Testing the KRuger-dunning effect with coaches: Are incompetent coaches unaware of their incompetence?
Bibliographic record
Abstract
Kruger and Dunning (1999) found that individuals' perceived competence was related to objective assessments of their ability in a particular way. Specifically, the most incompetent individuals tend to show significantly inflated perceived competence. This pattern has been found in a variety of contexts, including industry, health and education (Dunning et al., 2004). The current study was designed to see if the effect would be present in coaching. Seventy-nine experienced high school coaches (50 male, 29 female) participated in the study. Perceived competence was assessed via the strategy and teaching technique factors of the Coaching Efficacy Scale (Feltz et al., 1999). Actual coaching ability was measured with a test of volleyball skills and strategy designed and validated for this study. As per Kruger and Dunning's protocol, coaches were placed into quartiles based on their answers on the coaching knowledge assessment tool. Within each quartile, a paired samples t-test was performed on the differences between efficacy and ability. Because the measures used different scales, z scores were used for analysis. Consistent with previous findings, coaches in the bottom quartile showed significantly higher efficacy than ability (t (13) = 4.93, p < .001). There were no differences between efficacy and ability in the second and third quartiles. However, coaches in the top quartile showed a significant difference (t (23) = -3.75, p <.001) whereby their efficacy was signifcantly lower than their ability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.118 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".