Adapting Education for School Librarianship
Bibliographic record
Abstract
Over the past few years repeated calls have been made by teacher librarian educators for evidence based practice by teacher librarians. This study is an attempt to provide evidence for the adoption of innovative practice in a post-service, part time Bachelor of Education program. Part time tertiary students undertaking studies in education at the University of Hong Kong are often heard to voice the opinion that the demands of university study are excessive. While it is generally accepted that the Hong Kong lifestyle is hectic, that teachers have a heavy schedule, and that travel to and from the university campus is time-consuming, little useful data exists to allow university professors to better understand the plight of the students or to provide evidence from which action could be taken to better tailor courses to the needs of students. Likewise many assumptions are made about tertiary student motivation but these assumptions are probably not grounded in any research findings. This exploratory study was undertaken to determine the factors affecting the full-time teacher’s progress in their tertiary part-time study in school librarianship. The findings will better enable instructors to tailor teaching and learning to meet the needs of the part-time participant. Findings will also be informative for other part-time undergraduate programs.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".