Librarian Expertise is Under-Utilized by Students and Faculty in Online Courses
Bibliographic record
Abstract
A Review of: Steele, J.E. (2021). The role of the academic librarian in online courses: A case study. Journal of Academic Librarianship, 47(5), 102384. https://doi.org/10.1016/j.acalib.2021.102384 Abstract Objective – To examine the role of academic librarians in online courses in a university setting. Design – Survey questionnaire. Setting – A multi-campus university in the southern United States. Subjects – Students, faculty, and librarians who had taken, taught, or assisted in fully online courses. Methods – Email addresses for potential survey participants were provided by the university office of institutional research. The researchers tailored survey questions weto specific subject groups. The surveys took roughly 15 minutes to complete and were open for 1 week following the original email. Surveys included 12 – 16 questions, depending on the version, and included questions relating to the use of librarians in online courses, the type of assistance they provided, and how assistance was provided (e.g., in person, email, live chat). Question types included yes/no, check-all-that-apply, and open-ended-answer. Main Results – Of the student responders, 23.24% reported asking a librarian for help with research or an assignment. This help included finding resources (34.48%), database searching (28.57%), and searching the library catalog (20.69%). Help was given over email (28.03%), live chat (31.82%), and in person (17.42%), which was reported to be most helpful by several students. Only 10.61% reported using video-conferencing software such as Zoom. Only 5.88% of faculty reported including a librarian for synchronous instruction in online courses, while 19.12% made use of asynchronous tutorials created by a librarian. The majority of respondents (93.1%) had not worked with an embedded librarian in their courses, and many reported not knowing that it was an option. Instead, faculty perceived librarians to be an outside resource. Both faculty members and students reported a desire for more video tutorials from librarians. Several faculty mentioned wanting a library module that could serve as an introduction to the library, library resources, and basic instruction topics such as citation styles. Conclusion – While some students and faculty have worked with librarians in online courses and welcomed their involvement, there is room for improvement in library outreach, including how the library communicates with and supports this growing population.
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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 | 0.000 |
| 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 | 0.001 | 0.588 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".