December 12, 2023

ABA Discontinuous Measurement: Types, Examples, and Data Collection Strategies

Katherine Jester, MS, BCBA, LBA
ABA Discontinuous Measurement

Data collection is the bedrock of Applied Behavior Analysis (ABA), but it demands time and energy. We explain how discontinuous data collection can help you balance time with reliable data. Learn which measurements to use, best practices, and get data collection tips from ABA experts.

Inside this article:

ABA Discontinuous Measurement: Types, Examples, and Data Collection Strategies

What is Discontinuous Measurement in ABA?

In ABA, discontinuous measurement is a data collection method we use to break up a session into time intervals. Then, we take data on behavior during those time intervals. It works best for behavior that occurs frequently or when you have limited time and resources.

In discontinuous measurement, the data collector divides an observation period into intervals. They record data during these intervals. This method is also called “interval recording” or “time sampling.”  

Discontinuous data collection differs from continuous data collection, where the collector observes and records behavior throughout the entire session. ABA professionals use both methods to monitor ABA behavior intervention plans or track sessions like discrete trial training (download free discrete trial training sheets).

Conversely, discontinuous data offers a snapshot of behavior, not the complete picture. As a result, these methods tend to either underestimate or overestimate behavior patterns. However, in many situations, discontinuous collection can be more appropriate than continuous collection.

April Torres, M.Ed., BCBA

"Collecting data during specific intervals serves various purposes," says April Torres, M.Ed., BCBA.

"For instance, it can be time-consuming and redundant to use continuous data collection when we’re studying behaviors that occur very frequently. It’s also valuable for teachers overseeing entire classrooms where they don’t have the ability to take continuous data on one student. With careful planning, a teacher or Registered Behavior Technician (RBT) can collect discontinuous data on multiple students while managing the class effectively."

In fact, discontinuous data collection is quite popular. In the 2012 article Use of Discontinuous Methods of Data Collection in Behavior Intervention: Guidelines for Practitioners, the authors note that “due in large part to their ease of implementation, discontinuous collection is popular in practice and in applied research.” In the paper, published in the Behavior Analysis in Practice journal, the authors explain that data collectors and analysts must recognize that discontinuous data collection introduces some bias. Fortunately, they conclude that data collectors can use discontinuous data to make meaningful decisions as long as they account for the potential for biases and errors.  

Discontinuous measurement isn’t flawless, but it provides ABA professionals with a valuable way to collect data, particularly when juggling many tasks. Understanding how discontinuous measurements work is critical for any ABA professional who wants to make data-driven decisions to support client care.

Key Takeaways:

  • In discontinuous data collection, we only observe behavior during predetermined intervals.
  • Examples of discontinuous methods include whole interval recording, partial interval recording, and momentary time sampling.
  • Discontinuous methods tend to either underestimate or overestimate behavior patterns.
  • Selecting the right interval length for your target behavior is critical to collecting accurate and reliable data.
  • Usually, a shorter interval will provide more accurate data.
  • Electronic data collection with pop-up timing makes it far easier to keep track of intervals while collecting discontinuous data.

Types of Discontinuous Measurement in ABA

The types of discontinuous measurements include whole interval recording, partial interval recording, and momentary time sampling. Each approach offers key insights into behavior.

Whole Interval Recording in ABA

In whole interval recording, the data collector observes if a behavior occurs during the entire interval. This method underestimates behavior patterns. It’s best for studying behaviors you want to increase.

The observer splits up a session into several time intervals. They observe the target behavior during each segment. “Whole interval recording can underestimate the behavior’s frequency and duration,” shares Torres. “If the child engages in the behavior during the entire interval, the data collector will record it. However, if the child stops and starts within the interval, they won’t count it. As a result, the true frequency is higher than what the data might suggest.”

Torres adds, "With longer intervals, there’s a higher chance that the child will stop engaging in the behavior. Then, you won’t record the data and will underestimate their behavior patterns.”  

When to Collect ABA Whole Interval Recording Data

You should collect whole interval data:

  • Whenever you’re interested in increasing a target behavior. “We often use whole interval recording when we’re trying to monitor whether a positive behavior is increasing,” explains Torres. “For example, we might be interested in whether a child is spending the entire period working. Because whole interval recording underestimates frequency, it’s a conservative measure of whether our interventions are working.”
  • If you’re interested in knowing whether behavior occurs continuously without interruption over a specific time interval.
  • Whenever it’s impractical to record continuously.

