Difference between revisions of "TuccioNevile2017"
SaulAlbert (talk | contribs) |
SaulAlbert (talk | contribs) |
||
| Line 3: | Line 3: | ||
|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 | ||
| Line 10: | Line 10: | ||
|URL=https://doi.org/10.15394%2Fjaaer.2017.1706 | |URL=https://doi.org/10.15394%2Fjaaer.2017.1706 | ||
|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. | ||
}} | }} | ||
Revision as of 15:33, 3 February 2017
| 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 | |
| City | |
| Month | |
| Journal | The Journal of Aviation/Aerospace Education and Research |
| Volume | |
| Number | |
| Pages | |
| URL | Link |
| DOI | 10.15394/jaaer.2017.1706 |
| ISBN | |
| Organization | |
| Institution | |
| School | |
| Type | |
| Edition | |
| Series | |
| Howpublished | |
| Book title | |
| Chapter | |
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
