Developing Advanced Crew Resource Management (ACRM) Training: A Training Manual(108)

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common types of rater errors so that this information can be available and integrated into group
discussions:
Leniency and Severity: Raters who on a consistent basis are either inordinately lenient (“Santa Claus”) or inordinately severe (“Ax man”). Systematic differences analyses will tell you if raters are rating consistently lenient or harsh.
Central Tendency: Raters who avoid using high and low extremes and tend to cluster all of their ratings about the center of the rating scale. Low congruency indices may indicate the central tendency rating error.
Halo: Raters who assign ratings on the basis of a global impression of the ratee. An individual is rated either high or low on many factors because the rater knows that the individual is high or low on one specific factor. Low consistency indices may indicate halo rating error.
Contrast Effect: When raters evaluate more than one candidate at a time, they tend to use other candidates as a standard. Whom they rate favorably, then, is determined partly by others against whom the candidate is compared. (E.g. If a rater evaluates a candidate who is just average after evaluating three or four very unfavorable candidates in a row, the average candidate tends to be evaluated very favorably, instead of just average.) If two or more crews are taped for each event set, then contrast errors can occur. Extremely high sensitivity scores may indicate a contrast effect.
Congruency, Systematic Differences, Consistency, and Sensitivity Data (30-45 minutes)
1. The facilitator should begin with an overview of the discussion procedure. Then, a discussion about congruency, systematic differences, consistency, and sensitivity results should occur. Although these components can be discussed in any order, we recommend that your first discuss congruency, then systematic differences followed by consistency and sensitivity.
2. For the congruency, consistency, and sensitivity measures, the facilitator should begin with a 1-sentence definition of the measure, and then explain why it is important. This should be followed with examples of good and bad performance (use overheads to help get the point across). Next, the IEs should refer to their individual feedback packets to see how they compare to the average group index (using both 3 pt and 4 pt data). This should end with a discussion of the implications for IEs who are incongruent, inconsistent, or insensitive in their ratings.
3. For the systematic difference data, the facilitator should begin with a 1-sentence definition and then explain why it is important. The facilitator should then present the t-test graph (for both the 3 pt and 4 pt data) and point out the “Ax-Men” and the “Santa Clauses”. The IEs will have a copy of these graphs in their feedback packet. This should end with a discussion of the implications for IEs who are significantly high or low in their average ratings. Appropriate judgment standards and fairness to pilots can be discussed as focal points.
　
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