‘Where to start?’: Considerations for faculty and librarians in delivering information literacy instruction for graduate students.
Bibliographic record
Abstract
It is often assumed that incoming graduate students are information literate, yet many of them lack the skills needed to effectively organize and critically evaluate research. Supporting students in acquiring information literacy skills is a critical role for universities, as it improves the quality of student research and enhances their opportunities for lifelong learning. The literature in this area has focused on the partnership between librarians and course instructors, which has been shown to produce the most effective library instruction: however, additional research is needed concerning the collaborative approach to teaching information literacy to graduate students. The current study used action research to gather information on students’ perceptions of a blend of two methods of library instruction, a web-based tutorial and an in-class library instruction session. While few students indicated engagement with the online tutorial, most students appreciated the in-class session. Recommendations for information literacy instruction and further research are included.
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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 | 0.043 | 0.095 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".