Individualized Research Consultations in Academic Libraries: A Scoping Review of Practice and Evaluation Methods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract
 
 Introduction – Librarians in academic institutions have been providing personalized services to the student population by offering individualized research consultations (IRC) for decades. These consultations usually consume many hours of librarians’ busy schedules, and yet the impact of these consultations is unknown. Therefore, it’s worth asking the question: what assessment methods have been used in academic libraries to evaluate the impact of IRC?
 
 Methods – A retrospective scoping review of the literature was performed using the following databases: Library and Information Science Abstracts (LISA), Educational Resources Information Center (ERIC), Library and Information Technology Abstracts (LISTA), Scopus, and Web of Science. Additionally, a manual search of the included papers reference lists was conducted to locate additional relevant papers. Articles that mentioned a format of evaluation or assessment and were based within a library setting were included. Articles that discussed group instruction that were not in a library setting, or that did not include any form of evaluation or assessment, were excluded.
 
 Results – Researchers located 578 articles and reviewed titles and abstracts. 523 titles were eliminated, while full text sources of the remaining 55 were examined to check inclusion and exclusion criteria. 20 articles remained for qualitative synthesis. Specific methods of assessment were reviewed and three overall assessment methods were identified: 1) usage statistics, 2) survey, and 3) objective quantitative methods. 
 
 Conclusion – Many articles using a usage statistics method stated that they wanted to further their assessment of individual consultations. Several authors using a survey method described the value of the information gathered by surveying their users for improving their service, but also mentioned that this method is subjective in nature. They mentioned that objective assessment methods would provide a better understanding of the impact of IRCs. The few articles using objective quantitative methods obtained mixed results. Overall, more research in the assessment of IRCs is needed, particularly those with objective quantitative methods.
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.
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 | 0.084 | 0.266 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.165 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 it