Date of Award
12-2019
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Behavioral Analysis
First Advisor
Christopher A. Podlesnik
Second Advisor
Corina Jimenez-Gomez
Third Advisor
Darby Proctor
Fourth Advisor
Lisa Steelman
Abstract
Conditional discrimination skill is foundational in teaching many other functional skills in children diagnosed with Autism Spectrum Disorder (ASD) and error occur during training. Antecedent- and consequence-based intervention are commonly used without the understanding of underlying behavioral mechanism responsible for these errors. A quantitative framework based on choice- and signal-detection analyses (Davison & Tustin, 1978) was used to quantify and categorize errors. Three children diagnosed with ASD participated. The current study used an automated 0-s delayed matching-to-sample (DMTS) procedure on an iPad Pro® 9.7”. Four experimental conditions were arranged successively, wherein each corresponded with a level of sample stimuli disparity: high, low, and zero, and high disparity. Results showed that changes in sample disparity reflected corresponding changes in discriminability (log d) and possibly modulated changes observed in stimulus bias (log b stimulus) and location bias (log b location). Further correlational analyses confirmed that accuracy (percent correct) was found to have strong and positive correlation with discriminability, but weak correlation with stimulus and location bias. Clinical practice and research implications were discussed.
Recommended Citation
Putri, Tiara Rahadian, "A Quantitative Analysis of Errors during Conditional Discriminations: Changing Sample-Stimuli Disparity in Delayed Matching-To-Sample Task with Children Diagnosed with Autism Spectrum Disorder" (2019). Theses and Dissertations. 152.
https://repository.fit.edu/etd/152
Comments
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