How to Visualize ABA Whole Interval Recording Data

Graph whole interval data as the percentage of total intervals during which you observed the target behavior. You can visualize the data by creating a scatterplot. Place the session date on the x-axis and the average percentage of intervals on the y-axis.

To convert whole interval data into a percentage of intervals, count the intervals in which the behavior occurred. You can calculate the percentage of intervals in which the behavior occurred by dividing this count by the total number of intervals and multiplying that by 100.

Whole interval recording graph
Example of whole interval recording graph (Graphed as “percentage of intervals”)

ABA Whole Interval Examples

Here are some examples of whole interval recording data:

  • On-task behavior: A teacher uses whole interval recording to monitor a student's assignment engagement during a 30-second interval. In this scenario, the student must work on the assignment for the full thirty seconds.
  • Playtime behavior: A therapist working with a child utilizes whole interval recording to evaluate playtime behavior. They focus on the child playing with a specific toy uninterrupted for the entire three-minute interval.

Whole interval data is easier to collect than ABA continuous frequency or ABA duration data but can offer a biased picture of behavior.

Pros and Cons of ABA Whole Interval Recording Data

Whole interval recording data saves time and is useful in classroom settings. The cons include that it underestimates behavior and can be difficult to record


  • Saves time: It’s more time-effective to record data in certain intervals than continuously over a session.
  • Useful in classroom or large group settings: Whole interval recording demands less energy or time than continuously recording data. Teachers or ABA technicians working in a group can collect data without compromising the other children’s needs.  
  • Useful for measuring behaviors you want to increase: Whole-interval recording provides a conservative estimate of the behavior. If anything, it underestimates how long and how often the child engages in behavior. Overall, whole interval recording offers a conservative estimate of whether your intervention is working to increase behavior.  


  • Underestimates behavior: Whole interval recording underestimates the actual frequency of behaviors that do not last the entire interval. You can work around this bias when measuring behaviors you want to increase. If you’re trying to decrease the behavior, whole interval recording might give you a false sense that your intervention is working because it underestimates the behavior in general.  
  • Can be complex to record: Recording can be complex because the data collector must keep track of when intervals start and stop, all while observing the target behavior.
  • Limited applicability: Whole interval recording isn’t suitable for behaviors that frequently start and stop.

Our ABA whole interval recording template has everything you need to collect whole interval data and calculate the percentage of occurrence. Use this free, printable template to capture your measurements.

Partial Interval Recording in ABA

Partial interval recording measures whether a behavior occurs at any point within a time interval. It doesn’t directly measure frequency or duration but whether it occurred. Usually, it overestimates the behavior. It’s useful for measuring behaviors you want to decrease.

"Partial interval recording provides a useful overall view of a behavior. Start by defining intervals, like ten two-minute segments. If the behavior occurs at any time during the interval, mark it as present, and the data collector can stop observing,” emphasizes Torres. “However, marking it once can inaccurately suggest the behavior occurred throughout the interval. This means you risk overestimating behavior patterns. This bias can be managed effectively, especially when tracking behaviors targeted for reduction.”  

When to Collect Partial Interval Data

Here's more information about when to collect partial interval recording data:

  • When trying to decrease a behavior: Partial interval recording is valuable when working to reduce a specific behavior. It provides a conservative estimate of behavior patterns, so you won’t risk believing you’re reducing behavior when you’re not.
  • When you have limited time and cannot take data continuously: This method is a practical choice when time or resources are finite. The data collector can still take meaningful data on multiple students within a session.
  • For behaviors that don’t occur frequently: Partial interval recording works well for behaviors that occur sporadically. Unlike whole interval recording, it's better at catching these behaviors because it doesn't require them to last the entire interval.

How to Graph Partial Interval Recording Data

Collect partial interval data as the percentage of intervals in which the behavior occurred. Then, plot the average percentage for each session on a scatterplot. Use the y-axis for the percentage of intervals and the x-axis for the observation date.

Partial Interval Recording graph
Partial Interval Recording graph

Examples of Partial Interval Recording

Here are some examples of partial interval recording in various contexts:

  • Disruptive outbursts: A teacher uses partial interval recording to track a student’s behavior during two-minute intervals in a classroom. If the student displays disruptive behavior at any point within the interval, the data collector marks the behavior that occurred.
  • Hand flapping: An RBT uses partial interval recording to measure a child’s hand flapping for ten one-minute intervals. If the hand flapping occurs at any time within the minute, the data collector records it.
  • Inattention: A parent uses partial interval recording to monitor their child's inattentive behavior while doing homework. They divide the thirty-minute homework session into six five-minute intervals and record inattentive behavior.

