Contexts and constructs: Implications for the testing of listening in pilots’ communication with air traffic controllers
Bibliographic record
Abstract
The International Civil Aviation Organization (ICAO) published the Language Proficiency Requirements for pilots and air traffic controllers (ATCOs) in 2003. Research has shown that there is still a lack of clarity regarding what needs to be assessed in terms of the English used by pilots and ATCOs in radiotelephony (DOUGLAS, 2014; EMERY, 2014; KIM; BILLINGTON, 2016; KIM; ELDER, 2015; MONTEIRO, 2019; READ; KNOCH, 2009). The purpose of the present study was to investigate the nature of the listening tasks performed by pilots as an essential step in test development and validation. This explanatory sequential mixed-methods study (CRESWELL, 2015), elicited questionnaire responses from 156 pilots (Phase 1) and subsequently interviewed six aeronautical English experts (Phase 2) to better understand the characteristics of the listening tasks that pilots undertake during radiotelephony communications. Quantitative and qualitative data were analysed, and findings were merged. They provide information that may usefully inform the development of the listening test construct and the test specifications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.088 | 0.173 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".