Information Brief

Graphing Behavioral Data

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Data Collection Overview

It is often easy for educators to recognize when a student’s behavior is happening and how it is impacting the classroom. However, without data, educators might make incorrect assumptions about how frequently a behavior occurs or how long it lasts based on opinions, feelings, inaccurate recollections, or incomplete information. A systematic process for collecting and analyzing behavioral data in a consistent and accurate manner reduces this subjectivity. Additionally, it helps educators:

• Identify patterns related to when, where, and how behavior occurs
• Make informed decisions about how to address behavior
• Determine if behavioral supports and interventions have been effective
• Decide if an intervention should be continued, adapted, or stopped
• Monitor student progress over time
• Communicate behavioral progress to students, parents, and other school professionals

Graphing Data

Regardless of the specific method of data collection that is chosen, behavioral data are easiest to interpret when graphed. Unlike a list of numbers or a stack of data recording sheets, a graph offers educators a simple visual representation that can help them make quick instructional decisions. Some of the additional benefits of graphing for both educators and students are outlined in the table below.

Benefits for Educators	Benefits for Students
Allows educators to visually monitor a student’s progress Helps educators identify patterns related to when, where, and how behavior occurs Helps educators evaluate the effectiveness of behavioral supports or interventions Provides educators a visual for communicating with students, parents, and other professionals	Offers students a visual representation of their progress Allows students to see the relationship between effort and performance (e.g., that hard work pays off) Allows students to set appropriate goals for themselves Motivates students to either maintain their efforts or work harder

Although there are numerous types of graphs, line graphs are most often used to represent behavioral data. When using line graphs, educators plot data points over a given period, connect the adjacent plotted data points to create a line, and then interpret the shape of the connected line.

Steps for Implementation

1. Create a line graph. The grid for the line graph must be set up to align with the observation schedule and the nature of the data collected. It should include labels for both axes:
   • The x-axis—the horizontal line at the bottom of the graph—represents time (e.g., days, observation sessions, class periods).
   • The y-axis—the vertical line on the left side of the graph—represents the quantitative measurement of the behavior (e.g., rate, percentage of intervals, percentage of observation session, DBR rating).
2. Plot the data on the graph. Data is transferred to the graph by plotting a point to represent the behavioral occurrence at each time. For example, if frequency data show that a student engaged in a target behavior seven times during Observation Session 1, a point would be plotted at (1, 7) on the graph. A solid line is then drawn to connect each point to the next.
3. Analyze the data. Once the line graph has been constructed, it can be visually analyzed to identify:
   • Level—the behavior’s overall magnitude (e.g., high, moderate, low)
   • Trend—whether the behavior is increasing, decreasing, or staying the same over time
   • Variability—how consistent or fluctuating the rate of the behavior is

Based on this visual analysis, educators can determine the effectiveness of current supports and interventions and make adaptations if needed.

Tips for Implementation

• To more easily analyze the data, create a simple, uncluttered, and clearly labeled graph.
• To facilitate ongoing visual analysis of emerging trends, set up the graph early and plot data points as they are collected, rather than waiting to graph a large batch of data.
• To obtain an accurate reflection of student performance, aim for at least six to eight data points before analyzing the graph. Daily behavior can fluctuate due to factors like illness or fatigue, making a greater number of data points essential to minimize outliers and related misinterpretation.
• Teach students how to graph their own data to help them see their progress over time.
• If data are being collected on multiple behaviors simultaneously and both use the same type of measurement, represent both on the same line graph. Use a different geometric symbol (e.g., circle, triangle, square) for each behavior and provide a key to clearly denote which line represents which behavior. Review the example below.

  

• Consider using spreadsheet software or web-based tools to transform raw data into line graphs. Such tools can be much more efficient than graphing by hand and reduce the likelihood of human error.

For information about other data collection methods as well as graphing data, visit the following IRIS resources:

• Measuring Behavior
• Direct Behavior Rating
• Scatterplot Recording
• Systematic Direct Observation