Interview Intelligence Slides Advanced Data Methodologies
Interview Intelligence
Mastering the art of indirect assessment and the Functional Assessment Interview (FAI).
Module 01 // Indirect
Why Indirect?
Indirect assessments provide the foundation for our direct observations. They help us identify:
Potential environmental triggers (Antecedents)
Maintaining variables (Consequences)
Historical trends and medical factors
"The interview is not the assessment; it is the map that tells us where to look."
The Hook: The "No Reason" Trap
Teacher: "He just screams for no reason. It's totally random. He can be doing fine, and then—BOOM—he's under the desk."
As a graduate clinician, how do you steer this stakeholder toward functional descriptors without "leading the witness"?
Technique 1: Time Anchoring
"Tell me about a time today when it DIDN'T happen."
Technique 2: Specificity funnel
"What was the very last thing said right before he went under?"
Technique 3: Biological Scan
"Is there a pattern related to sleep or meals?"
Interview Modalities
Structured (FAI)
Pros:
High reliability across interviewers
Ensures no domain is missed (e.g., medical)
Clear operational definitions
Cons:
Can feel "clinical" or impersonal
Time-intensive
Unstructured
Pros:
Builds rapport naturally
Flexible to the speaker's narrative
Cons:
Prone to recall bias
Missing critical environmental data
Anatomy of the FAI
1
Operational Definitions
Pinpointing the topography. Not just "aggressive," but "closed fist contact with torso."
2
Setting Events
Biological, social, or environmental conditions that change the value of a reinforcer.
3
Predictors (A)
Specific people, places, times, or activities that trigger the behavior.
4
Maintaining Variables (C)
What does the student get or get away from? (Attention, Tangible, Escape, Sensory).
5
Efficiency
Why this behavior vs. the appropriate one? Is it faster? Easier? More reliable?
6
Summary Statements
The "Hypothesis Statement" that guides the entire FBA process.
Next Steps: The Practicum
We will now move into our role-play simulation. You will be paired with a "Difficult Stakeholder" and must complete a 4-section FAI draft within 15 minutes.
Watch For:
• Avoid leading questions ("It was for attention, right?")
• Redirect anecdotal venting to behavioral events
• Verify through "paraphrase checks"
Clinical FAI Practicum Worksheet Clinical FAI Practicum
Assessment Tool // Indirect Methods // Graduate Level
Student Name
Date
Section 1: The Topography Funnel
Scenario: A teacher describes a student's behavior as "explosive outbursts." Your task is to use clinical probing to refine this into a measurable, operational definition.
Initial Stakeholder Descriptor:
"He just explodes. He loses his mind, screams, and throws things. It's violent."
Probing Question 1 (Targeting Topography):
Probing Question 2 (Targeting Magnitude/Intensity):
Drafted Operational Definition:
Include onset/offset criteria and exclusions.
Section 2: Environmental Mapping
During the interview, map the environmental variables mentioned. Identify missing information gaps that require further probing.
Category Interview Findings (Stakeholder Mentions) Setting Events (Sleep, diet, medication, social stressors) Antecedent Predictors (Demands, transitions, noise, lack of attention) Consequent Maintenance (What happens immediately after?)
Identified Information Gaps:
Section 3: Clinical Hypothesis
Synthesize your findings into a summary statement using the following format:When [Antecedent/Setting Event] occurs, the student [Behavior] in order to [Function].
Potential Function(s):
Escape / Avoidance
Attention (Peer/Adult)
Access to Tangibles
Sensory / Automatic
Confidence Level (1-10):
Note: This hypothesis must be verified via direct observation (Module 2-4).
Interview Facilitation Guide Interview Facilitation Guide
Teacher Resource // Practicum Scenarios // Graduate Level
Instruction Overview
This guide supports the implementation of the "Clinical FAI Practicum." The goal is to challenge graduate students to move past vague, anecdotal descriptions and extract high-fidelity behavioral data from stakeholders who may be emotionally overwhelmed or biased.
Student Learning Targets
Differentiate topography from interpretation.
Identify missing environmental variables.
Formulate a function-based hypothesis statement.
Role-Play Setup
Divide students into pairs. Student A: Clinician. Student B: Stakeholder (Teacher or Parent). Swap after 15 minutes.
Stakeholder Scenarios (Scripts for Student B)
Scenario 1: The "Everything is a Trigger" Teacher
Complexity: Moderate
Backstory: You are a kindergarten teacher, Ms. H. Your student, Leo, is "aggressive."The "Trap": When asked for triggers, insist it's "everything." Use vague terms like "disrespectful" and "mean."Success Criteria for Clinician: They must get you to identify *one* specific task (e.g., transitions to math) as the primary antecedent.
