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Behavior acquisition is a central focus of applied behavior analysis (ABA) and comprises 25% of the Registered Behavior Technician (RBT) examination.

This domain focuses on the methodologies and techniques used to teach new skills and behaviors to clients.

As a behavior technician, you will spend the majority of your time implementing these procedures under the supervision of a Board Certified Behavior Analyst (BCBA).

This comprehensive guide covers all 11 task areas (C.1 through C.11) within the Behavior Acquisition domain as outlined in the RBT Test Content Outline (3rd edition).

Each section provides detailed explanations, implementation guidelines, examples, and practice scenarios to help you master these essential skills.

Note: This study guide is extremely detailed, allowing you to learn everything about RBT Behavior Acquisition. You don’t need to look elsewhere; this is the ultimate guide for you, with nearly 7,000 words.

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C.1. Implement Positive and Negative Reinforcement Procedures

Reinforcement is any consequence that increases the likelihood that a behavior will occur again in the future. Understanding how to properly implement reinforcement procedures is essential for behavior change.

Positive Reinforcement

Positive reinforcement involves adding a stimulus following a behavior that increases the future frequency of that behavior. The “positive” refers to addition, not the pleasantness of the stimulus.

Key Implementation Components:

  1. Immediacy: Reinforcement must be delivered immediately after the target behavior occurs. Delays between behavior and reinforcement weaken the association. Aim to reinforce within 3-5 seconds of the behavior.
  2. Contingency: Reinforcement must be contingent on the target behavior occurring. The individual must understand that “if I do X, then Y happens.” Never provide the reinforcer if the target behavior didn’t occur, as this breaks the contingency.
  3. Schedules of Reinforcement:
    • Continuous Reinforcement (CRF): Reinforcing every instance of a behavior. Used during initial acquisition.
    • Intermittent Schedules:
      • Fixed Ratio (FR): Reinforcement after a set number of responses (FR3 = every 3rd response)
      • Variable Ratio (VR): Reinforcement after an average number of responses that varies (VR5 = average of 5 responses)
      • Fixed Interval (FI): Reinforcement for the first response after a fixed time period (FI2 = first response after 2 minutes)
      • Variable Interval (VI): Reinforcement for the first response after a variable time period (VI3 = average of 3 minutes)
  4. Dimensions of Reinforcers:
    • Magnitude: The amount or duration of reinforcement (larger reinforcers may have greater effects)
    • Quality: The value or preference for a reinforcer (higher quality is more effective)
    • Immediacy: How quickly reinforcement is delivered after behavior (faster is better)
    • Variety: Using different reinforcers to prevent satiation
    • Deprivation/Satiation: Effectiveness depends on motivating operations

Negative Reinforcement

Negative reinforcement involves removing an aversive stimulus following a behavior, which increases the future frequency of that behavior. The “negative” refers to removal, not punishment.

Key Implementation Components:

  1. Identify the aversive stimulus that can be removed (e.g., difficult task, loud noise, social demand)
  2. Remove the aversive stimulus immediately after the target behavior occurs
  3. Ensure contingency between the behavior and removal of the aversive stimulus
  4. Avoid inadvertently reinforcing problem behaviors through negative reinforcement

Implementation Best Practices

  1. Conduct preference assessments to identify effective reinforcers
  2. Vary reinforcers to prevent satiation
  3. Pair social praise with tangible reinforcers to build social reinforcement
  4. Thin reinforcement schedules gradually as behavior becomes established
  5. Ensure consistency across implementers
  6. Take data on both the target behavior and reinforcer effectiveness
  7. Consider pairing with prompts initially, then fade prompts while maintaining reinforcement

Common Errors to Avoid

  1. Delayed reinforcement delivery
  2. Non-contingent reinforcement (giving reinforcers when behavior didn’t occur)
  3. Not varying reinforcers, leading to satiation
  4. Using reinforcers that aren’t actually reinforcing for that individual
  5. Inadvertently reinforcing problem behaviors
  6. Not thinning reinforcement schedules over time

C.2. Implement Procedures to Establish and Use Conditioned Reinforcers

Conditioned reinforcers are previously neutral stimuli that have acquired reinforcing properties through pairing with other reinforcers. Unlike primary reinforcers (which are inherently reinforcing due to biological needs), conditioned reinforcers must be established through specific procedures.

Types of Conditioned Reinforcers

  1. Token Systems: Physical items (coins, stars, points) that can be exchanged for backup reinforcers
  2. Social Reinforcers: Praise, high-fives, thumbs-up, smiles
  3. Activity Reinforcers: Preferred activities that have been paired with reinforcement
  4. Generalized Conditioned Reinforcers: Items that can be exchanged for multiple backup reinforcers (money being the most common example)

Establishing Conditioned Reinforcers

  1. Stimulus-Stimulus Pairing:
    • Present the neutral stimulus (future conditioned reinforcer) immediately before the established reinforcer
    • Ensure temporal contiguity (close timing) between the neutral stimulus and established reinforcer
    • Repeat the pairing multiple times until the neutral stimulus acquires reinforcing properties
    • Example: Saying “Good job!” immediately before giving a preferred item
  2. Response-Stimulus Pairing:
    • Present the neutral stimulus immediately after a target behavior
    • Follow this with an established reinforcer
    • Continue until the neutral stimulus alone functions as a reinforcer
    • Example: Giving a token for completing work, then later exchanging tokens for preferred items

Implementation Steps for Establishing Conditioned Reinforcers

  1. Select an appropriate neutral stimulus to be conditioned (token, verbal praise, gesture)
  2. Identify effective primary or established reinforcers for the individual
  3. Pair the neutral stimulus with the established reinforcer consistently
  4. Test the effectiveness of the conditioned reinforcer by using it alone
  5. Maintain the value through occasional re-pairing with primary reinforcers
  6. Gradually thin the schedule of primary reinforcement while maintaining the conditioned reinforcer

Token Systems as Conditioned Reinforcers

  1. Select appropriate tokens (chips, stickers, points on a card)
  2. Establish clear earning rules (what behaviors earn tokens)
  3. Create a clear exchange system (token values, backup reinforcers)
  4. Teach the system to the client through modeling and practice
  5. Implement consistently across settings and implementers
  6. Adjust token values and backup reinforcers based on effectiveness
  7. Gradually increase response requirements for earning tokens

