The is the 3rd course in the QABA Pre-approved QBA series. This courses meets the required 30 hours of Data Collection and Analysis, 10 hours of Skill Acquisition Programming, and 5 hours of Antecedent Interventions.
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In this course, students learn about and are able to select appropriate experimental designs for the evaluation of interventions, select relevant measurement methods, display data for evaluation and determining effectiveness of interventions, explain the logic and benefits of single subject designs vs. group research design approaches, as well as identify the most appropriate experimental evaluation method for the situation, behavior and type of setting and intervention being applied. This course utilizes principles from behavior analysis to teach the course, including those borrowed from the Keller Method, online activities, frequent assessment and feedback in the form of “probes,” and adult education methods.
Course Outcomes:
Upon completion of the course, students will be able to:
- Identify and select appropriate experimental designs for the evaluation of interventions
- Identify and select relevant measurement methods, display data for evaluation and determining effectiveness of interventions
- Identify and explain the logic and benefits of single subject designs vs. group research design approaches
- Identify the most appropriate experimental evaluation method for the situation, behavior and type of setting and intervention being applied.
Topic Areas Include:
Data Collection and Analysis
- Define operational definition.
- Define reliability and validity.
- Identify 3 indicators of measurement.
- Define observable and measurable and the importance of defining an onset and offset of a behavior in reliability.
- Identify measurement procedures, such as frequency count/event recording, duration, time sampling, interval, partial interval recording, latency, and planned activity checks. Identify benefits and limitations to each.
- Define continuous and discontinuous methods of measurement.
- Identify and select types of graphs, such as line, bar, cumulative, scatterplots, and single subject design to display data.
- Identify and analyze types of data for trends, level, stability, and variability.
- Define inter-rater reliability and possible threats.
- Identify design types of inter-observer agreement (IOA)/Inter-rater reliability, such as trial by trial or total count.
- How to calculate IOA based on various data including unscored intervals, multiple observers, etc.
- Identify treatment drift in analysis of data.
