This review—which summarizes the state-of-the art in aviation error reporting, classification, and analysis—serves as the foundation for our future taxonomic research.
Find specific work or narrow your results by type, topic, program, project, or service by selecting your criteria from the choices at right.
In the sections below, we describe the results of a large-scale survey of pilots' perceptions of and experiences in their training. In particular, we focus on their responses to a series of questions concerning Crew Resource Management (CRM) training. This project was a unique opportunity to conduct a scientifically rigorous, large-scale comparison of CRM training programs across multiple airlines. Nevertheless, we recognize that participants' reactions to training are only one measure of a training program's effectiveness.
In this article we use a multifacet measurement technique, the multifacet Rasch model, to analyze the results of an IRR-training program. Our approach is an alternative to the procedures—congruency, consistency, agreement (rwg), sensitivity, and systematic differences—currently used during IRR training within the airline industry. We believe that this multifacet procedure can improve the quality of pilot instructor training by providing pilot instructors with important information that is not available with other techniques. We used the multifacet Rasch method instead of generalizability (G) theory, another multifacet technique. Similar to multifacet Rasch analysis, G-theory provides information about facets—pilot instructors, videotapes of aircrews used in IRR training, and LOS grade sheets—and their interactions with one another. However, G-theory partitions the variance attributable to each of these facets using an analysis of variance (ANOVA) framework and thus focuses on groups as the unit of analysis (i.e., whether or not pilot instructors as a group are reliable or unreliable as opposed to the performance of a particular instructor undergoing IRR training).