Scenario 2: The "Sensory-Only" Parent
Complexity: High
Backstory: You are the parent of a 14-year-old, Maya. She flaps her hands and yells.The "Trap": Insist it's "biological" or "just autism" and that it has no environmental function.Success Criteria for Clinician: They must probe for antecedents like "denied access to tablet" or "loud sibling noise" that change the rate of behavior.
Clinician Performance Checklist
Use this to circulate and provide feedback to students acting as Clinicians.
Clinical Skill Look-For Indicators Operational Clarification Does the student ask: "What does that look like exactly?" or "If I were a video camera, what would I see?" Redirecting Narrative Does the student pivot away from venting? "I hear that it's frustrating, but let's talk about the 2 minutes before the scream." Leading-Question Avoidance FAIL POINT: Asking "Did he do it for your attention?" instead of "How did you respond after he screamed?" Summary Validation
Pulse of Behavior Slides Module 02 // Direct Observation
Pulse of Behavior
The mechanics and mathematics of event recording and frequency counts.
TECHNICAL PROFICIENCY: FREQUENCY
The "50 Screams" Problem
A student screams 50 times in a school day.
Is this severe?
• Scenario A: Each scream lasts 0.5s
• Scenario B: Each scream lasts 10min
"Frequency tells us how often, but it is blind to magnitude and temporal duration."
Why does frequency alone fail as a clinical measure of severity?
When to use Event Recording
Discrete Trials
The behavior has a clear beginning and clear end (e.g., kicking, asking a question).
Steady Rate
The behavior is relatively brief and consistent in its duration.
Too High to Count
Frequency fails if the rate is so high it is impossible to count accurately (e.g., rapid hand flapping).
From Frequency to Rate
"Frequency is a count. Rate is a comparison."
Observation Time
20 min
/
Count
10 occurrences
=
Rate
0.5 / min
Why calculate rate? Because observation sessions vary in length. Rate allows us to compare apples to apples.
Capturing Magnitude
When frequency doesn't tell the whole story, clinicians must add a Magnitude Scale.
1 Minor (Verbal only)
2 Moderate (Property destruction)
3 Severe (Physical injury potential)
Lab Activity Preview
You will watch 3 video clips. You must decide:
Frequency vs Rate Lab Frequency vs. Rate Lab
Technical Lab // Quantitative Measurement // Graduate Level
Student Name
Date
Part 1: The Mathematics of Rate
Complete the following calculations to normalize behavioral data across varying observation periods.
Session Raw Count (f) Duration (min) Rate (f/min) A 12 30 B 4 10 C 35 45
Clinical Interpretation:
Based on the rates above, which session actually demonstrated the highest behavioral intensity? Justify your answer using the data.
Part 2: Integrating Magnitude
Event recording can mask the true "cost" of a behavior. Review the following behavior log for a student (Sam) and assign a Magnitude Score (1-3) to each event.
Scoring Legend: 1 = Minor disruption; 2 = Disruption + Property impact; 3 = Danger to self/others.
Timestamp Behavioral Topography Observed Mag Score 09:15 Screams "NO" at teacher; sweeps pencils off desk. 09:18 Throws plastic chair toward empty corner. 09:45 Screams "NO" at teacher. No property contact. 10:02 Bites own hand (left) leaving red marks.
Synthesize the "Severity Pulse":
If the FBA report only said "Frequency of 4 in 60 minutes," what critical clinical information would be lost?
Part 3: Data Collection Tool Design
Design a simple but effective paper-and-pencil tally sheet for a teacher who has only one hand free and needs to track "Calling Out" (f) and "Out of Seat" (f).
[Draft Tally Sheet Layout Here]
Measurement Accuracy Key Measurement Accuracy Key
Teacher Resource // Pulse of Behavior // Answer Key
Part 1: The Mathematics of Rate
Session Calculation Correct Rate A 12 occurrences / 30 min 0.4 / min B 4 occurrences / 10 min 0.4 / min C 35 occurrences / 45 min 0.78 / min
Clinical Logic (Discussion Points):
Session C has the highest rate. Sessions A and B demonstrate identical rates despite the raw counts being significantly different—this highlights why reporting raw frequency without observation duration is clinically negligent in a professional FBA.
Part 2: Integrating Magnitude
Time Behavioral Topography Mag Score Rationale 09:15 Screams "NO"; sweeps pencils. 2 Disruptive + Property impact (pencils). 09:18 Throws plastic chair. 2 High magnitude property destruction; no injury. 09:45 Screams "NO". No contact. 1 Minor disruption; no safety risk. 10:02 Bites own hand; red marks. 3 Self-injurious behavior (SIB). Danger to self.
