Course
Discontinued
No
Course Code
DACS 5122
Descriptive
Applied Behaviour Analysis: Behavioural Techniques
Department
Disability & Community Studies
Faculty
Applied Community Studies
Credits
3.00
Start Date
End Term
201420
PLAR
No
Semester Length
Flexible delivery ranging over 2 to 15 weeks
Max Class Size
30
Contact Hours
60 hours: Lecture
Method(s) Of Instruction
Lecture
Learning Activities
- Lecture
- Case studies
- Videos
- Group presentation
Course Description
This upper level undergraduate course builds upon the science of applied behaviour analysis (ABA). Concepts include ABA definitions and characteristics, behavioural assessments, intervention outcomes and strategies, behaviour change procedures and systems support. All topics will be addressed within the context of current ethical standards.
Course Content
- Behavioural strategies will be grounded in evidence-based practices. This means the strategies need to be informed by:
- valid experimental designs for studying behaviours
- methods of applied observation that are subject to reliability and validity checks
- collection of data using various descriptive methods
- Dimensions of ABA and the Characteristics of Science:
- define and give examples of science, pseudo-science, anti-science, empiricism, parsimony, determinism, lawfulness of behaviour, experimentation, replication, philosophic doubt, and applied behaviour analysis
- describe respondent and operant behaviours and provide examples of private events
- identify environmental descriptions of behaviour from mentalistic explanations
- Evaluating Interventions and Literature:
- explain functional relations, dependent and independent variables and provide examples of each
- interpret peer-reviewed ABA journals using the lens of Baer, Wolf and Risley (1968)
- Functional Assessments and Functional Analysis:
- identify the characteristics of descriptive assessments
- differentiate between indirect and direct assessments
- identify the strengths and weaknesses of a descriptive assessment
- identify the characteristics of a functional (experimental) analysis
- identify the strengths and weaknesses of using a functional analysis
- Data Collection and Interpretation:
- write complete behavioural descriptions of target behaviours
- define behavioural cusp
- identify measurable dimensions of behaviour
- define social validity and identify its components
- identify between socially valid and socially invalid target behaviours
- Measurement of Behaviour:
- identify which behavioural dimension to measure based on the target behaviour
- define and give examples of frequency, rate, latency, duration, inter-response time (IRT), whole interval, partial interval, momentary time sampling, inter-observer agreement (IOA), data accuracy and reliability
- Reinforcement and Extinction:
- define and give examples of positive reinforcement, negative reinforcement and extinction
- differentiate between reinforcement and reinforcers and provide examples
- identify methods for identifying individualized reinforcers
- define schedules of reinforcement and provide appropriate uses of each including: variable and fixed ratio, variable and fixed interval, concurrent, multiple, chained, mixed, tandem and alternating
- identify side effects of reinforcement
- define and provide examples of the Premack Principle, behavioural momentum and the matching law
- define rule-governed behaviour and contrast it to contingency shaped behaviour
- Differential Reinforcement:
- define differential reinforcement of other (zero) behaviours (DRO), differential reinforcement of low rates of behaviour (DRL), differential reinforcement of alternative behaviour (DRA), differential reinforcement of incompatible behaviour (DRI), differential reinforcement of high rates of behaviour (DRH), differential negative reinforcement (DNR, DNRA, DNRI), and differential reinforcement of diminishing rates (DRD)
- choose appropriate differential reinforcement procedures based on the problem behaviour
- Shaping, Modeling and Chaining:
- define and give an example of shaping, modeling and chaining
- define and provide examples of forward, backwards and total task chaining
- compare single and multiple opportunity methods of chaining and identify uses for each
- identify factors that affect the performance of a behaviour chain
- discuss inappropriate behaviour chains and discuss methods for breaking them
- define and differentiate between modeling and imitation
- define “prompt” and identify the different types
- outline the methodology and importance of fading prompts quickly
- Punishment:
- define and give applied examples of positive punishment, negative punishment, time out, and over-correction
- identify key pros and cons of using punishment
- identify ethical considerations regarding the use of punishment
- define punisher and provide examples of a conditioned punisher and an unconditioned punisher
- define behavioural contrast and explain its implications to programming
- Token Economy:
- define token economy and identify the components necessary for a token economy
- determine steps for implementing and withdrawing a token economy
Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Demonstrate foundational concepts:
- Analyze data and summarize the importance of data-based measures to the field of ABA:
- Define reinforcement
- Define and employ various behavioural procedures:
- Define and provide applied examples of imitation
Means of Assessment
This course will conform to Douglas College policy regarding the number and weighting of evaluations. Typical means of evaluation would include a combination of:
- Weekly quizzes
- Mid term and final test
- Fluency tests
- Literature reviews
- Class presentation
Textbook Materials
Textbooks and Materials to be Purchased by Students:
Cooper, J. O., Heron, T. E., & Heward, W. L. (2007). Applied Behavior Analysis. 2nd Ed. Upper Saddle
River, NJ: Pearson/Prentice Hall.
Course pack of assigned journal readings or TBA
Prerequisites