Data Types Overview

Why this brief

Data is the bread and butter of a para's day. Every IEP, behavior plan, and progress report rests on it. But the word "data" can mean a lot of things: sometimes a tally on a clipboard, sometimes a stopwatch reading, sometimes a check mark on a prompt sheet. Picking the wrong type of data, or writing it down the wrong way, makes the data useless and your time wasted.

This brief is the map: what each data type measures, when to use it, what it looks like, and what good versus bad data looks like for paras. Other briefs in section 06 go deeper into one method at a time (interval recording, prompt-level data, ABC notes). This one shows you the whole map.

The data rule. Data exists to answer questions. Before you write down anything, the team should be able to say what question this data answers. "How often is the behavior happening?" is a real question. "Some kind of behavior data" is not.

Who this brief is for

• Paras writing down data on school work, behavior, talking, or self-help goals.

• New paras still figuring out what "take data" means in their room.

• Supervising teachers and case managers helping paras pick the right data type for the question.

• Anyone looking at data sheets and wondering if they are useful or just noise.

The seven main data types

Most school data is one of these. Each one measures something different. Each one answers a question well and answers another question badly.

Plus one method that mixes several of these into a story:

ABC notes (antecedent-behavior-consequence): written notes that catch the context around a behavior the team doesn't yet understand. Covered in brief 06.04.

Match the data to the question. If you can't say what question your data is supposed to answer, you're writing down noise. "How often does Mateo ask for a break?": frequency. "How long does he stay engaged in math?": duration. "Can he do the steps with less help over time?": prompt level. The question picks the type.

Frequency and rate

What it is

Frequency is a count: how many times the behavior happened during the window. Rate is the count divided by time so you can compare windows of different lengths. Example: 12 hand-raises in a 30-minute lesson is a frequency; 24 per hour is a rate.

When to use it

• The behavior has a clear start and stop (each one is countable).

• It happens at a rate you can actually catch: somewhere between every few minutes and every few days.

• You care about how often more than how long.

Examples: hand-raises, asking for help, hitting peers, off-topic questions, leaving the seat, words spelled right.

When NOT to use it

• The behavior is too fast or too constant to count well (vocal stims, fidgeting).

• Length matters more than count (on-task vs. off-task, use duration).

• Behaviors blur into each other (one long meltdown vs. four small ones, use intensity or duration).

How to write it down

• Tally marks on a sheet: the simplest method.

• Click counter (golf counter on the wrist): useful when you can't take your eyes off the student.

• Wristband ticker, sticky notes for each one, paper clips moved across pockets.

• Apps like BehaviorSnap or Catalyst, if your district uses them.

Whatever you use, spell out the behavior clearly and the same way every time. "Yelled" is fuzzy. "Used a voice loud enough that the next desk could hear, when not called on" is not.

Duration

What it is

How long a behavior lasted. Total duration adds up all the times across the window; mean duration is the average length of each one.

When to use it

• Length is what matters: on-task time, sleep time, tantrum length, time spent in self-stim.

• The behavior could last anywhere from a few seconds to a long stretch, and that range matters.

Examples: on-task during independent work, time engaged with a peer, length of meltdowns, time in a cool-down spot.

When NOT to use it

• Behaviors that are basically instant (a hit, a yell, count instead).

• You only have your eyes on the student now and then: duration usually needs close watching.

How to write it down

• Stopwatch: phone or kitchen timer works fine.

• Start and stop times noted on a sheet.

• Apps made for duration.

If you are tracking on-task time, spell out what counts as on-task before you start. Eyes on the work? Hands on the materials? Making output? Be clear or your data will drift between the people watching.

Latency

What it is

Time between a cue (often a teacher direction) and the student's response. Short latency = quick response; long latency = slow start.

When to use it

• Following directions: "how long does it take to start after I ask?"

• Transitions: "how long from the bell to seated and ready?"

• Processing goals: checking whether wait time and supports are cutting the latency over time.

• Some communication goals: wait time before starting a response on an AAC device.

How to write it down

• Stopwatch starting at the cue, stopping when the student begins the response.

• Note when the teacher gave the direction; note when the student started.

• Watch for things that throw it off: did the student hear the direction? Was a peer in the way? Note these so the data isn't misread later.

Latency is sensitive to the cue. Make sure the cue is the same across times you watch. A whispered redirect is not the same as a posted schedule cue. If you change the cue you've changed what you are measuring.