Maintaining Conditioned Reinforcers

  1. Periodic re-pairing with primary reinforcers to maintain effectiveness
  2. Varying backup reinforcers to prevent satiation
  3. Adjusting exchange ratios as skills improve
  4. Ensuring immediate delivery of tokens after target behaviors
  5. Consistent implementation of the token system across settings

Common Errors to Avoid

  1. Not pairing the conditioned reinforcer with established reinforcers enough times
  2. Inconsistent pairing that weakens the conditioning
  3. Delayed delivery of tokens after behavior
  4. Complex token systems that are difficult to understand
  5. Inconsistent implementation across settings or implementers
  6. Not providing enough variety in backup reinforcers
  7. Not maintaining the value through occasional re-pairing

C.3. Implement Discrete-Trial Teaching Procedures

Discrete-Trial Teaching (DTT) is a structured teaching methodology that breaks skills into small, manageable components and teaches them in a systematic way. Each trial consists of a clear beginning and end, with specific components that must be implemented precisely.

Components of a Discrete Trial

  1. Antecedent (SD or discriminative stimulus): The instruction, question, or environmental cue that signals the availability of reinforcement for a specific response
    • Must be clear, concise, and consistent
    • Delivered only when the learner is attending
    • Examples: “Touch blue,” “What is this?” while showing a picture
  2. Prompt (if necessary): Additional help provided to increase the likelihood of a correct response
    • Various types: physical, verbal, gestural, visual, positional
    • Implemented according to a specific prompting procedure (e.g., most-to-least, least-to-most)
    • Faded systematically as learner gains proficiency
  3. Response: The behavior exhibited by the learner following the antecedent
    • Correct response, incorrect response, or no response
    • Must be clearly defined in observable terms
  4. Consequence: What happens immediately after the learner’s response
    • For correct responses: reinforcement (praise, tangible item, token)
    • For incorrect responses: correction procedure, error correction, or neutral response
    • Delivered immediately after the response
  5. Inter-trial interval (ITI): Brief pause (1-5 seconds) between trials
    • Allows clear separation between consecutive trials
    • Provides time to record data and prepare for next trial

DTT Implementation Steps

  1. Prepare the environment:
    • Minimize distractions
    • Arrange materials in advance
    • Position yourself and the learner appropriately (typically facing each other)
    • Have data collection system ready
  2. Secure attention:
    • Ensure the learner is attending before delivering the SD
    • Use an attention cue if needed (“Look at me”)
    • Wait for eye contact or other indicators of readiness
  3. Present the antecedent:
    • Deliver the SD clearly and consistently
    • Use the exact wording specified in the program
    • Present any materials in a standardized way
  4. Implement prompting strategy (if needed):
    • Follow the prompting hierarchy specified in the program
    • Deliver prompts immediately after the SD or after a brief wait time
    • Ensure prompts are effective but minimally intrusive
  5. Wait for response:
    • Allow sufficient response time (typically 3-5 seconds)
    • Observe carefully for the target response
  6. Provide consequence:
    • For correct responses: deliver reinforcement immediately
    • For incorrect responses: implement error correction procedure
    • Maintain a neutral facial expression during error correction
  7. Record data:
    • Document response (correct, prompted, incorrect)
    • Note prompt level if applicable
    • Record any other relevant information
  8. Pause for inter-trial interval:
    • Brief 1-5 second pause before next trial
    • Reset materials if needed
  9. Begin next trial

Error Correction Procedures in DTT

  1. Interruption procedure: Stop incorrect response immediately and prompt correct response
  2. Return to stimulus: Re-present the SD with increased prompt level
  3. Modeling and practice: Demonstrate correct response and have learner practice
  4. Error-free learning: Use high levels of prompting to prevent errors, then systematically fade prompts

Mass Trials vs. Varied/Mixed Trials

  1. Mass trials: Repeating the same target multiple times in succession
    • Useful for initial acquisition of new skills
    • Example: “Point to dog” presented 10 times in a row
  2. Varied/mixed trials: Alternating between multiple targets
    • Promotes discrimination and maintenance
    • Example: Alternating between “Point to dog,” “Point to cat,” “Point to horse”

Tips for Effective DTT Implementation

  1. Pace trials appropriately – typically 8-12 trials per minute for fluent skills
  2. Keep sessions brief (10-20 minutes) to maintain attention
  3. Intersperse mastered tasks with acquisition targets to maintain motivation
  4. Vary reinforcers to prevent satiation
  5. Take data on every trial for decision-making
  6. Maintain a neutral tone during error correction
  7. Stay alert to signs of fatigue or frustration
  8. End sessions on successful trials when possible

C.4. Implement Naturalistic Teaching Procedures

Naturalistic teaching approaches leverage natural environments and activities to teach functional skills. Unlike the structured setting of DTT, naturalistic teaching embeds learning opportunities within everyday routines and follows the learner’s interests and motivation.

Key Naturalistic Teaching Approaches

  1. Incidental Teaching:
    • Arranges the environment to spark interest
    • Waits for the learner to initiate
    • Requires a response before providing access
    • Provides natural reinforcement
  2. Natural Environment Training (NET):
    • Teaching occurs in natural contexts where skills are typically used
    • Uses natural reinforcers directly related to the behavior
    • Follows the learner’s motivation and interests
    • Embeds multiple learning opportunities throughout daily routines
  3. Pivotal Response Training (PRT):
    • Focuses on “pivotal” areas that affect multiple behaviors
    • Core areas include motivation, responding to multiple cues, self-management, and self-initiation
    • Uses child choice, task variation, and natural reinforcers
    • Reinforces attempts, not just perfect responses
  4. Enhanced Milieu Teaching (EMT):
    • Combines environmental arrangement, responsive interaction, and specific teaching procedures
    • Uses modeling, mand-model, and time delay techniques
    • Follows child’s lead while creating communication opportunities
    • Expands on child’s communication attempts