Pros and Cons of Partial Interval Data

Partial interval data provides a generalized behavior view but allows data collectors to multitask. The major con is that it usually overestimates behavior.


  • Time efficient: As a discontinuous method, partial interval recording is less time-consuming than continuously monitoring the duration or frequency of a behavior. It’s much more feasible for a data collector to observe many students when they only collect data during set time intervals.
  • It’s a useful measurement for behaviors that you want to reduce.
  • It’s a good method for capturing behaviors that don’t occur often.


  • Overestimates behavior: This method underestimates behavior, which can provide a conservative way to track whether you’re successfully decreasing a problem behavior. The shorter the interval, the more accurate the data. However, shorter intervals are more challenging to time correctly.
  • The method isn’t as precise as doing continuous recording.
  • It can be complex to record: Partial interval recording doesn’t take as long as continuous methods, but recording can be more challenging. You’ll have to track interval lengths and when they start and stop, making it prone to error.

Use our free partial interval recording datasheet template to record and analyze your interval data.

Momentary Time Sampling in ABA

Momentary time sampling measures if a behavior occurs at the end of a specific time interval. BCBAs use this method when there’s limited time or resources to collect data. It tends to underestimate the behavior. It’s the most uncommon type and least precise discontinuous measurement.  

Momentary time sampling, also known as "momentary time intervals," is a type of discontinuous interval recording method, like partial and whole interval recording. The data collector observes and records data at the end of the interval. For example, if the entire interval is ten minutes long, the data collector might set an alarm for the nine-minute mark and observe the target behavior for the last minute of the interval.

"Typically, teachers use it when assessing a student's on-task behavior or when they have a specific interest in the timing of a particular behavior. However, we often opt for it when we don’t have a lot of time or resources and need a practical, efficient method,” explains Torres.

When to Use Momentary Time Sampling in ABA

You should use momentary time sampling data in ABA in the following situations:

  • In a classroom setting: Teachers commonly use this method to monitor whether a student stays on task during a period of solo or group work.
  • If you’re interested in the timing of behavior: "You can use this method to see if a student is still engaging in a given behavior towards the end of a designated period," notes Torres. "For example, you might assume that the kids play well together at the beginning of recess because you've noticed it before. However, if you take momentary time sampling data at the last minute of recess, you can see if they're still playing together. Of course, this doesn't mean they have been playing well together throughout the entire recess period, but it does provide useful data."
  • When you have limited time or resources: Momentary time sampling demands the least energy and time from the data collector, who only needs to pay attention for a short time. The method lends itself well to situations when the collector, say a teacher, must observe many students or engage in other tasks.

How to Graph Momentary Time Sampling in ABA

When graphing momentary time sampling data, present the data as percent of intervals in which the behavior occurred. Plot the average percentage on the y-axis and the date on the x-axis.

Momentary Time Sampling graph
Momentary Time Sampling graph

Examples of ABA Momentary Time Sampling

Here are some examples of momentary time sampling data:

  • Classroom engagement: A teacher observes a student's on-task behavior at the last 30 seconds of a five-minute interval to see if they’re still on task at the end of a lesson.
  • Social interaction: An RBT records whether a child engages in social interactions at the last minute of a ten-minute recess interval.

Pros and Cons of Momentary Time Sampling Data in ABA

The main benefit of momentary time sampling is that it only requires little time or energy. However, it is not particularly accurate and can provide a skewed picture of behavior.


  • Efficient: Momentary time sampling is the most efficient and least time-consuming data collection method in ABA.


  • Potential for missed data: There’s a high chance that you’ll miss some behavior when using the momentary time sampling method.

Consider practicing this method with our momentary time sampling datasheet template or using it in your next data collection session.

Planned Activity Check (PLACHECK) in ABA

A Planned Activity Check (PLACHECK) is a type of momentary time sampling. In a PLACHECK, the observer uses momentary time sampling to count the number of students engaged in an activity at the end of an interval.  

PLACHECKs help teachers and ABA professionals measure how many students engage in or pay attention to a task. The data collector observes behavior at the end of an interval. Instead of focusing on whether one person is engaging in a specific behavior, the data collector counts how many students in the group are doing the task or performing another target behavior (like playing at recess).  