Critical Synthesis:
Reporting only a frequency of 4 hides the fact that the behavior escalated to SIB. Frequency tracks the existence of behavior; magnitude tracks the clinical urgency.
Part 3: Data Collection Design
Effective Design Elements:
Pre-written codes for behavior types.
Ample white space for tally marks.
Clearly labeled timestamp/session duration slots.
Hand-held size (5x7 or clip-on).
Design Failures:
Too much "open narrative" space (distracts from tallying).
Requiring complex handwriting for a high-rate behavior.
No space to record session start/end times.
Temporal Dimensions Slides Module 03 // Temporal Measures
Temporal Dimensions
Precision measurement of duration, latency, and IRT in clinical settings.
Chronometric Analysis
The "Passive Refusal" Paradox
A teacher says:
The Problem with Frequency:
If we only count 'Compliance,' the data says he followed the direction (100% compliance).
The Solution: Latency
Measuring the elapsed time between the SD (Discriminative Stimulus) and the Response.
Core Temporal Concepts
Latency
Time from prompt to start.
"Leo, please sit down."
Duration
Time from start to end.
Leo starts screaming.
Advanced Concept: IRT
Inter-Response Time: The time between two successive responses.
R1
Time (IRT)
R2
Why measure IRT? It predicts bursting and patterning. Low IRT = High Rate.
Practical Challenges
The "Start/Stop" Problem: When does a behavior actually end? (The 5-second silence rule).Observer Fatigue: Keeping a stopwatch running during a 2-hour meltdown.Multi-Tasking: Prompting the student while measuring the latency of their response.
Workbook Activity
You will calibrate your timing skills against 5 video scenarios. Accuracy is paramount.
Timing Resistance Workbook Timing Resistance Workbook
Technical Practice // Temporal Measurement // Graduate Level
Student Name
Date
Section 1: Latency Calibration
Determine the latency for each scenario. Recall: Latency begins at the end of the SD and ends at the initiation of the response.
Case A: The Reluctant Transitions
ID: 03-LAT-A
10:00:00 — Teacher says, "Class, open your math journals to page 45."10:00:15 — Leo continues to sharpen his pencil.10:01:10 — Leo puts pencil away and touches the cover of his journal.
Onset (SD):
Calculated Latency:
Case B: Social Initiation
ID: 03-LAT-B
12:30:10 — Peer says, "Hey Leo, do you want to play tag?"12:30:15 — Leo looks at the peer.12:30:45 — Leo says, "Okay," and starts running.
Onset (SD):
Calculated Latency:
Section 2: Duration & Offset Criteria
The most difficult part of duration recording is determining the offset . As a clinician, you must define the "Silence Rule" (the amount of time behavior must cease to be considered one episode).
Scenario: Screaming
The student screams for 30s, stops for 3s, screams for 10s, stops for 2s, screams for 1min.
Your Offset Rule (e.g., 5 seconds of silence):
Total Duration of this Episode (based on your rule):
Clinical Rationale for this Rule:
Section 3: Inter-Response Time (IRT)
Calculate the Average IRT for the following sequence of self-stimulatory hand-claps:
0s [Clap] — 5s [Clap] — 12s [Clap] — 15s [Clap]
Interval 1:
Interval 2:
Interval 3:
Final Average IRT:
Temporal Scenario Script Temporal Scenario Script
Teacher Resource // Stopwatch Calibration // Graduate Level
Facilitator Instructions
This activity calibrates student timing accuracy. You will read the scripts below aloud or play the corresponding video clips. Students must use a stopwatch (or phone) to record Latency or Duration . Compare their results to the Master Key at the end of each round.
Round 1: Latency (Passive Refusal)
CALIBRATION-03-A
"Clinician instructions: Read the prompt, then start your silent count. Stop when I signal the response."
Prompt (Read aloud): "Alright class, eyes on me. Take out your blue folder and place it on the top left corner of your desk. Go."
[Teacher waits 14 seconds while student stares at ceiling]
Response (Signal): [Teacher mimes student reaching for folder]. "Stop timing now."
Master Target: 14.0 Seconds
Round 2: Duration (Crying Episode)
CALIBRATION-03-B
"Clinician instructions: Onset is the first audible sob. Offset is 5 seconds of continuous silence."
0s: [Loud sob begins]
22s: Student takes a breath, stops crying.
24s: [Sob resumes]
38s: Student stops crying, wipes eyes.
