Difference between revisions of "TuccioNevile2017"

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|Author(s)=William Tuccio; Maurice Nevile;
 
|Author(s)=William Tuccio; Maurice Nevile;
 
|Title=Using Conversation Analysis in Data-Driven Aviation Training with Large-Scale Qualitative Datasets
 
|Title=Using Conversation Analysis in Data-Driven Aviation Training with Large-Scale Qualitative Datasets
|Tag(s)=EMCA; Aviation; CARM; flight instruction; interventions; applied; transcription; video; audio; Airline cockpit;  
+
|Tag(s)=EMCA; Aviation; CARM; flight instruction; interventions; applied; transcription; video; audio; Airline cockpit;
 
|Key=TuccioNevile2017
 
|Key=TuccioNevile2017
 
|Publisher=Embry-Riddle Aeronautical University/Hunt Library
 
|Publisher=Embry-Riddle Aeronautical University/Hunt Library
 
|Year=2017
 
|Year=2017
 +
|Language=English
 
|Journal=The Journal of Aviation/Aerospace Education and Research
 
|Journal=The Journal of Aviation/Aerospace Education and Research
|URL=https://doi.org/10.15394%2Fjaaer.2017.1706
+
|Volume=26
 +
|Number=1
 +
|URL=https://commons.erau.edu/jaaer/vol26/iss1/1/
 
|DOI=10.15394/jaaer.2017.1706
 
|DOI=10.15394/jaaer.2017.1706
 +
|Abstract=This paper contributes to a growing body of work related to the Conversation Analytic Role-play Method (CARM) by studying the primary flight instruction environment to create training interventions related to radio communications and flight instruction practices. Framed in the context of conversation analysis, an approach to the detailed analysis of naturally occurring interaction, the large-scale, long-duration qualitative audio/video data collection and coding methodology is discussed, followed by trends identified in the ongoing study. The concept of CARM “trainables” are discussed with examples. The study shows that large-scale qualitative datasets may be leveraged to produce valuable data-driven training interventions.
 
}}
 
}}

Latest revision as of 04:34, 7 July 2018

TuccioNevile2017
BibType ARTICLE
Key TuccioNevile2017
Author(s) William Tuccio, Maurice Nevile
Title Using Conversation Analysis in Data-Driven Aviation Training with Large-Scale Qualitative Datasets
Editor(s)
Tag(s) EMCA, Aviation, CARM, flight instruction, interventions, applied, transcription, video, audio, Airline cockpit
Publisher Embry-Riddle Aeronautical University/Hunt Library
Year 2017
Language English
City
Month
Journal The Journal of Aviation/Aerospace Education and Research
Volume 26
Number 1
Pages
URL Link
DOI 10.15394/jaaer.2017.1706
ISBN
Organization
Institution
School
Type
Edition
Series
Howpublished
Book title
Chapter

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Abstract

This paper contributes to a growing body of work related to the Conversation Analytic Role-play Method (CARM) by studying the primary flight instruction environment to create training interventions related to radio communications and flight instruction practices. Framed in the context of conversation analysis, an approach to the detailed analysis of naturally occurring interaction, the large-scale, long-duration qualitative audio/video data collection and coding methodology is discussed, followed by trends identified in the ongoing study. The concept of CARM “trainables” are discussed with examples. The study shows that large-scale qualitative datasets may be leveraged to produce valuable data-driven training interventions.

Notes