Looking Toward the Future: Competences for 21st-Century Teacher-Librarians
Bibliographic record
Abstract
What are the core competences required by teacher-librarians for developing exemplary school library programs in 21st-century schools? This article reports on a study that explored the experiences and attitudes of graduates from the Teacher Librarianship by Distance Learning program at the University of Alberta in Edmonton. Key findings from this study of teacher-librarians indicate that technology and leadership issues are the most pressing needs. These graduates also indicated that their “traditional roles and responsibilities” are changing as they are responsible for promoting new literacies and evaluating, selecting, organizing, and managing diverse learning resources. Quelles sont les compétences de base dont ont besoin les professeurs-bibliothécaires pour développer des programmes de bibliothèque exemplaires pour les écoles du 21e siècle? Cet article décrit une étude qui a exploré les expériences et les attitudes des étudiants diplômés du programme en bibliothéconomie par apprentissage à distance à la University of Alberta à Edmonton. Les principales conclusions découlant de cette étude sur les professeurs-bibliothécaires révèlent que les enjeux relatifs à la technologie et au leadership constituent les besoins les plus immédiats. Les diplômés ont également indiqué que leurs « rôles et responsabilités traditionnels » évoluent puisqu’ils sont responsables de la promotion de nouveaux modes d’alphabétisation, ainsi que de l’évaluation, la sélection, l’organisation et la gestion de diverses ressources d’apprentissage.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.010 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".