The Effectiveness of Library Instruction for Graduate/Professional Students: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Objective - This study sought to assess the effectiveness of library instruction for increasing information literacy skills and/or knowledge among graduate and professional students. Methods - A search was conducted in Library Literature and Information Science Index (H. W. Wilson); Library, Information Science & Technology Abstracts; Medline; CINAHL; ERIC; Library and Information Science Abstracts (LISA); and ProQuest Dissertations and Theses Global. Studies were included if they were published between 2000 and 2019, in English, reported on library instruction for graduate or professional students, and objectively measured change in information literacy knowledge/skills. Results - Sixteen studies were included in the systematic review; 12 of the 16 studies included sufficient information to be included in the meta-analysis. The overall effect of library instruction was significant [SMD = 1.03, SE=0.19, z=5.49, P<.0001, 95% CI=0.66-1.40], meaning that on average, a student scored about one standard deviation higher on an information literacy assessment after library instruction. High heterogeneity indicated a need for subgroup analysis, which showed a significant moderation of effect by discipline of students, but none by format of instruction. However, subgroup analysis must be viewed with caution due to the small number of studies in several of the subgroups. Conclusions - This meta-analysis indicates that library instruction for graduate students is effective in increasing information literacy knowledge and/or skills. However, to strengthen the accuracy of results of future meta-analyses, there is a need for more precise descriptions of instructional sessions as well as more complete data reporting by authors of primary studies. There is also a need for the publication of more studies, particularly studies of hybrid and online instruction.
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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 | 0.019 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.031 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".