Assessing the Library’s Influence on Freshman and Senior Level Outcomes with User Surveys
Bibliographic record
Abstract
Abstract
 
 Objectives – This study seeks to identify areas where relationships exist between a student’s library usage and student outcomes at Bellarmine University, a private master’s level institution. The study has two primary aims. The first is to see if an operationally oriented user survey can be used to provide evidence of the library’s support for institutionally important student outcomes. The second is to develop a regression model that provides a big picture with multiple variables to determine if library factors are still significant in student outcomes when controlling for significant demographic factors. 
 
 Methods – The library regularly conducts student user surveys, and this study examines the results of the first three surveys, from 2007, 2008 and 2010. These surveys include individually identifiable data on why students come to the library and how often they use it in person and online. Researchers aggregated student responses into class-based cohorts and used regression analysis to analyze the extent and significance of the relationships, if any, that exist between student use of the library and student outcomes such as retention, graduation and cumulative GPA. The study takes into consideration known significant student demographic factors such as American Collect Testing (ACT) composite score, full- or part-time status, and their session GPA. 
 
 Results – The study identifies specific library services and resources that have significant correlations with the selected student learning measures and outcomes. For freshman students, the ability to access the library online influences both retention and graduation. In looking at freshman learning outcomes represented by GPA, the results again indicate that the library has a positive influence on a student’s GPA. The library’s influence appears through two factors that highlight the library as a place: providing a place to study alone and as a place that has specialized equipment available to students. The library influences seniors’ cumulative GPA differently than for freshmen, primarily through the library’s role as an information resource. The variable check out books had a positive impact on senior’s GPA.
 
 Conclusions – This study indicates that the library does have an influence on student outcomes, whether learning outcomes, represented by cumulative GPA, or more typical student success outcomes, represented by second-year retention and graduation. This is true even when controlling for certain demographics, including the student’s ACT score, whether the student is part-time or full-time, and their session GPA. The factors that influence an individual student’s outcome change depending on the point in time in the undergraduate experience. These statistical analyses provide significant evidence for the value the library provides in support of institutionally important student outcome goals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.803 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".