Use of Library Services Can Be Associated with a Positive Effect on First-Year Students’ GPA and Retention
Bibliographic record
Abstract
A Review of:
 Soria, K. M., Fransen, J., & Nackerud, S. (2014). Stacks, serials, search engines, and students’ success: First-year undergraduate students’ library use, academic achievement, and retention. The Journal of Academic Librarianship, 40(1), 84-91.http://dx.doi.org/10.1016/j.acalib.2013.12.002
 
 Abstract
 
 Objective – To investigate the degree of relation between first-year undergraduate students’ library use and their academic achievement (measured by cumulative GPA) and first- to second-year retention. 
 
 Design – Quantitative data obtained from library systems combined with regression analyses.
 
 Setting – A large public university located in the United States of America.
 
 Subjects – The study included 5,368 non-transfer first-year students, with a total of 5,162 students retained for the final sample. 
 
 Methods – Data on 10 library usage variables were collected using student logins to library databases and websites and analyzed using SPSS. These variables included logins to databases, use of electronic books and journals, chat reference questions, and workshops signed up for, among others. There were 2 separate regressions utilized to predict students’ cumulative GPA by these 10 types of library use. Two separate logistic regressions were utilized to predict first- to second-year retention by the same library usage variables.
 
 Main Results – 81.9% of first-year students used at least one library service. Overall, students who used their academic library’s services and/or resources once or more during an academic year had a higher average retention rate and GPA compared to their peers who had not used the library. It was found that four library use areas, including book loans, database logins, electronic journal logins, and library workstation logins, were positively associated with students’ GPA. Database logins and library workstation logins were positively associated with retention. Each of the models used to predict either student GPA or retention by library use were found to be statistically significant.
 
 Conclusions – The study suggests that there is a positive and significant relationship between a number of library activities and students’ GPA and retention. The effect size of these activities upon the primary outcome variables of GPA and retention is small, though this is logical considering the one-time use of a library service is unlikely to meaningfully influence one’s academic success. Other non-library factors in the student experience must be considered.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.591 |
| 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".