What is the Best Way to Develop Information Literacy and Academic Skills of First Year Health Science Students? A Systematic Review
Bibliographic record
Abstract
Abstract Objective – This systematic review sought to identify evidence for best practice to support the development of information literacy and academic skills of first year undergraduate health science students. Methods – A range of electronic databases were searched and hand searches conducted. Initial results were screened using explicit inclusion and exclusion criteria to identify 53 relevant articles. Data on study design, student cohort, support strategy, and learning outcomes were extracted from each article. Quality of individual studies was considered and described narratively. Articles were classified and findings synthesized according to the mode of delivery of the intervention (Embedded, Integrated, or Adjunct) and classification of the study’s learning evaluation outcome (Organizational change, Behaviour, Learning, or Reaction). Results – Studies included in this review provide information on academic skills and information literacy support strategies offered to over 12,000 first year health science students. Courses targeted were varied but most commonly involved nursing, followed by psychology. Embedded strategies were adopted in 21 studies with Integrated and Adjunct strategies covered in 14 and 16 studies respectively. Across all modes of delivery, intervention formats included face-to-face, peer mentoring, online, and print based approaches, either solely or in combination. Most studies provided some outcomes at a level higher than student reaction to the intervention. Overall, irrespective of mode of delivery, positive learning outcomes were generally reported. Typically, findings of individual studies were confounded by the absence of suitable control groups, students self-selecting support and analysis of outcomes not accounting for these issues. As a result, there is very little unbiased, evaluative evidence for the best approach to supporting students. Nonetheless, our findings did identify poor student uptake of strategies when they are not interwoven into the curriculum, even when students were encouraged to attend on the basis that they had been identified at academic risk. Conclusions – The majority of studies included have reported positive learning outcomes following the implementation of academic skills and information literacy support strategies, irrespective of their mode of delivery (Embedded, Integrated, or Adjunct). Clear, rigorous evidence that embedded strategies offer superior learning outcomes compared to other delivery modes is lacking. However, because of poor student uptake of strategies offered outside curricula, embedded modes of academic and information literacy support are recommended for first year health science courses.
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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 | 0.016 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".