When to Use PLACHECK Data

PLACHECK is best in these situations:

  • In classroom settings: A PLACHECK is particularly beneficial in classroom environments where educators aim to assess and enhance student engagement during group activities.
  • When you’re interested in group behavior: A PLACHECK allows professionals to monitor and potentially improve the participation of multiple individuals within a group.
  • When you have limited time and resources.

How to Graph PLACHECK Data in ABA  

Plotting the percentage of students engaged or on task during specific intervals is a common way to visualize PLACHECK data. The y-axis represents the average number of students on task during the observed intervals for a particular day. The x-axis indicates the observation date.


Examples of ABA PLACHECK Data  

Here are several examples of how teachers and BCBAs can use PLACHECK data:

  • Classroom participation: A teacher uses a PLACHECK to monitor how many students actively participate in a group discussion during the last minute of a ten-minute interval.
  • Group therapy: An ABA therapist employs a PLACHECK to assess children’s engagement in a group therapy session, tracking how many are on task during the last minute of five-minute intervals.

Pros and Cons of PLA-check Data in ABA

The main pro of PLACHECK is that it allows you to record data on multiple students. However, a PLACHECK doesn’t apply to many behaviors and can provide a biased snapshot.


  • Efficient data collection: A PLACHECK is a time-efficient method for assessing group behavior, allowing for data collection within set time intervals.
  • Focus on group behavior: A PLACHECK provides valuable insights into group behavior and helps educators and professionals manage and improve group activities.
  • Minimal time investment: A PLACHECK is a practical choice when there isn’t enough time or resources to collect continuous data on multiple students.  


  • Doesn’t provide individual data: PLACHECKs don’t capture individual behavior data.
  • Can be complex to record: To record PLACHECK data accurately, you’ll need to know when the interval begins and ends.
  • Can be inaccurate: A PLACHECK only records the last part of the interval so you won’t get data on what happened previously.

Try our comprehensive PLACHECK datasheet template to document your classroom data.

ABA Discontinuous Data Cheat Sheet

Our ABA discontinuous data cheat sheet offers a concise resource for understanding discontinuous data metrics. The single-page sheet provides quick-reference definitions, real-life examples, and advantages and disadvantages. Find guidance on when to use each metric.  

Discontinuous data collection is a cornerstone of ABA. It involves many different methods and options to suit your needs. This cheat sheet is a handy reference that breaks down every discontinuous data metric. Seasoned pros and new ABA students will find it a useful tool.

How to Implement Discontinuous Measurement in ABA

Implementing discontinuous measurements starts with goals. Then, assess how much time and resources you have for data collection. Determine which metric to use and make a data collection plan.  

“If you want to start collecting discontinuous data, first define your goals,” advises Torres. “Do you want to increase or decrease the target behavior? Or do you want to learn more about it? These questions will help guide you towards the metric and method leading to the best possible outcome.”

When implementing discontinuous data procedures, the key lies in selecting the appropriate metric and method for the task.

Here are some primary considerations:

  • Student's personality and abilities: Evaluate the student's capabilities and potential challenges to ensure the chosen measurement method aligns with their age, developmental level, and skillset.
  • Specific behavior: Different behavior classes might require a different approach. For example, a discrete behavior like hand-raising might lend itself to methods that won’t work for complex, indiscrete behaviors.  
  • Resources for data collection: Assess the available time and resources for data collection and consider the practicality of the chosen metrics and methods. Select the approach that works within your constraints and provides accurate and meaningful data.

Let's explore how each metric aligns with specific behavior goals:

  • Increase a positive behavior: If your goal is to boost positive behavior, whole interval recording data can be an excellent choice. This metric typically underestimates behavior, providing conservative feedback on the effectiveness of your interventions. Alternatively, consider using momentary time sampling data if you don’t have enough time or resources to collect whole interval data.  
  • Decrease a negative behavior: Partial-interval recording is a good choice whenever you want to decrease the frequency or duration of a negative behavior. This metric tends to overestimate behavior, resulting in conservative data. This overestimation provides more accurate feedback on whether the intervention plan is effective.
  • Monitor a group: PLACHECK data helps teachers and RBTs monitor the activity of larger groups of students.

Best Practices for ABA Discontinuous Data Recording

Defining your target behavior is the first step to picking a discontinuous data recording method. Other best practices include training data collectors and limiting how many you use. Also, use electronic data collection, especially for interval data.  

