Scaffolding Information Literacy Learning for Undergraduate Nursing Students: A Mixed-Method Exploration of Student IL Self-Efficacy
Bibliographic record
Abstract
Purpose: Information literacy (IL) competency is an essential component of evidence-informed nursing practice. It is integral to introduce and develop core information literacy competencies for evidence-informed practice within undergraduate education programs. Research has shown undergraduate students may experience challenges with information literacy skills. More research to inform teaching methodologies that effectively enhance students’ skills and abilities, as well as their self-efficacy with these skills, is needed. This article describes an innovative teaching strategy, called journal club, which uses scaffolded learning activities in small groups over one semester. Methods: This mixed-methods research study used a non-experimental pre-post survey and was aimed at understanding the impact of the journal club strategy on students’ information literacy self-efficacy. The survey included the Information Literacy Self-Efficacy Scale (Kurbanoglu et al., 2006) and two open-ended questions in the post-survey. Results: A total of 37 participants, out of 42 potential participants, consented and responded to the pre-survey and 28 to the post-survey. Cohort-based descriptive statistics demonstrated a significant increase in overall scoring on the Information Literacy Self-Efficacy Scale from the pre-survey to the post-survey. Additionally, all relevant item measures from the tool showed statistically significant improvement. The open-ended questions were analyzed thematically, which resulted in the themes of recognition of personal growth, IL skill development, the opportunity to practise, time, the impact in the future, and relational engagement and benefits of the group. Conclusion: Overall, the findings of this study provide ample evidence that the journal club teaching strategy has positively enhanced students’ IL self-efficacy and will continue to be utilized in future offerings of the course. This strategy could be replicated in other contexts and content areas.
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".