Difference between revisions of "Muskett2017"
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| − | |BibType= | + | |BibType=INCOLLECTION |
|Author(s)=Tom Muskett | |Author(s)=Tom Muskett | ||
|Title=Using Conversation Analysis to Assess the Language and Communication of People on the Autism Spectrum: A Case-Based Tutorial | |Title=Using Conversation Analysis to Assess the Language and Communication of People on the Autism Spectrum: A Case-Based Tutorial | ||
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|Pages=117-140 | |Pages=117-140 | ||
|URL=https://link.springer.com/chapter/10.1057/978-1-137-59236-1_5 | |URL=https://link.springer.com/chapter/10.1057/978-1-137-59236-1_5 | ||
| − | |DOI= | + | |DOI=10.1057/978-1-137-59236-1_5 |
|Abstract=A powerful application of conversation analysis (CA) is to re-examine features of verbal communication diagnostically associated with autism spectrum disorder (ASD) (e.g., apparent problems with conversation, echolalia, idiosyncratic language). In this data-driven tutorial chapter, Muskett draws on his experiences as an academic psychologist and clinical speech and language therapist to lead the reader through the following questions. First, how do we undertake CA with ASD data, and with what methodological assumptions? Second, what are the broad theoretical implications of the kinds of findings that are generated when CA is used in this way? And finally, how might these findings be applied to underpin real-world practice across a range of clinical, educational, and social care contexts? | |Abstract=A powerful application of conversation analysis (CA) is to re-examine features of verbal communication diagnostically associated with autism spectrum disorder (ASD) (e.g., apparent problems with conversation, echolalia, idiosyncratic language). In this data-driven tutorial chapter, Muskett draws on his experiences as an academic psychologist and clinical speech and language therapist to lead the reader through the following questions. First, how do we undertake CA with ASD data, and with what methodological assumptions? Second, what are the broad theoretical implications of the kinds of findings that are generated when CA is used in this way? And finally, how might these findings be applied to underpin real-world practice across a range of clinical, educational, and social care contexts? | ||
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Revision as of 06:38, 6 July 2018
| Muskett2017 | |
|---|---|
| BibType | INCOLLECTION |
| Key | Muskett2017 |
| Author(s) | Tom Muskett |
| Title | Using Conversation Analysis to Assess the Language and Communication of People on the Autism Spectrum: A Case-Based Tutorial |
| Editor(s) | Michelle O'Reilly, Jessica Nina Lester, Tom Muskett |
| Tag(s) | EMCA, ASD |
| Publisher | |
| Year | 2017 |
| Language | English |
| City | |
| Month | |
| Journal | |
| Volume | |
| Number | |
| Pages | 117-140 |
| URL | Link |
| DOI | 10.1057/978-1-137-59236-1_5 |
| ISBN | |
| Organization | |
| Institution | |
| School | |
| Type | |
| Edition | |
| Series | |
| Howpublished | |
| Book title | A Practical Guide to Social Interaction Research in Autism Spectrum Disorders |
| Chapter | |
Abstract
A powerful application of conversation analysis (CA) is to re-examine features of verbal communication diagnostically associated with autism spectrum disorder (ASD) (e.g., apparent problems with conversation, echolalia, idiosyncratic language). In this data-driven tutorial chapter, Muskett draws on his experiences as an academic psychologist and clinical speech and language therapist to lead the reader through the following questions. First, how do we undertake CA with ASD data, and with what methodological assumptions? Second, what are the broad theoretical implications of the kinds of findings that are generated when CA is used in this way? And finally, how might these findings be applied to underpin real-world practice across a range of clinical, educational, and social care contexts?
Notes