43s: [Timer ends here - Offset criteria met]
Master Target: 38.0 Seconds
Note: The duration ends at 38s, even though the observer waits until 43s to confirm the offset.
Reliability Discussion
Inter-Observer Agreement (IOA)
Ask students to compare their times with a partner. If they differ by more than 2 seconds, what caused the drift? Was it onset recognition or stopwatch reflex?
The "Fudge" Factor
Discuss the danger of rounding up (e.g., 38s to 40s). How does over-reporting duration by 5% daily impact the visual trend of the data over a month?
Interval Insights Slides Module 04 // Discontinuous Systems
Interval Insights
Understanding overestimation, underestimation, and the ethics of time-sampling.
Slicing the Data
Continuous (The Film)
Every instance is recorded. Frequency, duration, latency. High Accuracy, High Effort.
Discontinuous (The Photos)
Observations are 'sampled' in intervals. Partial, Whole, Momentary. High Efficiency, Potential Bias.
"We use discontinuous systems when we cannot dedicate 100% of our attention to the behavior, or when the behavior occurs at too high a rate to count."
Warning: Every choice introduces error.
The Interval Taxonomy
Partial Interval
Target: Behavior occurs at ANY point during the interval.
CLINICAL EFFECT:
Overestimates total duration; underestimates high-rate frequency.
Use for: Behaviors you want to DECREASE.
Whole Interval
Target: Behavior occurs during the ENTIRE interval.
CLINICAL EFFECT:
Underestimates total duration of the behavior.
Use for: Behaviors you want to INCREASE (e.g., On-task).
Momentary Sampling
Target: Behavior occurs at the EXACT moment the interval ends.
CLINICAL EFFECT:
Can over- or underestimate. Least biased for long durations.
Use for: Teachers/Clinicians with HIGH WORKLOADS.
Calculating Percentages
We report interval data as "Percentage of intervals in which behavior was recorded."
Int 1
Int 2
Int 3
Int 4
Int 5
3 / 5 Intervals = 60%
Procedural Integrity
"As a graduate student, you must not only pick the system but critique it. If a BIP says 10% behavior, but you used Whole Interval... is the behavior actually gone?"
Module 4 Practice
You will now analyze a single behavior stream using all three systems to see the bias in real-time.
Discontinuous Data Analysis Worksheet Discontinuous Data Analysis
Comparative Lab // Measurement Bias // Graduate Level
Student Name
Date
Part 1: The Behavior Stream
The following timeline represents 60 seconds of a student (Alex) exhibiting vocal stereotypical behavior (humming).
0s10s20s30s40s50s60s
Note: Shaded areas indicate behavior. Actual behavior duration: 24 seconds (40% of the session).
Part 2: 10-Second Interval Coding
Code the 60-second stream above into six 10-second intervals (Int 1-6) using all three systems.
System Int 1 Int 2 Int 3 Int 4 Int 5 Int 6 % Total Partial Interval Whole Interval Momentary Sampling
Part 3: Bias Critique & Validity
Compare your percentages to the actual duration (40%).
1. Mathematical Bias Identification:
Which system resulted in the largest overestimation? Explain why topography and interval length caused this.
2. Ethical & Reporting Responsibility:
You are writing an FBA for Alex. The behavior is harmless humming, but the teacher wants it gone. Which system should you avoid using if you want to provide the most balanced, least-biased view of Alex's behavior?
Graduate Competency Checklist:
• Can calculate percentage of intervals accurately.
• Can identify over- and underestimation tendencies.
• Selects appropriate measurement systems based on behavior function and goal.
Sampling Bias Answer Key Sampling Bias Answer Key
Teacher Resource // Discontinuous Data Analysis // Answer Key
Part 1: Comparison Matrix
| System | Int 1
Actual behavior duration was 24s (40%).
Part 2: Bias Analysis
Overestimation Analysis (Partial Interval)
Partial interval recorded 66.7%, a significant overestimation of the actual 40%. This occurs because short, bursty behaviors trigger the "any point" rule, counting a 3-second burst the same as a 10-second burst. This makes the student look "worse" than they are.
Underestimation Analysis (Whole Interval)
Whole interval recorded 0%! Since none of the humming episodes spanned the full 10 seconds of an interval, this system suggests the behavior didn't happen at all. This is a massive failure of validity for this specific behavior topography.
When to use which? (The "Ethics" Test)
Scenario: High-Risk Behavior
Use Partial Interval. It is better to "over-record" a dangerous behavior so you don't miss any instances and ensure high support.