Certain best practices will improve your ABA data collection methods. Here are some tips from ABA experts:

  • Define your intervals well
    Torres stresses the length of the interval can affect your data and how you interpret it. “While shorter intervals often offer greater accuracy, they can be more challenging to measure. The key is to understand your objectives and the behavior you're observing to select the most suitable interval length. Be mindful of the inherent bias associated with different metrics, such as partial or whole interval recording.”
  • Create an operational definition
    Clearly define the behavior you're tracking. An operational definition ensures data collectors share a common understanding of it. This knowledge makes it more likely that they collect data on the same behavior.  
  • Don’t include too many data collectors
    Avoid involving too many data collectors. A streamlined team minimizes the potential for data collection inconsistencies, leading to more reliable and consistent results.
  • Use electronic data collection
    Electronic data collection methods can enhance efficiency and accuracy. These tools can streamline data collection, reduce human error, and facilitate data analysis, making it a practical choice in many cases.

“Discontinuous data requires less total time investment, but it can be even tricker to track,” points out Torres. “Imagine juggling different timers or continuously looking at the clock to figure out when you're supposed to record data. Software that has pop-up data collection helps the technician focus the child's programming and receive convenient, timed reminders when a new data collection interval is about to begin.”

Using Electronic ABA Data Collection for Discontinuous Data

Experts recommend using electronic data collection whenever you’re collecting discontinuous data. You’ll get alerted when intervals start and stop. It also instantly graphs and analyzes the data. The software helps you focus on observing the behavior, not the clock.  

Electronic data collection represents another shift of digitization in the ABA space. The benefits are clear: less human error, instant and accurate analysis, and more time spent with the children, not collecting or graphing data.  

These solutions eliminate the need to constantly monitor the clock by alerting you to when intervals start and stop. They streamline data collection, generating higher-quality data and leads to more informed interventions.

If you’re in the market for an electronic data collection software, particularly for discontinuous data collection, consider the following features:

  • Pop-up timers
    Pop-up timers alert you when an interval is about to begin or end. This feature is invaluable for collecting discontinuous measurements because data collectors don’t need to track both the clock and the target behavior.  
  • Includes all measurements and has customizable fields
    Some discontinuous metrics can be rare, like momentary time sampling. That said, pick a program that includes all measurements—you never know when you’ll need it. The program should also allow you to customize your time intervals and other fields like the “notes” column.
  • Graphing capabilities and instant analysis
    Quick graphing and instant analysis will save BCBAs and RBTs valuable time. Instead, they focus on developing fine-tuned intervention plans or communicating the results to stakeholders.
Graph of discontinuous data
Example of a software-generated graph of discontinuous data
  • Part of a fully integrated practice management software
    Consider purchasing a full practice management program with data collection functionality. This holistic approach simplifies ABA therapy administration and eliminates the complexities of integrating separate programs. Choosing a single software solution ensures data accuracy and centralized data management.

Comprehensive, Integrated ABA Data Collection

Understanding and evaluating data plays a crucial role in monitoring clients’ progress. Artemis' all-in-one practice management software helps with every step of patient care—from patient intake to insights. With integrated data collection and analysis, Artemis helps turn your data into action.  

Artemis ABA software offers a comprehensive solution that allows you to conveniently record all types of discontinuous measurements in a single platform. Our pop-up timers eliminate the need for manual interval tracking. Unlike other ABA software that require integrations, Artemis ABA provides a dependable and interconnected data system that stores all your valuable information in one centralized location. Our software transforms collected data into actionable insights, supporting well-informed treatment decisions.

Our practice management solution is designed to be adaptable and tailored to meet the needs of any ABA practice. ABA therapists can use the software to effectively utilize the collected data to monitor client development and make well-informed treatment decisions. Unlike most ABA software, Artemis ABA has it all under one roof, including reliable, in-house clinical data management—it’s the online companion your ABA practice deserves.

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Katherine Jester, MS, BCBA, LBA

Clinical Technical Solutions | Board Certified Behavior Analyst & Mental Health Therapist 

Katherine Jester is a Michigan-based BCBA and mental health therapist with 10+ years of experience helping diverse clinical populations. Katherine completed her graduate work at the University of Michigan and has had the privilege to work with incredible kids and families in both residential treatment and outpatient clinic settings. She is proud to support the clinical development of Artemis ABA, and enjoys working with Applied Behavior Analysis (ABA) practice stakeholders to put time and flexibility back in the hands of their teams.