Better Collaborative Working is Likely to Increase Uptake of Library Resources in a University Setting
Bibliographic record
Abstract
A review of: Hightower, Barbara, Carolyn Rawl, and Michelle Schutt. “Collaborations for Delivering the Library to Students Through WebCT.” Reference Services Review 35.4 (2007): 541-51. Objectives – To ascertain the extent to which university faculty members are integrating library resources within the WebCT course management system / managed learning environment. Also, to identify the reasons why faculty members are not integrating library resources within WebCT, and to explore their willingness to do so in future. Design – Case study with survey questionnaire and selected interview follow up. Setting – Urban campus of Auburn University in Montgomery, Alabama, United States of America. Subjects – One hundred and two members of faculty received a questionnaire. Five follow-up interviews were conducted. Methods – One hundred and two members of faculty with WebCT-supported courses received a questionnaire. They were asked to indicate if they linked to library resources, and if so which specific ones (e.g. library homepage, online catalogue, etc.). If they did not link to library resources they were asked to indicate the reason why not, either by selecting one or more of five pre-selected reasons, or by detailing their own. Follow-up interviews were conducted with five respondents, two of whom (Education and Nursing) linked to library resources, and three of whom (from Business, Education and Science) did not. Server log reports were also examined to identify how many students were entering library resources from WebCT. Main Results – The survey response rate was 28% (29 individuals), and of these Nursing and Sciences were the highest users with 7 individuals in each faculty. Of the 29 respondents only 7 (24%) currently linked to library resources. Nursing were the biggest group with 10 links (38% of the total), Science with 6 (23%) and 5 each from Liberal Arts and Education (19%). The resources chosen to link to were • Article databases (6) • Library homepage (5) • Ask a Librarian e-mail service(3) • Net library e-book collection (3) Six other library resources scored lower and two were not linked to at all. While few respondents actually provided links at present, 77% of those did express an interest in doing so in the future. Almost a third of respondents asked to be contacted to learn more about how to provide links and to learn more about library services. Only 57 incidents of students linking through to library resources from WebCT occurred in the study period. Conclusion – Numbers of faculty currently providing links from WebCT to the library is very small, and few students find their way to library resources via this route. However, interest generated by the survey and follow up indicates that this may be a valuable means of promoting library resources.
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 | 0.028 | 0.111 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 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".