AASL National School Library Standards: Progress toward Implementation
Bibliographic record
Abstract
This mixed-methods, exploratory case study examines perceptions of the implementation of the U.S. National School Library Standards for Learners, School Librarians, and School Libraries. A survey was first distributed to gain insight into school librarian implementation of the NSLS. Participants included practitioners in the state of Virginia in the United States who had attended professional development training on the National School Library Standards (NSLS). A sample was then interviewed about their implementation. Using the standards implementation levels identified by the California Common Core Implementation Task Force (2019) as a framework, findings indicate that after one year of training and use, many librarians remain at the awareness phase of implementation. Findings do suggest some areas in which practitioners have shown progress as they implement the standards into practice. Finally, common challenges or barriers to implementing the NSLS are noted. Future directions for research and recommendations for training at both the school/district level and national organization level are suggested.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.055 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.042 | 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; 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".