To what extent has doctoral (PhD) education supported academic nurse educators in their teaching roles: an integrative review
Bibliographic record
Abstract
BACKGROUND: A doctoral degree, either a PhD or equivalent, is the academic credential required for an academic nurse educator position in a university setting; however, the lack of formal teaching courses in doctoral programs contradict the belief that these graduates are proficient in teaching. As a result, many PhD prepared individuals are not ready to meet the demands of teaching. METHODS: An integrative literature review was undertaken. Four electronic databases were searched including the Cumulative Index to Nursing & Allied Health Literature (CINAHL), PubMed, Educational Resources Information Center (ERIC) and ProQuest. Date range and type of peer-reviewed literature was not specified. RESULTS: Conditions and factors that influenced or impacted on academic nurse educators' roles and continue to perpetuate insufficient pedagogical preparation include the requirement of a research focused PhD, lack of mentorship in doctoral programs and the influence of epistemic cultures (including institutional emphasis and reward system). Other factors that have impacted the academic nurse educator's role are society's demand for highly educated nurses that have increased the required credential, the assumption that all nurses are considered natural teachers, and a lack of consensus on the practice of the scholarship of teaching. CONCLUSIONS: Despite recommendations from nursing licensing bodies and a major US national nursing education study, little has been done to address the issue of formal pedagogical preparation in doctoral (PhD) nursing programs. There is an expectation of academic nurse educators to deliver quality nursing education yet, have very little or no formal pedagogical preparation for this role. While PhD programs remain research-intensive, the PhD degree remains a requirement for a role in which teaching is the major responsibility.
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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 | 0.012 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".