Library Instruction and Academic Success: A Mixed-Methods Assessment of a Library Instruction Program
Bibliographic record
Abstract
Abstract Objectives – This study examines the connection between student academic success and information literacy instruction. Locally, it allowed librarians to ascertain the institution’s saturation rate for information literacy instruction and identify academic programs not utilizing library instruction services. In a broader application, it provides an argument for a tiered program of information literacy instruction and offers student perspectives on improving a library instruction program. Methods – Focus groups with 15 graduating seniors, all of whom had attended at least one library instruction session, discussed student experiences and preferences regarding library instruction. An analysis of 4,489 academic transcripts of graduating seniors identified differences in grade point average (GPA) between students with different levels of library instruction. Results – Students value library instruction for orientation purposes as beginning students, and specialized, discipline-specific library instruction in upper-level courses. There is a statistically significant difference in GPA between graduating seniors who had library instruction in upper-level courses (defined in this study as post-freshman-level) and those who did not. Conclusions – Library instruction seems to make the most difference to student success when it is repeated at different levels in the university curriculum, especially when it is offered in upper-level courses. Instruction librarians should differentiate between lower-division and upper-division learning objectives for students in order to create a more cohesive and non-repetitive information literacy curriculum.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".