Implementation Steps for Naturalistic Teaching

  1. Environmental Arrangement:
    • Place desired items in sight but out of reach
    • Create situations that require assistance
    • Sabotage routines to create communication opportunities
    • Offer choices between preferred items
    • Set up incomplete activities
  2. Following the Learner’s Lead:
    • Observe what interests the learner
    • Join in their chosen activities
    • Comment on what they’re doing without demands
    • Wait expectantly for initiations
  3. Creating Teaching Opportunities:
    • Wait for learner to initiate interest (reaching, looking, approaching)
    • Respond promptly to initiations
    • Create a brief, naturalistic expectation for a response
    • Use the least intrusive prompt necessary
    • Provide immediate access to the desired item/activity following response
  4. Using Natural Reinforcers:
    • Ensure reinforcement is directly related to the response
    • Example: If child says “ball,” give them the ball (not a cookie)
    • Pair social praise with natural reinforcers
    • Make reinforcement contingent on a communicative response
  5. Expanding Skills:
    • Once basic responses are established, require slightly more advanced responses
    • Shape responses toward increasingly complex language or behavior
    • Use time delay to encourage spontaneous responses
    • Expand on learner’s utterances by adding words

Specific Naturalistic Teaching Techniques

  1. Mand-Model Procedure:
    • When learner shows interest, ask a question (“What do you want?”)
    • If no response, model the correct response (“Say ‘ball'”)
    • Provide reinforcement when learner responds
  2. Time Delay:
    • Establish eye contact and show the desired item
    • Wait expectantly (3-5 seconds) before prompting
    • Gradually increase wait time to promote spontaneous communication
  3. Interrupted Chain Procedure:
    • Begin a familiar routine or activity
    • Pause at a critical point, creating an opportunity for communication
    • Wait for learner to request continuation
    • Example: Start pushing child on swing, then stop and wait for “more”
  4. Expectant Waiting:
    • Create a situation where reinforcement is obvious but not given
    • Use an expectant look and body language
    • Wait silently for learner to initiate

Collecting Data During Naturalistic Teaching

  1. Probe data: Periodically test specific skills in structured opportunities
  2. Frequency data: Count instances of target behaviors during sessions
  3. Duration data: Track how long learner engages appropriately
  4. ABC data: Document antecedents, behaviors, and consequences
  5. Opportunity-based data: Record responses to specific arranged opportunities

Comparing DTT and Naturalistic Teaching

AspectDiscrete Trial TeachingNaturalistic Teaching
SettingStructured, controlledNatural environments
InitiationTeacher-directedOften learner-initiated
MaterialsPre-selected by teacherBased on learner interest
ReinforcementOften contrivedNatural and functional
TrialsClearly delineatedEmbedded in activities
GeneralizationRequires specific programmingMore naturally occurring

C.5. Implement Task Analyzed Chaining Procedures

Task analysis is the process of breaking complex skills into smaller, teachable steps. Chaining involves teaching these steps in sequence to establish the complete behavior chain. Properly implementing chaining procedures is essential for teaching multi-step skills like daily living activities, vocational tasks, and complex social routines.

Creating a Task Analysis

  1. Identify the target skill to be taught
  2. Define the starting point and ending point clearly
  3. Perform the task yourself or observe someone performing it
  4. Break the task into small, teachable steps (typically 5-15 steps)
  5. Write steps in clear, observable terms using action verbs
  6. Ensure steps are sequentially ordered and logical
  7. Test the task analysis by having someone follow it exactly
  8. Revise as needed based on learner performance

Types of Chaining Procedures

  1. Forward Chaining:
    • Teach the first step in the sequence until mastered
    • Provide full prompting for remaining steps
    • Once first step is independent, teach the second step
    • Continue adding steps sequentially until entire chain is mastered
    • Example: Teaching hand washing by first teaching turning on water, then getting soap, etc.
  2. Backward Chaining:
    • Complete all steps except the final step for the learner
    • Teach the last step in the sequence until mastered
    • Once last step is independent, teach the second-to-last step
    • Continue adding steps in reverse sequence until entire chain is mastered
    • Example: Teaching shoe tying by helping with all steps except the final pull to tighten
  3. Total Task Presentation (Whole Task Chaining):
    • Teach all steps in the sequence during each teaching opportunity
    • Provide appropriate prompting level for each step
    • Fade prompts across all steps simultaneously
    • Example: Teaching toothbrushing by prompting through all steps every session

Implementation Steps for Chaining Procedures

  1. Select the appropriate chaining strategy based on:
    • Learner characteristics and previous experience
    • Complexity of the task
    • Natural reinforcers within the chain
    • Danger or safety concerns in early steps
  2. Determine prompting strategy:
    • Most-to-least prompting
    • Least-to-most prompting
    • Graduated guidance
    • Time delay
  3. Prepare the environment:
    • Gather all necessary materials
    • Minimize distractions
    • Arrange materials in logical sequence
    • Position yourself to provide prompts effectively
  4. Begin teaching sequence:
    • For forward chaining: Start with first step
    • For backward chaining: Complete all but last step, then teach last step
    • For total task: Teach all steps in sequence
  5. Use appropriate prompts for targeted steps:
    • Physical guidance
    • Modeling
    • Gestural prompts
    • Verbal instructions
  6. Fade prompts systematically:
    • Reduce prompt intensity gradually
    • Increase delay before providing prompts
    • Move from physical to less intrusive prompts
  7. Provide reinforcement:
    • Initially reinforce completion of targeted step(s)
    • Eventually reinforce completion of entire chain
    • Use natural reinforcers when possible (e.g., eating food after preparing it)
  8. Collect data on each step:
    • Record prompt levels needed
    • Track independent performance
    • Note problem steps that require additional teaching

Data Collection for Chaining

  1. Step-by-step analysis:
    • Record performance on each step (independent, prompted, incorrect)
    • Note prompt level required for each step
    • Calculate percentage of steps performed independently
  2. Mastery criteria examples:
    • Independent performance of all steps across 3 consecutive sessions
    • 90% of steps performed independently across 5 sessions
    • Independent performance across 3 different settings or with 3 different instructors

Choosing the Right Chaining Procedure

  1. Forward Chaining is best when:
    • Task has a natural progression
    • Initial steps are easier or safer
    • Early steps are prerequisite for later steps
    • Natural reinforcement occurs throughout the chain
  2. Backward Chaining is best when:
    • Natural reinforcement occurs at end of chain
    • Final outcome serves as motivator
    • Final steps are easier to learn
    • Learner has difficulty with initiation
  3. Total Task is best when:
    • Chain is relatively short
    • Learner has some existing skills in the sequence
    • Natural sequence is important for learning
    • Frequent practice of all steps is beneficial

Common Challenges and Solutions

  1. Task too complex:
    • Break steps into smaller sub-steps
    • Provide additional practice on difficult steps
  2. Prompt dependency:
    • Use systematic prompt-fading procedures
    • Incorporate time delay before prompting
  3. Motivation issues:
    • Identify more effective reinforcers
    • Use high-preference activities following completion
  4. Inconsistent performance:
    • Ensure consistent cues and materials
    • Practice across different settings and instructors

C.6. Implement Discrimination Training

Discrimination training teaches individuals to respond differently to different stimuli. The fundamental goal is to establish stimulus control, where behavior occurs in the presence of specific antecedent stimuli but not in the presence of others.

