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Nina R. Benway; Jonathan L. Preston – Language, Speech, and Hearing Services in Schools, 2025
Purpose: Artificial intelligence (AI) is more capable and accessible than ever before. But what does this mean for clinical practice? How can speech-language clinicians evaluate the efficacy, validity, and reliability of AI and machine learning tools for automating assessment and treatment? How can speech-language clinicians ethically use these…
Descriptors: Speech Language Pathology, Allied Health Personnel, Speech Therapy, Artificial Intelligence
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Wendy R. Meyer; Maria D. Resendiz; Elizabeth D. Peña – Language, Speech, and Hearing Services in Schools, 2025
Purpose: The purpose of this study was twofold: (a) to gather evidence about the efficacy of performance feedback for improving school-based speech-language pathologist (SLP) narrative mediated learning implementation fidelity and (b) to determine SLPs' knowledge and attitudes about dynamic assessment (DA). Method: This investigation used a…
Descriptors: Feedback (Response), Allied Health Personnel, Intervention, Speech Language Pathology
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Karla N. Washington; Kathryn Crowe; Sharynne McLeod; Kate Margetson; Nicole B. M. Bazzocchi; Leslie E. Kokotek; Pauline van der Straten Waillet; Thora Másdóttir; Marc D. S. Volhardt – Language, Speech, and Hearing Services in Schools, 2025
Purpose: Identification of speech sound disorder (SSD) in children who are multilingual is challenging for many speech-language pathologists (SLPs). This may be due to a lack of clinical resources to accurately identify SSD in multilingual children as easily as for monolingual children. The purpose of this article is to describe features of…
Descriptors: Speech Evaluation, Speech Impairments, Accuracy, Clinical Diagnosis