Intensity

What it is

How big the behavior was. Almost always measured on a set scale: because "intensity" usually means how serious, not the exact size.

When to use it

• Hitting or self-hurt where a tap and a punch are not the same.

• Voice where loud and quiet matter (calling out vs. shouting).

• Crying or upset where mild fussing and a full meltdown should be tracked apart.

• Stims where some forms get in the way and some do not.

How to write it down

Use a set scale that everyone agrees on. Common scales:

Whatever scale you use, write down what each level looks like with real examples. Otherwise observers drift, and your "3" today might be someone else's "4" tomorrow.

Prompt-level data

What it is

How much help the student needed to do the skill. This is one of the most important data types for paras because it drives teaching right away. Without prompt data, you can't fade prompts; without fading prompts, you can't build independence.

Common prompt hierarchies

Different programs use slightly different scales. The idea is the same: rank from most help to least help, and write down which level each try needed.

How to write it down

During teaching, after each chance to do the skill, mark the lowest level of prompt that worked. Sample data sheet for putting on a shirt across 10 trials:

This data tells the team: she's moving forward, she's at gestural-to-verbal across tries, fade physical prompts entirely next session. Without prompt-level data, you'd just have "she's working on dressing": useless for changing teaching.

Be honest about prompts. The biggest data problem with prompt levels is over-prompting and then writing down "independent." If you said the answer first or guided their hand, that's not independent. That's verbal direct or partial physical. Write down the help you really gave. This is what really helps the student in the long run.

Permanent products

What it is

The output of the behavior: a worksheet, a finished task, a load of laundry, a journal page. Permanent products let you score the data later, often without watching the behavior happen.

When to use it

• Academic work: finished problems, words written, reading passages read.

• Job tasks: items packed, copies made, tables wiped.

• Self-help routines that make something: laundry done, lunch eaten.

• Communication: words said (recorded with consent) or AAC outputs (logged by the device).

Strong points

• Doesn't need you to watch every minute.

• Can be scored by anyone using the same scoring guide.

• Gives a record you can show (you have the real work).

• Can be scored later, by the teacher rather than the para in real time.

Cautions

• Can't tell you about the process: was the work copied from a peer? Was it done hand-over-hand?

• Should be paired with prompt-level data for skills being taught.

• Spell out what counts as "done" or "right" before scoring: fuzzy scoring guides make fuzzy data.

ABC notes (cross-reference)

ABC notes have their own brief (06.04). Short version: when a behavior is a concern but the team doesn't yet understand it, you write down the antecedent (what happened before), the behavior (what the student did), and the consequence (what happened next). Patterns across many ABC notes shape a guess about the function (see brief 05.01).

ABC is a story method, not a count. Use it when you need to understand a behavior, not just track it. Once a function is guessed and a plan is in place, you usually shift to frequency, duration, intensity, or prompt-level data tied to the plan's goals.

Picking the right data type

This is the question paras get wrong most often: usually because someone handed them a data sheet without saying why this one. A few ways to think it through:

Start with the question

Match data type to the behavior

Two data types are often better than one

Many goals need two things tracked at once. Examples:

• Hitting: frequency + intensity. "He hit twice today, once a 2 and once a 5."

• On-task: duration + permanent product. "She was on-task 22 minutes of 30, finished 8 of 10 problems."

• Asking for breaks: frequency + latency. "He asked 6 times today; average wait 4 minutes after a hard task."

• Toileting: frequency + prompt level. "Three trips, two with verbal cue, one independent."

Data quality: what makes data trustworthy

Bad data is worse than no data because it can lead the team to wrong answers. What trustworthy data looks like:

Clear behavior descriptions

Every behavior on a data sheet should be spelled out clearly enough that two people watching the same student would write down the same thing. "Disruption" is not clear. "Calling out without raising a hand, meaning words loud enough that the next desk over could hear" is.

People watching agree with each other

When more than one person takes data on the same behavior, they should agree on what they saw at least 80% of the time (some standards say 90%). If two paras watching the same hour come back with very different counts, the description needs to be tighter or more training is needed. The teacher or BCBA usually checks this from time to time.

Honest, real-time writing

Data filled in from memory at the end of the day is rarely right. People misremember the bad days as worse and the good days as better. Write it down as it happens, even if it's a tally on a sticky note that gets moved over later.

What you can keep up with

Data that is too much to actually take during a real school day will not get taken. Better to track one thing well than five things half-way. The simplest sheet that answers the question is usually the right one.

