The effect of career commitment on academic success among undergraduate baccalaureate nursing students
Bibliographic record
Abstract
Background: The ability of students, specifically in higher education environments, to persist is a critical determinant of academic success. Student success is especially precarious within programs of nursing, where curricula include clinical, laboratory, and didactic content. Identifying and describing the barriers and facilitators to nursing student persistence provides a blueprint to appropriately use financial and human resources as well as determine the effect student demographic variables has on desiring, attending, or benefiting from academic interventions.Methods: A descriptive study was used to examine the relationship between the independent variable of self-assessed career commitment, and the dependent variable of academic success among undergraduate nursing students enrolled in a required blended course.Results: Despite no statistical significance between career commitment and academic success, it should be noted that the failing population had a higher mean score of TTF (Tendency to Foreclose) M = 32.75 than the passing population M = 31.54, which may that those students who failed may tend to prematurely commit to nursing as a career choice without a true exploration of possible career choices. The VEC (Vocational Exploration Commitment) M = 41.59 was higher in the passing population than the failures with a M = 37.50, which may indicate those that passed had explored all career options before committing to nursing as a career choice.Conclusions: The outcome of this study can guide further research concerning career commitment and career exploration interventions since the process of career commitment is a task for all college students, including those who choose nursing as they identify how they will meet their career goals. Framed by Tinto’s Theory of Student Departure, this study assessed the effect of career commitment on academic success among undergraduate baccalaureate nursing students.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".