Experiences of Baccalaureate Prepared Nurses on Their Transition to Novice Faculty Members
Bibliographic record
Abstract
The shortage of qualified nursing faculty in Canada threatens the ability to educate sufficient numbers of nurses to meet healthcare demands. Despite this, limited research explores how baccalaureate-prepared nurses experience the transition into nursing faculty roles. The purpose of this qualitative study, guided by Schoening’s nurse educator transition model, was to explore the experiences of baccalaureate prepared nurses on the transition to novice nurse faculty members teaching in 2-year diploma prepared nursing programs in Northwestern Ontario. Five semi-structured interviews were conducted with baccalaureate-prepared novice nursing faculty members, analyzed, and transcribed using Zoom. Data were coded and analyzed using Saldana’s first and second cycle coding methods. Four major themes emerged: (a) anticipation of structured support and preparedness, (b) lack of orientation and institutional support, (c) the emotional weight of role unpreparedness, and (d) lack of accessible, comprehensive, and timely teaching resources. Participants entered their roles with expectations of structured support and resources, but instead encountered a lack of orientation, insufficient mentorship, and limited managerial guidance. These challenges contributed to role stress, identity conflict, and significant emotional strain, often leaving participants overwhelmed, discouraged, and questioning their preparedness for academic responsibilities. Findings highlight the need for formal mentorship, comprehensive orientation programs, and timely access to teaching resources to enhance role satisfaction and retention. Implications for positive social change include improving faculty retention, strengthening the quality of nursing education, and supporting a sustainable nursing workforce.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".