Respect for what's going on

Sometimes the data isn't taken because something else mattered more: a student in crisis, a fire drill, a sub. Note it. "No data, school assembly" is honest. Making up data to fill gaps is risky and dishonest.

If the data sheet is broken, fix it. If you can't make the data sheet work in your real day, that is information for the supervising teacher and BCBA. The fix is making the sheet simpler, changing the data type, or rethinking the timing, not white-knuckling through a bad design.

Privacy

Data sheets are school records under FERPA (see brief 13.01). Treat them like the IEPs they go with.

• Use student initials or codes on sheets that are visible in the classroom.

• File finished sheets in the student's locked folder; don't leave them out.

• Don't take photos of data sheets with your personal phone or email.

• Don't talk about specific data with anyone who doesn't have a school reason to know, including other paras.

• Recording video or audio for data needs district-level consent and family consent; don't make that call on your own.

Pitfalls

Scenarios

Scenario 1: A fuzzy data sheet for hand-raising

You've been handed a data sheet that says "Hand-raising: yes/no per period." The student raises his hand sometimes right, sometimes after blurting, and sometimes for completely off-topic comments.

This sheet doesn't answer a useful question. What does "yes" mean: at least one hand-raise? Bring this back to the supervising teacher and ask what the goal actually is. If it's about more right hand-raising, you want a count of right hand-raises (spelled out: hand raised before speaking, on-topic). If the goal is less blurting, that's a different behavior to count. The sheet should match the goal.

Scenario 2: A hard-to-count high-rate behavior

A student vocally stims pretty much non-stop through the morning. The team wants data on whether it's getting worse.

Frequency won't work. You can't count hundreds of sounds per hour well. Duration of total vocal-stim time would work but needs watching. Interval recording (see 06.02) is probably the best fit: split the period into 30-second windows and mark whether vocal stim happened during each one. This gives you a percentage that can be compared over time without burning out the para.

Scenario 3: Independence on a self-help skill

A student is learning to brush teeth. The IEP goal is "will independently finish tooth-brushing routine in 8 of 10 trials."

Permanent product alone won't tell you what's happening. You need prompt-level data per step. Break the routine into steps (get toothbrush, put on paste, brush all surfaces, rinse, spit, put away) and mark the prompt level for each step on each trial. Now you can see: she's independent on getting the toothbrush and paste, but still at modeling for brushing molars and partial physical for rinsing. Teaching targets the steps that still need help.

Scenario 4: Hitting that varies

A student is sometimes aggressive. The frequency hasn't changed but the team thinks the severity has.

You're tracking frequency only. That's why the change isn't showing up. Add intensity. Spell out a 1–5 scale (1 = open-hand tap, 5 = closed-fist or weapon use). Now you can see: same number of times, but average intensity has gone from 1.5 to 3.2 over a month. That's data that backs a plan change.

Scenario 5: A behavior the team doesn't yet understand

A student has started slamming his head on the desk during math but not during reading or other classes. The team has not yet figured out the function.

Frequency or duration alone will tell you it's happening but not why. Run ABC notes (see brief 06.04) for a couple of weeks. What was happening just before each time? What followed? Patterns will show up: maybe the work is too hard, maybe certain assignments, maybe times of day. Once a function is guessed, switch to a data system tied to the plan.

Scenario 6: Multiple paras, drifting data

Three paras rotate through your student's day. The data is all over the place: one para is writing down 4 hand-raises a day, another is writing down 30.

Either the description isn't tight, or someone is counting differently. Get the team together with the supervising teacher and BCBA. Watch the same period together. Talk about what counts. Write the description on the data sheet itself. Take inter-observer agreement data on a few sessions until everyone matches at 80%+.

Closing thought

Good data is one of the most powerful things paras add to a team. Teachers and BCBAs can't be everywhere. Paras can come closer. The data you take, if it's right and tied to a real question, drives teaching, behavior plans, IEP goals, and family talks. The data you take poorly (fuzzy, after-the-fact, or not honest about prompts) drives the team toward bad choices for the student.

The hardest part is usually picking the right type for the question and writing clear descriptions you can stick to. Once those are in place, the real writing-it-down becomes part of the rhythm of the day.

Bottom line. Data exists to answer questions. Match the type to the question. Spell out the behavior. Write it down in real time. Be honest about prompts. Pair types when one isn't enough. Keep it up. File it carefully. Push back when the system isn't working.

Related briefs

• 06.02 Interval Recording: for high-rate or long behaviors.

