Investigating Technology Integration Practices and Competencies of School Librarians
Bibliographic record
Abstract
The 21st century school has demanded the increasing use of technology integration. This study investigates technology practices and competencies of school librarians. An online survey targeting current school librarians working in Kentucky, USA was conducted through the email listserv for Kentucky Library Media Specialists (KYLMS). The survey data were analyzed and interpreted on the basis of, and in relation to, a cross-mapping of the following two criteria via the seven technology areas by the National Center for Education Statistics: (1) 2010 ALA/AASL Standards for Initial Preparation of School Librarians, and (2) knowledge and skills specifications for school media librarians in the Praxis II Library Media Specialist test. The combined context can serve as a framework for comparative or evaluative analyses on the school librarians’ practices and competencies of technology integration. Implications of the results are discussed, including as a reference for school library program curriculum development and implementation.
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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 | 0.000 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".