Key Concepts in Discrimination Training

  1. Stimulus control: When a behavior occurs more frequently in the presence of a specific stimulus (SD) than in its absence (S-delta)
  2. Discriminative stimulus (SD): Signal that reinforcement is available for a specific response
  3. S-delta (SΔ): Signal that reinforcement is not available for a specific response
  4. Generalization: Responding similarly to stimuli that share properties with the trained SD
  5. Discrimination: Responding differently to different stimuli based on their properties

Types of Discriminations

  1. Simple discrimination: Responding to one stimulus but not to others
    • Example: Saying “dog” when shown a picture of a dog, but not when shown other animals
  2. Conditional discrimination: Responding based on relationship between stimuli
    • Example: In matching tasks, selecting the comparison stimulus that matches the sample
  3. Feature discrimination: Responding based on specific features of stimuli
    • Example: Sorting objects by color regardless of shape
  4. Compound discrimination: Responding based on combination of stimulus features
    • Example: Responding only to red squares but not red circles or blue squares

Implementation Steps for Discrimination Training

  1. Assessment and target selection:
    • Identify stimuli that need to be discriminated
    • Assess current discrimination abilities
    • Select appropriate targets based on prerequisite skills
    • Begin with easily discriminable stimuli (highly different)
  2. Establish response to SD:
    • Teach response to target SD in isolation
    • Use effective prompting and reinforcement
    • Ensure consistent responding before introducing S-delta
  3. Introduce S-delta:
    • Present SD and S-delta in separate trials initially
    • Reinforce responses to SD
    • Do not reinforce responses to S-delta
    • Use errorless learning procedures to minimize errors
  4. Mix SD and S-delta trials:
    • Present SD and S-delta in random sequence
    • Maintain higher ratio of SD trials initially (e.g., 80% SD, 20% S-delta)
    • Gradually equalize frequency of SD and S-delta presentations
    • Collect data on responses to both stimulus types
  5. Increase difficulty gradually:
    • Introduce more similar stimuli as discrimination improves
    • Decrease prompts systematically
    • Add additional exemplars of each stimulus class
    • Vary irrelevant features while maintaining relevant ones
  6. Program for generalization:
    • Train with multiple examples of each stimulus class
    • Vary irrelevant stimulus dimensions
    • Train across settings, materials, and instructors

Specific Discrimination Training Procedures

  1. Discrete Trial Discrimination Training:
    • Present SD or S-delta in structured trials
    • Provide clear consequences for correct/incorrect responses
    • Intersperse SD and S-delta trials systematically
    • Track accuracy for each stimulus type
  2. Errorless Discrimination Training:
    • Initially make stimuli very different
    • Gradually make them more similar as discrimination improves
    • Use prompt fading to ensure high success rate
    • Prevent errors through careful stimulus selection and presentation
  3. Matching-to-Sample:
    • Present sample stimulus
    • Present comparison stimuli (including target and non-targets)
    • Reinforce selection of comparison that matches sample
    • Can be identity matching (identical stimuli) or arbitrary matching (related but not identical)
  4. Oddity Discrimination:
    • Present array of stimuli where one differs
    • Reinforce selection of the different stimulus
    • Gradually increase similarity between target and non-targets

Data Collection for Discrimination Training

  1. Trial-by-trial data:
    • Record responses to each SD and S-delta presentation
    • Calculate percentage of correct responses for each stimulus type
    • Track prompt levels if applicable
  2. Discrimination index:
    • Compare rate of responding to SD vs. S-delta
    • Calculate ratio of correct responses to SDs divided by total responses
  3. Error analysis:
    • Document patterns of errors
    • Identify specific stimuli causing confusion
    • Note whether errors are false positives (responding to S-delta) or false negatives (not responding to SD)

Common Challenges and Solutions

  1. Overselectivity:
    • Problem: Attending to only one feature of multi-feature stimuli
    • Solution: Highlight relevant features initially, then fade prompts
  2. Stimulus generalization:
    • Problem: Overgeneralizing response to similar stimuli
    • Solution: Train with minimal differences, then gradually introduce more similar exemplars
  3. Weak stimulus control:
    • Problem: Inconsistent responding to SD
    • Solution: Increase reinforcement density, use more preferred reinforcers
  4. Prompt dependency:
    • Problem: Reliance on prompts to make discriminations
    • Solution: Use systematic prompt-fading procedures, incorporate time delay

C.7. Implement Procedures Using Stimulus and Response Prompts with Appropriate Fading

Prompts are supplementary antecedent stimuli that increase the likelihood of correct responding. Prompt fading refers to the systematic removal of these additional stimuli to transfer stimulus control to the natural SD. Effective implementation requires understanding various prompt types and fading procedures.

