The lived experience of transfer students in a collaborative baccalaureate nursing program
Bibliographic record
Abstract
Community college students who transfer to universities face innumerable challenges. These have been well documented in the American literature on transfer; however, there has been relatively little published research on transfer in Canada and a dearth of information about articulated professional programs with a collaborative curriculum. This study is intended to add to both the Canadian literature on transfer between community colleges and universities and the literature on inter-sectoral collaboration in professional education, more specifically in nursing education. The purpose of this study was to explore the lived experience of transfer students in a collaborative baccalaureate nursing program. Key elements comprising the foundation for the study are the literature on the development and evolution of college to university transfer in Canada and the United States, the organization and reform of nursing education, and the theoretical perspectives explaining persistence and transition in postsecondary education. Utilizing a naturalistic approach, both quantitative and qualitative data were gathered to elucidate the feelings, experiences and satisfaction of third year nursing students in a collaborative articulated program. Fifty-four students responded to a questionnaire and a subgroup of 13 students, selected through purposeful sampling, were interviewed. After an analysis and interpretation of the findings, several themes emerged. It was learned that transferring to university was not the smooth seamless transition expected by the students. For example, students experienced a professional transformation requiring a refraining of their nursing knowledge at university, a finding that is unique to this study. Also the process of transfer was found to cause significant stress. Even after adapting to the university geography, culture, and expectations, students in the closing month of their third year had not become fully incorporated into the mainstream of the university. However, in spite of all of the difficulties adjusting to the university, ultimately students were satisfied with their decision and the overall experience. In fact, they would recommend the program to a friend. On the basis of the findings and the students' suggestions, several general recommendations were made to provide a more seamless transition from college to university in collaborative articulated programs.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.014 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.006 |
| 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".