.
What is Data Literacy? Why is Data Literacy Important in Education?
Before diving into the framework, let’s get clear on the meaning of data literacy.
Data literacy is the ability to read, interpret, analyze, and communicate data. Data literacy skills include:
Understanding graphs and charts
Identifying patterns and trends
Interpreting data accurately
Evaluating whether data can be trusted
Teaching students how to interpret graphs helps them:
Think critically
Ask better questions
Make informed decisions
A Simple Idea for How to Read a Graph (A “PEMDAS for Graphs”)
What if students had a simple, consistent way to approach any graph?
When students approach a mathematical problem, they know the order of operations (PEMDAS). They know to evaluate pieces of the expression in order: Parentheses, Exponents, Multiplication, Add, Subtract. But when even advanced learners are trained to make sense of figures and charts, there is no equivalent, detailed framework guiding sensemaking.
When our team explored available resources, we found frameworks like the National Center for Science Education’s DataWISE Tool that focus on interpreting data in a media literacy context. And we found frameworks like I^2 (Identify and Interpret) Strategy, which does not fully unpack the steps needed to make sense of data figures, or general routines like CER (Claim Evidence Reasoning). While all these frameworks are valuable tools for critical thinking, they fall short of addressing the very first challenge of data literacy—how do I make sense of a graph?
While working with Dr. Tom Luhring (an ecologist at Wichita State) to develop our free high school unit “Data Streams: A crash course in data literacy using stream ecology,” we realized that student engagement with his authentic research depended on building stronger foundational skills in data literacy. Thus, we set out to develop a framework that works across subjects, reflects how experts think, and is simple enough to use immediately.
Over months of research and development, this led to the PPSTT framework (psst…it’s the secret to data literacy).
The PPSTT Framework for Graph Interpretation
To make this process simple and memorable, we developed the PPSTT framework, which students can use to read graphs in any subject.
Patterns (What do you notice?)
Prompts (What does the text tell you?)
Strange (Are there outliers, missing points, or unusual areas in the data?)
Takeaway (What’s the story?)
Trust (Do you trust the story?)
It guides students from: What do I see? → What does it mean? → Can I trust it?
How to Analyze a Graph using PPSTT: How It Works
1. Patterns— Start with observation
Look for trends, shapes, highs/lows, and overall structure. What type of graph or chart is this? What am I seeing? This builds the foundation for understanding graphs.
2. Prompts— Use the context
Titles, axes, units, and particularly the caption and data attribution (or lack thereof) provide essential meaning and help students read graphs accurately.
3. Strange— Find what stands out
Outliers, gaps, and scale differences often hold key insights. This step ensures accurate and deeper graph analysis.
4. Takeaway — Build a claim
Use evidence from the graph to explain what’s happening. This strengthens core data interpretation skills.
5. Trust — Evaluate the data
Is anything misleading? What might be missing? This step flows naturally into the DataWISE and other media literacy approaches to data literacy, diving deeper into what it means to be a “reputable” source and helping students determine: What should I do with information?
An interesting note is that many college courses (and our earliest version of this framework) suggest you should start by “reading the title and other text” first. However, after working with Dr. Luhring, his grad students, asking other scientists, and examining my own approach to data sensemaking, we realized that humans actually look at the pattern first.
The eye naturally first tries to determine the type of figure and notice any patterns, so this framework is informed by natural tendencies of professional data analysts and scientists. The steps are ordered in a logical fashion, but they necessarily connect and build on each other.
As you read text to gain additional context, your eye naturally darts back to the pattern, which may help you notice something strange, like an outlier. All of this feeds into your takeaway as you digest the figure’s meaning. Finally, and importantly, one must determine if they trust the takeaway.
Graph Analysis Example: See the PPSTT in Action
Watch Tom and his grad students provide cognitive apprenticeship, doing a think-aloud to show how scientists apply the PPSTT to their natural sensemaking of figures.
Teaching Data Literacy in the Classroom: A Framework for Any K-12 Classroom
The PPSTT framework helps with teaching data literacy by:
Providing a simple, meaningful, and consistent routine that students can use (from elementary through high school and beyond)
Helping students build confidence with reading graphs
Encouraging critical thinking, discussion, and evidence-based reasoning
Students can apply the PPSTT framework to:
historical trends
social media data
sports statistics
financial graphs
everyday decisions
Our intro example uses Google Ngram data on how word usage in books changes over time. We chose this as the introduction (even though it doesn’t directly relate to ecological data like the other two lessons in Data Streams) because it taps into students’ inherent interest in words and allows instant buy-in and curiosity. And to circle back—in the Information Age, we need to encourage student curiosity and inherent interest in data as we support their lifelong data literacy journey with simple heuristic tools like the PPSTT framework.
The Bottom Line
Data literacy is a big goal—but it starts with a simple question:
What do I do when I’m looking at this graph?
PPSTT offers one clear answer, helping students learn how to read graphs, interpret data, and think critically in any subject.
FAQ: Data Literacy and Reading Graphs
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Data literacy is the ability to read, interpret, and use data effectively. It includes understanding graphs, identifying patterns, and making informed decisions.
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Data literacy in education helps students build critical thinking skills, evaluate information, and prepare for real-world decision-making.
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To read a graph, students should use the PPSTT framework:
Patterns: Start with observation
Prompts: Use the context
Strange: Find what stands out (identify unusual data points)
Takeaway: Build a claim (interpret the meaning)
Trust: Evaluate the data’s reliability
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Key graphing skills include:
identifying trends and patterns
understanding axes and labels
identifying outliers
interpreting data
evaluating data sources
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Teachers can support data literacy skills by:
using structured routines like PPSTT
incorporating real-world data
encouraging discussion and inquiry
practicing graph interpretation regularly