Types of Prompts

  1. Stimulus Prompts (modify the antecedent stimulus):
    • Visual prompts: Highlighting, arrows, visual cues added to materials
    • Textual prompts: Written words or instructions
    • Positional prompts: Placing correct option closer to learner
    • Enhanced prompts: Making target stimulus more noticeable (larger, brighter)
  2. Response Prompts (provide additional help to produce the response):
    • Physical prompts: Hand-over-hand guidance, partial physical assistance
    • Gestural prompts: Pointing, nodding, or other movements
    • Verbal prompts: Instructions, hints, or direct verbal cues
    • Model prompts: Demonstrating the correct response
    • Verbal prompts: Full verbal model, partial verbal model, phonemic cue

Prompt Hierarchies

  1. Most-to-Least Prompting (MTL):
    • Begin with most intrusive prompt level that ensures correct responding
    • Systematically fade to less intrusive prompts
    • Example hierarchy: Physical → Model → Gestural → Verbal → Independent
    • Advantages: Fewer errors, more successful trials, less frustration
    • Disadvantages: May create prompt dependency, less opportunity for independent responding
  2. Least-to-Most Prompting (LTM):
    • Begin with opportunity for independent response
    • Add increasingly intrusive prompts until success
    • Example hierarchy: Independent → Verbal → Gestural → Model → Physical
    • Advantages: Promotes independence, identifies minimal prompt needed
    • Disadvantages: More errors possible, may be frustrating initially
  3. Graduated Guidance:
    • Continuous physical contact with intensity adjusted moment-to-moment
    • Prompt level varies within trial based on learner’s performance
    • Shadow the learner’s movements, providing support as needed
    • Advantages: Fluid support, responsive to moment-by-moment performance
    • Disadvantages: Requires skilled implementation, difficult to measure consistently

Prompt Fading Procedures

  1. Errorless Learning:
    • Present prompt immediately before or with SD to prevent errors
    • Gradually delay or reduce prompt intensity
    • Ensures high success rate during acquisition
    • Used often with most-to-least prompting
  2. Time Delay:
    • Progressive time delay:
      • Initially provide prompt immediately (0-second delay)
      • Gradually increase delay before prompt (1s → 2s → 3s → 4s → 5s)
      • Reinforcement for correct responses before prompt
    • Constant time delay:
      • Initial trials with 0-second delay
      • Then shift to consistent delay interval (e.g., 4 seconds) for all trials
      • Simpler to implement than progressive delay
  3. Stimulus Fading:
    • Gradually change stimulus prompt dimensions:
      • Size (large → small)
      • Intensity (bright → dim)
      • Position (central → peripheral)
    • Example: Gradually fading highlighted text until only normal text remains
  4. Stimulus Shaping:
    • Gradually transform prompting stimulus into target stimulus
    • Example: Morphing picture prompt into text-only card
  5. Within-Stimulus Prompting:
    • Build prompts into the target stimulus itself
    • Gradually remove or fade these built-in prompts
    • Example: Highlighting key features of letters then fading the highlighting

Implementation Steps for Prompt and Prompt Fading Procedures

  1. Assess and select appropriate prompting strategy:
    • Consider learner’s previous experience with prompts
    • Analyze task complexity and current skill level
    • Determine if errors would be detrimental to learning
  2. Define prompt hierarchy clearly:
    • Specify exact prompts to be used
    • Define criteria for moving between prompt levels
    • Document specific language or actions for each prompt level
  3. Establish consistent implementation:
    • Train all implementers on exact prompting procedure
    • Create operational definitions for each prompt level
    • Practice prompt delivery and fading techniques
  4. Implement prompt fading systematically:
    • Define criteria for reducing prompt level (e.g., 3 consecutive correct responses)
    • Move to next prompt level based on data, not time
    • Return to more intrusive prompts if errors occur
  5. Collect detailed data:
    • Record prompt level required for each trial
    • Document successful independent responses
    • Track pattern of prompt fading over sessions
  6. Avoid common errors:
    • Fading prompts too quickly
    • Inconsistent prompt delivery across implementers
    • Inadvertently adding unplanned prompts
    • Not waiting for attention before prompting

Data Collection for Prompting Procedures

  1. Trial-by-trial data:
    • Record prompt level for each trial
    • Note independent correct responses
    • Calculate percentage of trials at each prompt level
  2. Types of prompt level recording:
    • First prompt that led to correct response
    • Most intrusive prompt used during trial
    • All prompts used during trial
  3. Visual representation:
    • Graph showing decreasing prompt levels over time
    • Increasing percentage of independent responses

Transfer of Stimulus Control

The ultimate goal of prompting and fading is to transfer stimulus control from the prompt to the natural SD. This occurs when:

  1. The learner responds correctly to the SD without prompts
  2. The learner maintains responding over time without prompts
  3. The SD alone (not the prompts) evokes the target behavior
  4. The behavior generalizes to different examples of the same SD

C.8. Implement Generalization Procedures

Generalization occurs when a behavior taught in one setting, with specific stimuli, or with certain people transfers to novel settings, stimuli, or people without direct teaching. Implementing effective generalization procedures ensures that learned skills are functional in the natural environment.

Types of Generalization

  1. Stimulus Generalization:
    • Response occurs with similar but untrained stimuli
    • Example: Saying “dog” to different breeds of dogs after learning with one breed
  2. Response Generalization:
    • Similar but untrained responses occur to the same stimulus
    • Example: Using different greetings after learning to say “hello”
  3. Setting Generalization:
    • Behavior occurs in different environments than training setting
    • Example: Using requesting skills at home and at school
  4. Temporal Generalization:
    • Behavior maintains over time after training ends
    • Example: Continuing to use social skills months after intervention
  5. People Generalization:
    • Behavior occurs with different people than original trainers
    • Example: Following instructions from various adults, not just teachers

Strategies for Programming Generalization

  1. Train Sufficient Exemplars:
    • Teach using multiple examples of stimuli
    • Vary irrelevant features while maintaining relevant ones
    • Example: Teaching “cup” using plastic cups, ceramic mugs, travel tumblers
  2. Train Loosely:
    • Introduce planned variations in teaching procedures
    • Vary instructions, materials, setting arrangements
    • Avoid rigid teaching patterns that create inadvertent stimulus control
    • Example: Teaching hand-washing using different sinks, soaps, and towels
  3. Use Indiscriminable Contingencies:
    • Vary reinforcement schedules unpredictably
    • Intermix reinforced and non-reinforced trials
    • Prevents discrimination of “training mode” vs. “real life”
    • Example: Occasionally reinforcing social interactions in natural settings
  4. Program Common Stimuli:
    • Include elements from generalization setting in training setting
    • Use materials, language, and cues that match natural environment
    • Example: Using actual grocery items when teaching shopping skills
  5. Mediate Generalization:
    • Teach rules or problem-solving strategies rather than just specific responses
    • Train self-management techniques that can apply across situations
    • Example: Teaching “if-then” rules for social situations
  6. Train to Generalize:
    • Explicitly reinforce generalized responding
    • Provide direct instruction on when and how to use skills in new situations
    • Example: Reinforcing use of communication skills in novel contexts

