Reframing from the ground up: Redesigning a credit-bearing information literacy course using the Framework for Information Literacy for Higher Education
Bibliographic record
Abstract
LIB 1500 is a three-credit information literacy course offered by the University Library at California State Polytechnic University, Pomona (Cal Poly-Pomona), which is taught by faculty librarians. The course was developed during the 2014–15 academic year and has been offered continuously since. While targeted primarily toward freshmen, in the course inevitably include a number of sophomores and upper-level students seeking to fulfill their lifelong learning General Education requirement, for which LIB 1500 is one of several options. While the development of LIB 1500 has been a labor of love, by the end of Spring Quarter 2017, those of us involved in teaching the class had noticed that the course was becoming dated and needed a complete overhaul. Therefore, during the 2017–18 academic year, librarians at Cal Poly-Pomona fundamentally redesigned LIB 1500 to reflect the threshold concepts described in the ACRL Framework for Information Literacy for Higher Education. In doing so, we learned valuable lessons about course structure, applied learning, and the iterative nature of course revision.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".