• 06.03 Prompt-Level Data: deeper look at the most important data type for fading.

• 06.04 ABC Narrative Recording: when you don't yet know the function.

• 06.05 IEP Progress Monitoring: tying data to goals.

• 05.01 Function-Based Thinking: what data is for, in behavior support.

• 04.02 Prompting Hierarchies: the prompt levels you'll be coding.

• 12.06 Working with the BCBA: your team member on data systems. (in expert review, not published yet)

• 13.01 FERPA and Confidentiality: data sheets are school records.

Frequency, duration, latency, intensity, prompt level, permanent product, ABC, and how to know which to use

For paraprofessionals who collect data in classrooms

Why this brief

Data is the bread and butter of a para's day. Every IEP, behavior plan, and progress report rests on it. But the word "data" can mean a dozen different things: sometimes a tally on a clipboard, sometimes a stopwatch reading, sometimes a checked box on a prompt-level sheet. Choosing the wrong type of data, or collecting it the wrong way, makes the data useless and your time wasted.

This brief is the orientation: what each data type measures, when each is the right choice, what each looks like in practice, and what good versus bad data collection looks like for paras specifically. Other briefs in domain 06 dig deeper into individual methods (interval recording, prompt-level data, ABC narrative). This one helps you see the whole map.

Who this brief is for

Paras who are collecting data on academic, behavioral, communication, or self-help goals

New paras still figuring out what "take data" actually means in their setting

Supervising teachers and case managers helping paras pick the right data type for the question

Anyone reviewing data sheets and wondering if they're useful or just noise

The seven main data types

Most school-based data falls into one of these categories. Each measures something different. Each has a question it answers well and a question it answers badly.

Plus one method that combines several of these into a narrative format:

ABC (antecedent-behavior-consequence) narrative recording: captures the context around behaviors that need understanding before counting can mean anything. Covered in detail in brief 06.04.

Frequency and rate

What it is

Frequency is a count: how many times the behavior occurred during the observation period. Rate is frequency divided by time so you can compare across different-length observations. Example: 12 hand-raises in a 30-minute lesson is a frequency; 24 per hour is a rate.

When to use it

The behavior has a clear start and stop (each instance is countable)

It happens at a rate you can actually catch: somewhere between every-few-minutes and every-few-days

You care about how often more than how long

Examples: hand-raises, requests for help, hitting peers, asking off-topic questions, leaving the seat, words spelled correctly

When NOT to use it

The behavior is too fast or too constant to count reliably (vocal stims, fidgeting)

Length matters more than count (on-task vs. off-task, duration is better)

Behaviors blur into each other (one long meltdown vs. four small ones, intensity or duration is better)

How to record it

Tally marks on a sheet: simplest method

Click counter (golf counter on the wrist): useful when you can't take eyes off the student

Wristband ticker, sticky notes for each instance, paperclips moved across pockets

Apps like BehaviorSnap, Catalyst, if your district uses them

Whatever you use, define the behavior precisely and consistently. "Yelled" is fuzzy. "Used a voice loud enough that the next desk could hear, when not called on" is not.

Duration

What it is

How long a behavior lasted. Total duration adds up all instances across the observation period; mean duration is the average length per instance.

When to use it

Length is what matters: on-task time, sleep time, tantrum length, time spent in self-stimulation

The behavior could last anywhere from a few seconds to a long stretch, and that variability matters

Examples: on-task during independent work, time engaged with a peer, length of meltdowns, time in cool-down

When NOT to use it

Behaviors that are essentially instantaneous (a hit, a yell, count instead)

You only have your eyes available occasionally: duration usually requires close watching

How to record it

Stopwatch: phone or kitchen timer works fine

Start/stop times noted on a sheet

Apps designed for duration recording

If you're tracking on-task or engagement, define what counts as on-task before you start. Eyes on the work? Hands on the materials? Producing output? Be specific or your data will drift between observers.

Latency

What it is

Time between a cue (often a teacher direction) and the student's response. Short latency = quick response; long latency = slow start.

When to use it

Compliance and following directions: "how long does it take to start after I ask?"

Transitions: "how long from the bell to seated and ready?"

Processing-related goals: measuring whether wait time and supports are reducing latency over time

Some communication goals: wait time before initiating a response on AAC

How to record it

Stopwatch starting at the cue, stopping when the student begins the response

Note when the teacher gave the direction; note when the student started

Watch for confounds: did the student hear the direction? Was a peer interrupting? Note these so the data isn't misread later

Intensity / magnitude

What it is

How big the behavior was. Almost always measured on a defined scale rather than a precise number: because "intensity" usually means severity, not size.