Implementation Steps for Generalization Procedures

  1. Plan for generalization from the beginning:
    • Identify target generalization settings, people, and stimuli
    • Incorporate generalization strategies into initial teaching plan
    • Set specific generalization objectives and criteria
  2. Assess baseline across generalization dimensions:
    • Conduct probes in different settings before training
    • Test with untrained stimuli and people
    • Document pre-intervention performance across contexts
  3. Implement teaching with built-in variation:
    • Use multiple examples of training materials
    • Vary your teaching presentation style
    • Change aspects of the environment during teaching
  4. Conduct regular generalization probes:
    • Test periodically in non-training settings
    • Assess with novel stimuli not used in teaching
    • Have different people conduct assessment sessions
  5. Use sequential modification if needed:
    • If generalization doesn’t occur naturally, teach directly in the generalization setting
    • Provide additional training with problem stimuli or in difficult settings
    • Implement booster sessions targeting specific generalization gaps
  6. Fade artificial teaching contingencies:
    • Gradually make teaching environment more natural
    • Thin reinforcement schedules to match natural contingencies
    • Replace contrived reinforcers with natural ones

Data Collection for Generalization

  1. Generalization probes:
    • Conduct periodic tests in non-training conditions
    • Assess performance without additional prompting or instruction
    • Compare to baseline measures in same conditions
  2. Train and hope testing:
    • Train in one setting/condition
    • Test in novel settings/conditions without additional teaching
    • Document where generalization occurs naturally
  3. Multiple baseline across settings/people:
    • Begin intervention in one setting while monitoring others
    • Sequentially introduce intervention across settings
    • Evaluate if skills transfer before direct instruction

Common Challenges in Generalization

  1. Restricted stimulus control:
    • Problem: Behavior only occurs with exact training stimuli
    • Solution: Use varied materials and examples during teaching
  2. Prompt dependency:
    • Problem: Behavior only occurs with familiar instructors or prompts
    • Solution: Systematically vary instructors and fade prompts across people
  3. Failure to maintain:
    • Problem: Skills decay when reinforcement is reduced
    • Solution: Thin reinforcement gradually, program for intermittent natural reinforcement
  4. Over-generalization:
    • Problem: Behavior occurs in inappropriate contexts
    • Solution: Teach discrimination of when behavior is appropriate and when it isn’t
  5. Environmental barriers:
    • Problem: Natural environment doesn’t support generalization
    • Solution: Train caregivers, modify environment, or create supports in generalization settings

C.9. Distinguish Between Maintenance and Acquisition Procedures

Understanding the difference between acquisition and maintenance procedures is crucial for efficient and effective teaching. These two phases of learning require different instructional approaches, reinforcement schedules, and data collection methods.

Acquisition Phase Characteristics

  1. Definition: The period when a learner is initially developing a new skill or behavior.
  2. Key features during acquisition:
    • Higher levels of prompting required
    • More frequent and immediate reinforcement
    • More structured teaching environment
    • Generally lower fluency and accuracy
    • More direct teaching trials
    • New skills not yet reliably performed independently
  3. Indicators that a behavior is in acquisition phase:
    • Performance below mastery criteria
    • Inconsistent responding
    • Requires prompts for successful completion
    • Higher error rates
    • Limited generalization across settings/people
  4. Appropriate procedures for acquisition:
    • Continuous reinforcement schedules (reinforcing every correct response)
    • Systematic prompting procedures (most-to-least, least-to-most)
    • Errorless learning techniques to minimize mistakes
    • High density of teaching trials
    • Controlled teaching environment with minimal distractions
    • Frequent data collection (often trial-by-trial)

Maintenance Phase Characteristics

  1. Definition: The period after a skill has been acquired when the focus shifts to ensuring the behavior continues over time without direct teaching.
  2. Key features during maintenance:
    • Reduced or eliminated prompting
    • Thinned reinforcement schedules
    • More natural contingencies
    • Higher fluency and accuracy
    • Less structured practice opportunities
    • Skills performed independently across conditions
  3. Indicators that a behavior is in maintenance phase:
    • Performance consistently meets or exceeds mastery criteria
    • Independent responding without prompts
    • Low error rate
    • Generalization beginning to occur
    • Skill performed fluently and consistently
  4. Appropriate procedures for maintenance:
    • Intermittent reinforcement schedules (FR, VR, FI, VI)
    • Natural and intrinsic reinforcers rather than contrived ones
    • Embedded practice opportunities throughout daily routines
    • Self-management and self-monitoring techniques
    • Periodic probes rather than continuous data collection
    • Diverse practice contexts and materials

Transitioning from Acquisition to Maintenance

  1. Determining when to transition:
    • Establish clear mastery criteria (e.g., 80% correct across 3 consecutive sessions)
    • Consider both accuracy and fluency measures
    • Ensure independent performance without prompts
    • Look for initial generalization across at least some conditions
    • Verify skill stability over several sessions
  2. Procedural changes during transition:
    • Gradually thin reinforcement schedule
    • Systematically remove prompts
    • Increase delay between behavior and reinforcement
    • Introduce more variable practice conditions
    • Shift from contrived to natural reinforcers
    • Move from massed practice to distributed practice
  3. Data-based decision making:
    • Monitor performance during transition period
    • Be prepared to return to acquisition procedures if performance deteriorates
    • Use periodic probes to assess maintenance
    • Track performance across varied conditions

Maintenance Strategies

  1. Reinforcement schedule thinning:
    • Gradually increase response requirement (FR1 → FR2 → FR5 → FR10)
    • Introduce variable ratios (VR schedules)
    • Mix schedules to create resistance to extinction
    • Fade to naturally occurring reinforcement
  2. Distributed practice:
    • Space practice opportunities across time rather than massed practice
    • Brief, frequent practice sessions rather than long, infrequent ones
    • Incorporate skills into daily routines
  3. Mixed and varied practice:
    • Intersperse maintained skills with skills in acquisition
    • Practice in varied settings and with different materials
    • Combine skills into functional routines
  4. Self-management techniques:
    • Teach self-monitoring of performance
    • Implement self-reinforcement procedures
    • Develop self-prompting strategies
    • Fade external management to internal management
  5. Behavioral momentum:
    • Intersperse easy, well-maintained tasks with more challenging ones
    • Create high-probability request sequences
    • Build in success to maintain motivation

