Evaluating Artificial Intelligence on the Efficacy of Preference Assessments for Preservice Speech-Language Pathologists
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View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence (AI) training significantly improved speech-language pathologists' (SLPs) ability to conduct preference assessments for individuals with intellectual and developmental disabilities (IDD). AI reduced errors and time, enhancing inclusion and skill development.
Area Of Science
- Applied Behavior Analysis
- Speech-Language Pathology
- Assistive Technology
Background
- Individuals with intellectual and developmental disabilities (IDD) experience significant barriers to inclusion, often linked to communication challenges.
- Speech-language pathologists (SLPs) are crucial in promoting skill development and inclusion for individuals with IDD.
- Preference assessments, like the multiple stimulus without replacement (MSWO), are vital for increasing skill acquisition and social interaction but can be hindered by training limitations.
Purpose Of The Study
- To compare the efficacy of artificial intelligence (AI) versus traditional pen-and-paper methods for self-instructional MSWO training among preservice SLPs.
- To evaluate the impact of AI training on implementation fidelity and assessment duration.
Main Methods
- Five preservice SLPs were trained using either AI-based or traditional MSWO assessment methods.
- Fidelity of implementation and duration of the assessment were systematically measured.
- A follow-up survey assessed treatment acceptability and perceived effectiveness.
Main Results
- AI training led to notable increases in implementation fidelity across participants.
- All participants showed reduced scoring errors when using AI.
- AI significantly reduced the duration of assessment implementation for most participants.
Conclusions
- AI-powered self-instructional training offers a more effective and efficient method for teaching MSWO preference assessments to SLPs.
- The use of AI in training enhances fidelity, reduces errors, and shortens assessment time, thereby improving treatment acceptability and outcomes for individuals with IDD.
- AI presents a promising tool for overcoming training barriers and promoting the meaningful inclusion of individuals with IDD.
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