Library & information literacy initiative : the SSC-R de Cavite experience
Bibliographic record
Abstract
A paper presents the result of the study conducted on the level of library and information literacy competency of engineering students of SSC-R de Cavite as basis for the development of an intervention programs. The study attempted to look into the following: 1) the level of library and information literacy competency of engineering students; and, the respondents strengths and weaknesses in terms of the identified competencies. The researcher used the descriptive-normative method, using the CSPU (California State Polytechnic University) and the CREPQU (Conference of Rectors and Principals of Quebec Universities) Information Competency Assessment instruments. The reliability index suggests that there is a high degree of internal consistency among the items as well as there is a marked reliability of the instrument; hence, the instrument was valid. It was then, administered to 341 engineering students enrolled in a 4- and 5-year program with 87.38% (298) response rate. Results revealed that the respondents have limited knowledge and have not acquired the desired library and information literacy competencies in determining the extent of information needed; accessing the needed information effectively and efficiently; evaluating information and its sources critically; and using information effectively to accomplish a specific purpose; and understand the economic, legal, and social issues surrounding the use of information.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".