Common Errors in Distinguishing Phases

  1. Premature transition to maintenance:
    • Moving to maintenance procedures before skill is truly mastered
    • Result: Performance deterioration requiring return to acquisition
  2. Prolonged acquisition phase:
    • Continuing intensive teaching after mastery has been achieved
    • Result: Inefficient use of teaching time and potential prompt dependency
  3. Abrupt rather than gradual transitions:
    • Suddenly changing reinforcement from continuous to thin schedules
    • Result: Extinction-like effects and decreased motivation
  4. Neglecting maintenance programming:
    • Failing to plan for maintenance after acquisition
    • Result: Skill regression and need for re-teaching
  5. Insufficient monitoring during maintenance:
    • Assuming skills will maintain without periodic assessment
    • Result: Undetected loss of skills over time

C.10. Implement Shaping Procedures

Shaping is a behavior-change procedure that involves reinforcing successive approximations of a target behavior until the final desired behavior is achieved. This technique is particularly useful when the target behavior is complex or when the learner does not currently display any instances of the behavior.

Key Concepts in Shaping

  1. Successive approximations: Behaviors that increasingly resemble the target behavior in topography, duration, intensity, or other dimensions
  2. Terminal behavior: The final desired behavior that is the ultimate goal of the shaping process
  3. Reinforcement criteria: The specific response requirements that must be met to earn reinforcement at each step
  4. Differential reinforcement: Reinforcing behaviors that meet current criteria while withholding reinforcement for previously accepted approximations

Implementation Steps for Shaping

  1. Define the terminal behavior:
    • Specify exactly what the final behavior should look like
    • Describe in observable and measurable terms
    • Identify all relevant dimensions (topography, duration, intensity, frequency)
    • Example: “Independently writing complete sentences with correct capitalization and punctuation”
  2. Assess current level of performance:
    • Determine what approximations of the behavior already exist
    • Identify starting point based on current abilities
    • Example: If teaching writing, assess if learner can hold pencil, make marks, form letters, etc.
  3. Create a shaping plan:
    • Break down the path from current to target behavior into small, achievable steps
    • Arrange steps in logical sequence of increasing difficulty
    • Define specific criteria for reinforcement at each step
    • Example sequence for teaching writing:
      • Making marks on paper
      • Drawing lines
      • Tracing letters
      • Copying letters
      • Writing letters independently
      • Writing words
      • Writing sentences
  4. Begin reinforcement at attainable level:
    • Start with approximations the learner can already perform
    • Use continuous reinforcement initially
    • Provide immediate feedback and reinforcement
    • Example: Reinforce any mark made on paper initially
  5. Shift criteria gradually:
    • Once current level is consistent, raise criteria slightly
    • Change only one dimension at a time (e.g., duration OR accuracy, not both)
    • Make increments small enough to ensure success
    • Example: After reinforcing any mark on paper, only reinforce marks within lines
  6. Use differential reinforcement:
    • Reinforce behaviors meeting new criteria
    • Withhold reinforcement for previously accepted approximations
    • Provide stronger reinforcement for closer approximations
    • Example: Once learner can trace letters, no longer reinforce just making marks
  7. Monitor progress and adjust plan:
    • Track performance at each step
    • Be prepared to adjust criteria if progress stalls
    • Return to previous step if necessary
    • Continue until terminal behavior is established

Behavioral Dimensions That Can Be Shaped

  1. Topography: The physical form or appearance of the behavior
    • Example: Shaping hand movements for sign language from gross approximations to precise signs
  2. Duration: How long the behavior lasts
    • Example: Shaping on-task behavior from 30 seconds to 30 minutes
  3. Intensity: The force or strength of the behavior
    • Example: Shaping appropriate voice volume from too loud to conversational level
  4. Frequency: How often the behavior occurs
    • Example: Shaping hand-raising from never to consistently when appropriate
  5. Latency: Time between stimulus and response
    • Example: Shaping response time from delayed to immediate compliance
  6. Accuracy: How closely the behavior matches the target
    • Example: Shaping pronunciation from approximations to correct articulation

Examples of Shaping Sequences

  1. Shaping vocal language:
    • Any vocalization → Specific sounds → Word approximations → Clear words → Phrases → Sentences
  2. Shaping toilet training:
    • Sitting on toilet fully clothed → Sitting without clothes → Eliminating in toilet with prompt → Independent elimination → Self-initiation
  3. Shaping social interaction:
    • Proximity to peers → Looking at peers → Responding to peer initiations → Brief interactions → Sustained interactions → Initiating interactions
  4. Shaping independent work:
    • Working with constant prompting → Working with intermittent prompts → Working with adult proximity → Working with periodic check-ins → Fully independent work

Data Collection for Shaping

  1. Frequency of approximations:
    • Count instances of behaviors at current target level
    • Track instances of behaviors at previous and future levels
  2. Dimensional measurement:
    • Measure specific dimensions being shaped (duration, intensity, etc.)
    • Graph progress along the targeted dimension
  3. Step achievement:
    • Document when criteria for each step are met
    • Record dates for changes in reinforcement criteria
  4. Visual representation:
    • Graph showing progression through shaping steps
    • Include criteria changes and performance at each step

Common Challenges and Solutions

  1. Plateauing:
    • Problem: Progress stops at particular step
    • Solution: Break step into smaller increments or temporarily lower criteria
  2. Resurgence of previous approximations:
    • Problem: Return to earlier approximations when criteria increase
    • Solution: Use differential reinforcement more systematically, consider higher magnitude reinforcement for new target
  3. Inconsistent performance:
    • Problem: Meeting criteria some times but not others
    • Solution: Ensure stable performance at current level before advancing
  4. Moving too quickly through steps:
    • Problem: Raising criteria before stability at current level
    • Solution: Establish clear performance criteria before advancing (e.g., 3 consecutive sessions at 90% accuracy)
  5. Moving too slowly through steps:
    • Problem: Keeping criteria constant despite ready capability for more
    • Solution: Use probes to test readiness for next level, be responsive to learner progress

C.11. Implement Token Economies

Token economies are structured reinforcement systems in which tokens are earned for target behaviors and later exchanged for backup reinforcers. This system allows for delayed reinforcement while maintaining motivation through the immediate earning of tokens.

