Evaluating the Impact of Information Literacy Workshops on Student Success
Bibliographic record
Abstract
Objective – This study was designed to identify the impact of standalone information literacy tutorials on student success indicators. The study was conducted in two different phases to compare findings across different modalities and to identify whether online, asynchronous delivery of substantively similar content affected outcomes. Methods – Using institutional records from a mid-sized, Midwestern public university, and attendance and completion data from student participation in asynchronous library workshops, the authors used propensity score matching to construct a control group that mirrored library workshop participants based on like characteristics. Statistical analyses were then conducted comparing the GPA, semester completion, and retention rates between the two groups. Results – Students who completed at least one information literacy workshop had significantly higher semester GPAs (M = 3.25, SD = 0.85, SE = 0.06) than non-participants (M = 2.99, SD = 1.13, SE = 0.07); significantly higher semester completion rates (M = 0.93, SD = 0.18, SE = 0.01) than non-participants (M = 0.87, SD = 0.27, SE = 0.02); and substantially higher odds (OR = 3.5) of returning to the university the following semester than non-participants. Conclusion – The findings in this study provide evidence for librarians advocating for the benefit of information literacy instruction on student success, particularly for undergraduate student retention. Additionally, library instruction programs making decisions about where to focus resources will find the comparisons between outcomes for online and traditional methods of instruction informative.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".