Scenario: Skill Acquisition
Use Whole Interval. This ensures we only count progress when the student can maintain the skill for the entire period.
Visual Patterns Slides Module 05 // Pattern Analysis
Visual Patterns
Synthesizing scatterplot data to identify setting events and temporal clusters.
The Noise vs. The Signal
A behavior appears "random." It happens in math, it happens at lunch, it happens in the hallway.
The Question:
"Is the trigger a person, a place, or a hidden time-based variable?"
Scatterplots reveal temporal density . They tell us when behavior ISN'T happening as much as when it is.
Visual Analysis > Statistical Significance
Structure of the Matrix
Y
Vertical Axis: Time increments (e.g., 30-minute blocks).
X
Horizontal Axis: Days or dates of the week.
Cell Coding: Frequency markers (None, 1-3, 3+).
Temporal Cluster Detected (11:00 AM)
Triangulation: The Final Act
Indirect
Interviews (FAI)
Direct
ABC, Frequency, Temporal
Analysis
Scatterplots & Trends
"If all three points don't aim at the same function, your assessment is incomplete."
The Detective Project
You will be handed a folder of "Raw Data." Your job is to generate a scatterplot, identify the hidden pattern, and write the final functional hypothesis.
Pattern Detection
Clinical Synthesis
Scatterplot Detective Project Scatterplot Detective Project
Capstone Analysis // Data Triangulation // Graduate Level
Student Name
Date
Section 1: The Raw Data (Behavior: Physical Aggression)
Review the following log from a 3-day observation period.
Monday (Day 1)
08:35 - Hit peer
09:12 - Kicked wall
12:45 - Hit peer
13:10 - Hit teacher
Tuesday (Day 2)
08:42 - Kicked peer
09:05 - Hit teacher
11:20 - Kicked peer
13:05 - Hit peer
Wednesday (Day 3)
08:28 - Hit teacher
09:15 - Kicked wall
12:55 - Hit peer
13:15 - Kicked peer
Section 2: Scatterplot Mapping
Shade the cells where behavior occurred. Identify the "Clusters."
Time Block Mon Tue Wed Pattern Note 08:00 - 09:00 09:00 - 10:00 10:00 - 11:00 11:00 - 12:00 12:00 - 13:00 13:00 - 14:00
Section 3: Triangulation & Hypothesis
Stakeholder Interview Snippet (FAI):
"He's always worse right after lunch. I think he's just hyper from the sugar. Also, transitions to independent reading at 8:30 are a nightmare."
1. Visual Trend Analysis:
Based on your scatterplot, does the visual data support the teacher's "hyper from sugar" (post-lunch) claim? Explain.
2. Hidden Pattern Identification:
Identify a cluster the teacher *missed* or a time of day where behavior is notably *absent*. What environmental variable might be present then?
Final Functional Hypothesis:
Synthesis of Indirect + Direct + Visual Pattern.
Triangulation Final Guide Triangulation Final Guide
Teacher Resource // Capstone Project Key // Graduate Level
Part 1: Master Scatterplot Mapping
Time Block Mon Tue Wed Pattern Logic 08:00 - 09:00 X X X Cluster: Transition (Math) 09:00 - 10:00 X X X Residual aggression 10:00 - 11:00 Zero Rate (PE/Music) 11:00 - 12:00 X Random Instance 12:00 - 13:00 X X Post-Lunch Cluster 13:00 - 14:00 X X X Cluster: Academic Demand
Part 2: Triangulation Analysis
Teacher Claim Check
The teacher claimed behavior is "always worse right after lunch (12:00-13:00)."Verdict: Partially true. There is a cluster at 12:00, but the strongest clusters are 08:00 and 13:00 (Math and Science transitions).
Hidden Patterns
The 10:00-11:00 block shows a Zero-Rate. Students should identify that this corresponds to low-demand/high-interest periods (e.g., specials). This strengthens the "Escape" hypothesis.
Master Functional Hypothesis
"When presented with independent academic tasks (particularly Math and Science) or transitions from preferred activities (Lunch/Recess), the student engages in physical aggression (hitting/kicking) in order to escape or delay the task demand. This pattern is intensified during morning transitions."
Triangulated Point 1
FAI: Teacher reports 'Math' struggle
Triangulated Point 2
Direct: Topography is hit/kick
Triangulated Point 3
Scatterplot: Temporal demand clusters
Criteria High (3) Developing (2) Low (1) Pattern Recognition Identifies all 3 clusters. Identifies 1-2 clusters. Fails to identify trends. Triangulation Explicitly links FAI to Scatterplot. Mentions data sources separately.