When to use it

Aggressive or self-injurious behavior where a tap and a punch are not the same

Vocal behavior where loud and quiet matter (calling out vs. shouting)

Crying or distress where mild fussing and screaming-meltdown should be tracked separately

Stereotypy where some forms are interfering and some are not

How to record it

Use a defined scale that everyone agrees on. Common scales:

Whatever scale you use, write down what each level looks like with concrete examples. Otherwise observers drift, and your "3" today might be someone else's "4" tomorrow.

Prompt-level data

What it is

How much help the student needed to do the skill. This is arguably the most important data type for paras to understand because it directly drives instruction. Without prompt data, you can't fade prompts; without fading prompts, you can't build independence.

Common prompt hierarchies

Different programs use slightly different scales. The principle is the same: rank from most help to least help, and track which level each opportunity required.

How to record it

During teaching, after each opportunity to perform the skill, mark the lowest level of prompt that worked. Sample data sheet for putting on a shirt across 10 trials:

This data tells the team: she's progressing, she's at gestural-to-verbal across opportunities, fade physical prompts entirely on next session. Without prompt-level data, you'd just have "she's working on dressing": useless for adjusting instruction.

Permanent products

What it is

The output of the behavior: a worksheet, a completed task, a wash-cycle of laundry, a journal entry. Permanent products let you score the data later, often without needing to watch the behavior happen.

When to use it

Academic work: completed problems, words written, reading passages decoded

Vocational tasks: items packaged, copies made, tables wiped

Self-help routines that produce something: laundry done, lunch eaten

Communication: words spoken (recorded with consent) or AAC outputs (logged by the device)

Advantages

Doesn't require you to watch every minute

Can be scored by anyone using the same rubric

Provides a defensible record (you have the actual work)

Can be scored after the fact, by the teacher rather than the para in real time

Cautions

Can't tell you about the process: was the work copied from a peer? Was it done with hand-over-hand support?

Should be paired with prompt-level data for skills being taught

Define what counts as "complete" or "correct" before scoring: vague rubrics produce vague data

ABC narrative recording (cross-reference)

ABC recording is its own brief (06.04). The short version: when a behavior is concerning but the team doesn't yet understand it, you record the antecedent (what happened before), the behavior (what the student did), and the consequence (what happened next). Patterns across many ABC entries inform a function-based hypothesis (see brief 05.01).

ABC is a narrative method, not a count. Use it when you need to understand a behavior, not just track it. Once a function is hypothesized and a plan is in place, you usually shift to frequency, duration, intensity, or prompt-level data tied to the plan's measurable outcomes.

Choosing the right data type

This is the question that paras get wrong most often: usually because someone handed them a data sheet without explaining why this one. A few ways to think it through:

Start with the question

Match data type to behavior characteristics

Two data types are often better than one

Many goals benefit from tracking two metrics. Examples:

Aggression: frequency + intensity. "He hit twice today, once a 2 and once a 5."

On-task: duration + permanent product. "She was on-task 22 minutes of 30, completed 8 of 10 problems."

Asking for breaks: frequency + latency. "He asked 6 times today; average wait 4 minutes after a difficult task."

Toileting: frequency + prompt level. "Three trips, two with verbal cue, one independent initiation."

Data quality: what makes data trustworthy

Bad data is worse than no data because it can lead the team to wrong conclusions. Some hallmarks of trustworthy data:

Operational definitions

Every behavior on a data sheet should be defined precisely enough that two people watching the same student would record the same thing. "Disruption" is not an operational definition. "Calling out without raising a hand, defined as words audible to the next desk over" is.

Inter-observer agreement

When more than one person collects data on the same behavior, they should agree on what they saw at least 80% of the time (some standards say 90%). If two paras watching the same hour come back with very different counts, the operational definition needs sharpening or training. The teacher or BCBA usually checks this periodically.

Honest, real-time recording

Data filled in from memory at the end of the day is rarely accurate. People misremember the bad days as worse and the good days as better. Record as it happens, even if it's a tally on a sticky note that gets transferred later.

Sustainability

Data that's too complex to actually take during a real classroom day will not get taken. Better to track one variable well than five variables half-way. The simplest data sheet that answers the question is usually the right one.

Respect for context

Sometimes the data isn't taken because something else mattered more: a student in crisis, a fire drill, a substitute teacher. Note it. "No data, school assembly" is honest. Inventing data to fill gaps is dangerous and dishonest.

