Nursing students' and clinical educators' perceptions of characteristics of effective clinical educators in an Australian university school of nursing
Bibliographic record
Abstract
BACKGROUND: This study is a replication of research undertaken by Mogan and Knox in 1987, which investigated and described characteristics of 'best' and 'worst' clinical educators. They developed and used an instrument known as the Nursing Clinical Teacher Effectiveness Inventory (NCTEI), a 48 item checklist that describes discrete characteristics clustered into five subscales or categories: teaching ability; interpersonal relationships, personality traits, nursing competence and evaluation. The tool has since been used in several countries including Greece, Hong Kong, Israel and North America and is the instrument most frequently used to identify effective clinical teaching characteristics of clinical educators. AIM: The aim of the present study was to administer the NCTEI to undergraduate nursing students and clinical educators in a school of nursing at an Australian university to explore the perceived characteristics of effective clinical educators as rated by students and educators, and the significant differences and commonalities between these perceptions. FINDINGS: Results indicate that the category of Interpersonal Relationships was the most highly valued characteristic rated by both Australian students and clinical educators, and both groups (students and educators) ranked the subset of personality as the lowest amongst five categories. In common with Mogan and Knox, this study found that students who had not been exposed to real clinical situations prior to commencing nursing studies ranked items related to interpersonal relationships more highly than students who had previous nursing experience. Although there were no statistically significant differences in the two groups, students were more concerned with evaluation while clinical educators were more concerned with nursing competence. CONCLUSION: This study is the first research to be reported in Australia, which has simultaneously compared both students' and educators' perceptions and the first to replicate Mogan and Knox's seminal work. Findings point to the need for clinical educators to value interpersonal relationships with students as well as clinical competence.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".