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Implementation of an automated grading tool for phonetic transcription training
Marisha Speights Atkins1, Dallin J Bailey2, Cheryl D Seals3
1Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, Illinois, USA.
Abstract:
Clinical phonetic transcription is regarded as a highly specialised skill requiring hours of practice for mastery. Although this skill is a critical part of students' clinical preparation to become speech-language pathologists, students often report feeling unprepared to apply the skill in clinical practice. Previous studies suggest that increased opportunities for practice and timely feedback on transcriptions are needed in order to develop skill confidence. However, providing more opportunities for practice can be impeded by the limited resources to manage the grading of additional assignments. The purpose of this study is to show the implementation of a web-based learning management system (LMS) designed in our labs for phonetics instruction. The Automated Phonetic Transcription Grading Tool (APTgt LMS) was developed to provide a platform for assignment delivery and automated grading of transcription assignments. The APTgt LMS has three embedded IPA keyboards (basic, advanced, and full IPA) and an automated edit distance algorithm modified by phonetic alignment principles, which allows for individualised scoring and visual course-level feedback in an interactive online environment. For pilot testing, student confidence was queried before and after practice opportunities using APTgt. A concurrent mixed methods research design was used to analyse four Likert scale and three open-ended questions. Student confidence in transcribing disordered speech was found to significantly increase (p <0.001) following additional practice. Students reported concerns related to accurate transcription of disordered speech and that additional practice is still needed. Tools like APTgt can aid in facilitating student learning and increasing student confidence in applied transcription.
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