Study on Establishing Competency Profile Standard of Teacher Librarian in Optimizing the Use of ICT in Secondary Level School Library
Bibliographic record
Abstract
Teacher librarians are expected to have good skills in using information and communication technology (ICT) so that they can assist both students and teachers in finding the information they need. The aim of this study was to establish the competency profile standard of teacher librarians using ICT at the secondary level. More specifically, this study would like to find out the competency profile of teacher librarians, the optimization of the use of ICT by teacher librarians, and the competency standard required in using ICT for teacher librarians in secondary level. This study used qualitative approach with survey method and the data was collected through interview and observation. The general conclusion is that the library administrators/teacher librarians in the schools presented in this research always met and enhanced the competencies that supported their daily tasks in the library and in their field of study by trying to take advantage of hardware utilization to improve the library service to the users. Specifically, this study shows that library administrators/teacher librarians are the subject teachers who receive additional tasks to manage the library; have a willingness to study and make innovations in the library; and try to have information, media and technology literacy skills, as well as the ability to enliven the life and career related to their fields. The competency standard of the majority of library administrators/teacher librarians in using ICT is considered good, they show good attitude, knowledges and skills but are often hampered by the lack of infrastructure, budget, and practice training to apply ICT in the school library. This research recommends that library administrators/teacher librarians should have functional status as librarians, not educative function as subject teachers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".