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Record W7067277727

Library & information literacy initiative : the SSC-R de Cavite experience

2006· article· en· W7067277727 on OpenAlexaboutno aff

Bibliographic record

VenueE-LIS Repository (University of Naples Federico II) · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsInformation literacyConsistency (knowledge bases)Internal consistencyReliability (semiconductor)Strengths and weaknessesIntervention (counseling)Index (typography)
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0010.038
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.222
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2006
Admission routes1
Has abstractyes

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