Quality of Student Paper Sources Improves after Individual Consultation with Librarians
Bibliographic record
Abstract
Objective – To determine whether the quality of sources used for a research paper will improve after a student receives one-on-one instruction with a librarian. To test citation analysis and a rating scale as means for measuring effectiveness of one-on-one consultations. Design – Citation analysis. Setting – Academic library of a large American university. Subjects – Papers from 10 courses were evaluated. In total, 76 students were asked to meet with librarians. Of these, 61 actually participated. Another 36 students from the control group were not asked to meet with a librarian (although 1 partook in a consultation). Methods – Librarians invited faculty to participate in a new service to help improve quality of student research papers. Eligible courses included those with a required research paper component where papers could be evaluated at different times in the project. Faculty instructed students in the class to meet with the librarian after a first draft of a paper was written. Students from seven courses were asked to meet with a librarian. Courses included English Composition (2), Geography (1), Child Development (1), Occupational Therapy (1), Marketing (1) and Women Writers (1). Three courses acted as control groups (all English Composition). After meeting with students to make recommendations, librarians used a rating scale (measuring relevancy, authority, appropriate dates and scope) to review the quality of sources in both drafts and final papers. Main Results – One-on-one consultations with a librarian resulted in sources being of a higher quality in the final paper. With the exception of authority, the differences between draft and final paper were statistically significant in all measures (overall quality, relevance, dates and scope). Those in the control group showed no improvement in quality of sources between draft and final paper. Conclusion – Quality of sources in final paper improves after one-on-one consultations with librarians. The use of a rating scale is helpful in objectively measuring quality of sources, although there is potential for subjective interpretation.
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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 | 0.061 | 0.348 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".