The integration of course support materials into the information literacy research process
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore how course informational needs are being satisfied by materials outside of traditional library resources. Design/methodology/approach The design is based on the results of a survey of instructional faculty at Central Washington University during fall quarter 2008. Findings The findings show that course support materials available through publishers meet in many cases the immediate informational needs of students. Additionally, these materials are directly tied to specific course/research needs and activities. The paper also demonstrates that these materials permit students to bypass the initial and fundamental steps of the information literacy process. Practical implications The implications may be that libraries will continue to see stagnant funding as the informational needs of students are being met through other means. The lack of complaints regarding adequate material budgets will remain strong within the library but largely silent at the campus level. Another implication is that the cost of access is now being borne by the immediate user, the student, and that the library is repurchasing similar materials for the university as a whole. Originality/value The paper provides useful information on whether course informational needs are being satisfied by materials outside of traditional library resources.
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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 | 0.033 | 0.121 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".