Health Professions Students’ Lifelong Learning Orientation: Associations with Information Skills and Self Efficacy
Bibliographic record
Abstract
Objective – This study aimed to investigate the relationships among health professions students’ lifelong learning orientation, self-assessed information skills, and information self-efficacy. Methods – This was a descriptive study with a cross-sectional research design. Participants included 850 nursing students and 325 medical students. A total of 419 students responded to a survey questionnaire that was comprised of 3 parts: demographic information, the Jefferson Scale of Lifelong Learning (JeffSLL-HPS), and an information self-efficacy scale. Results – Findings of the study show a significant correlation between students’ lifelong learning orientation and information self-efficacy. Average JeffSLL-HPS total scores for undergraduate nursing students (M = 41.84) were significantly lower than the scores for graduate nursing students (M = 46.20). Average information self-efficacy total scores were significantly lower for undergraduate nursing students (M = 63.34) than the scores for graduate nursing students (M = 65.97). There were no significant differences among cohorts of medical students for JeffSLL-HPS total scores. However, for information self-efficacy, first year medical students (M = 55.62) and second year medical students (M = 58.00) had significantly lower scores than third/fourth year students (M = 64.42). Conclusion – Findings from the study suggest implications for librarians seeking ways to advance the value and utility of information literacy instruction in educational curricula. As such instruction has the potential to lead to high levels of information self-efficacy associated with lifelong learning; various strategies could be developed and incorporated into the instruction to cultivate students’ information self-efficacy.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".