Privacy and confidentiality

Data sheets are educational records under FERPA (see brief 13.01). Treat them like the IEPs they're tied to.

Use student initials or codes on sheets visible in the classroom

File completed sheets in the student's secure folder; don't leave them out

Don't photograph data sheets to your personal phone or email

Don't discuss specific data with anyone who doesn't have an educational need to know, including other paras

Recording video or audio for data requires district-level consent and family consent; don't improvise

Pitfalls

Scenarios

Scenario 1: A vague data sheet for hand-raising

You've been given a data sheet that says "Hand-raising: yes/no per period." The student raises his hand sometimes appropriately, sometimes after blurting, and sometimes for completely off-topic comments.

This sheet doesn't answer a useful question. What does "yes" mean: at least one hand-raise? Bring this back to the supervising teacher and ask what the goal actually is. If it's increasing appropriate hand-raising, you want frequency of appropriate hand-raises (operationally defined: hand raised before speaking, on-topic). If the goal is reducing blurting, that's a different behavior to count. The sheet should match the goal.

Scenario 2: Hard-to-count high-rate behavior

A student vocally stims roughly continuously throughout the morning. The team wants data on whether it's getting worse.

Frequency won't work. You can't count hundreds of vocalizations per hour reliably. Duration of total vocal-stim time would work but requires watching. Interval recording (see 06.02) is probably the best fit: divide the period into 30-second intervals and mark whether vocal stim occurred during each interval. This gives you a percentage that can be compared over time without burning out the para.

Scenario 3: Independence on a self-help skill

A student is learning to brush teeth. The IEP goal is "will independently complete tooth-brushing routine in 8 of 10 trials."

Permanent product alone won't tell you what's happening. You need prompt-level data per step. Break the routine into steps (get toothbrush, apply paste, brush all surfaces, rinse, spit, put away) and mark the prompt level for each step each trial. Now you can see: she's independent on getting the toothbrush and paste, but still at modeling for brushing molars and partial physical for rinsing. Instruction targets the steps still requiring help.

Scenario 4: Aggression that varies

A student is occasionally aggressive. The frequency hasn't changed but the team thinks the severity has.

You're tracking frequency only. That's why the change isn't showing up. Add intensity. Define a 1–5 scale (1 = open-hand tap, 5 = closed-fist or weapon use). Now you can see: same number of incidents, but average intensity has gone from 1.5 to 3.2 over a month. That's data that supports a plan revision.

Scenario 5: A behavior the team doesn't yet understand

A student has started slamming his head on the desk during math but not during reading or other subjects. The team has not yet figured out the function.

Frequency or duration alone will tell you it's happening but not why. Run ABC narrative recording (see brief 06.04) for a couple of weeks. What was happening just before each incident? What followed? Patterns will emerge: maybe demands above his level, maybe specific assignments, maybe times of day. Once a function is hypothesized, switch to a data system tied to the plan.

Scenario 6: Multiple paras, drifting data

Three paras rotate through your student's day. The data is wildly inconsistent: one para is reporting 4 hand-raises a day, another is reporting 30.

Either the operational definition isn't tight, or someone is counting differently. Get the team together with the supervising teacher and BCBA. Watch the same period together. Discuss what counts. Write the operational definition on the data sheet itself. Take inter-observer agreement data on a few sessions until everyone matches at 80%+.

Closing thought

Good data is one of the most powerful things paras contribute to a team. Teachers and BCBAs can't be everywhere. Paras can come closer. The data you take, if it's accurate and tied to a real question, drives instruction, behavior plans, IEP goals, and family communication. The data you take poorly (vague, after-the-fact, or unhonest about prompts) drives the team toward bad decisions for the student.

The hardest part is usually picking the right type for the question and writing operational definitions you can stick to. Once those are in place, the actual collection becomes part of the rhythm of the day.

Related briefs

06.02 Interval Recording: for high-rate or long-duration behaviors

06.03 Prompt-Level Data: deeper dive on the most important data type for fading

06.04 ABC Narrative Recording: when you don't yet know the function

06.05 IEP Progress Monitoring: tying data to goals

05.01 Function-Based Thinking: what data is for, in behavior support

04.02 Prompting Hierarchies: the prompt levels you'll be coding

12.06 Working with the BCBA: your collaborator on data systems (in expert review, not published yet)

13.01 FERPA and Confidentiality: data sheets are educational records