Components of a Token Economy

  1. Tokens:
    • Physical items (chips, stickers, points, stamps)
    • Digital representations (points on an app, stars on a chart)
    • Characteristics: Durable, portable, easy to deliver, resistant to counterfeiting, safe
  2. Target behaviors:
    • Clearly defined behaviors that earn tokens
    • Can include skill acquisition targets and behavior reduction goals
    • Should be observable and measurable
  3. Token earning rules:
    • Schedule for earning tokens (how many behaviors per token)
    • Criteria for earning tokens (quality/duration requirements)
    • When and how tokens are delivered
  4. Backup reinforcers:
    • Items, activities, or privileges that can be purchased with tokens
    • Range of options with different token costs
    • Should be genuinely reinforcing to the individual
  5. Exchange system:
    • Rules for when exchanges can occur
    • Token values for different reinforcers
    • Process for conducting exchanges

Implementation Steps for Token Economies

  1. Assessment and planning:
    • Conduct preference assessment to identify effective backup reinforcers
    • Select appropriate token type based on learner’s age and abilities
    • Determine which behaviors will earn tokens
    • Establish initial token values and exchange schedule
  2. Design materials:
    • Create token board, chart, or digital tracking system
    • Develop visual menu of backup reinforcers with token costs
    • Prepare data collection system
    • Gather necessary tokens and storage
  3. Teach the system:
    • Explicitly teach how tokens are earned
    • Demonstrate exchange process
    • Practice with guided examples
    • Check understanding through questions and role-play
  4. Initial implementation:
    • Start with rich reinforcement schedule (easy to earn tokens)
    • Frequent exchange opportunities initially
    • Immediate token delivery following target behaviors
    • Consistent implementation across all settings/implementers
  5. Systematic adjustments:
    • Gradually increase response requirements for tokens
    • Extend time between exchange opportunities
    • Increase token costs for highly preferred reinforcers
    • Add new target behaviors as initial ones become established
  6. Data collection and evaluation:
    • Track tokens earned across behaviors and settings
    • Monitor frequency of target behaviors
    • Record reinforcer selections during exchanges
    • Evaluate overall effectiveness of the system

Types of Token Economies

  1. Individual token systems:
    • Designed for a single learner
    • Customized to individual preferences and needs
    • Tokens and reinforcers specific to that learner
  2. Group token systems:
    • Implemented with multiple learners
    • May have individual or shared token goals
    • Can incorporate cooperative earning opportunities
  3. Level systems:
    • Include multiple tiers with increasing privileges
    • Advancement based on consistent performance
    • Higher levels typically require more independence and self-management
  4. Response cost components:
    • Include both earning and losing tokens
    • Specify behaviors that result in token loss
    • Require careful implementation to maintain motivation

Schedules in Token Economies

  1. Token earning schedules:
    • Continuous reinforcement: Every instance of behavior earns token(s)
    • Fixed ratio: Token earned after set number of responses
    • Variable ratio: Token earned after variable number of responses
    • Time-based: Tokens earned for behavior during/throughout time intervals
  2. Exchange schedules:
    • Fixed time: Exchanges available at set times only
    • Delayed exchange: Accumulate tokens for later exchange
    • Immediate exchange: Trade tokens as soon as minimum is earned
    • Combined schedules: Different reinforcers available on different schedules

Fading and Transitioning Token Economies

  1. Gradual thinning procedures:
    • Increase response requirements for earning tokens
    • Extend duration between exchange opportunities
    • Increase token costs for reinforcers
    • Reduce magnitude or quality of backup reinforcers
  2. Transition to natural contingencies:
    • Pair tokens with social reinforcement consistently
    • Introduce naturally occurring reinforcers
    • Gradually shift to more naturally occurring schedules
    • Implement self-monitoring components
  3. Self-management transition:
    • Teach self-recording of target behaviors
    • Involve learner in token delivery
    • Incorporate self-evaluation components
    • Shift to self-administered token systems

Common Challenges and Solutions

  1. Token satiation:
    • Problem: Tokens lose value over time
    • Solution: Rotate backup reinforcers, vary token types, use token economy intermittently
  2. Backup reinforcer satiation:
    • Problem: Backup reinforcers lose effectiveness
    • Solution: Rotate reinforcer options, conduct frequent preference assessments, allow saving for higher-value items
  3. Inconsistent implementation:
    • Problem: Different implementers apply rules differently
    • Solution: Written protocols, staff training, visual reminders of procedures
  4. Counterfeiting/stealing:
    • Problem: Unauthorized token acquisition
    • Solution: Use unique tokens, close supervision of token storage, digital systems
  5. Focus on tokens rather than behavior change:
    • Problem: Emphasis shifts from target behaviors to token accumulation
    • Solution: Pair social reinforcement with tokens, emphasize progress on target behaviors

Token Economy Variations and Enhancements

  1. Response cost components:
    • Include both earning and losing tokens
    • Clearly define behaviors that result in token loss
    • Always ensure opportunities to earn exceed opportunities to lose
  2. Token banking systems:
    • Allow saving tokens for higher-value reinforcers
    • Teach delay of gratification and planning
    • Incorporate “interest” for saved tokens to encourage saving
  3. Token contracts:
    • Formalize token earning and exchange rules in written agreement
    • Involve learner in establishing contract terms
    • Review and update contracts periodically
  4. Interdependent group contingencies:
    • Group earns tokens based on collective performance
    • Promotes cooperation and peer support
    • Can be combined with individual token systems

Ethical Considerations in Token Economies

  1. Access to necessities:
    • Basic needs and rights should never be contingent on tokens
    • Food, water, bathroom access, and safety cannot be token-contingent
  2. Least restrictive intervention:
    • Consider whether less intrusive interventions could be effective
    • Plan for systematic fading from the beginning
  3. Individualization:
    • Tailor token systems to individual needs and preferences
    • Ensure reinforcers are actually reinforcing for the specific learner
  4. Dignity and age-appropriateness:
    • Design systems that are respectful and age-appropriate
    • Consider how the system appears to others in inclusive settings
  5. Consistent implementation:
    • Token systems must be implemented as designed to be ethical and effective
    • Follow through with promised reinforcement

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