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Record W3139899015 · doi:10.29173/iasl8077

Online Library Systems for Malaysian School Libraries: An Experimental Approach

2021· article· en· W3139899015 on OpenAlexvenueno aff
A. N. Zainab

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceInterface (matter)World Wide WebSchool libraryTest (biology)Graphical user interfaceLibrary classificationUser FriendlyMultimediaProgramming languageOperating system

Abstract

fetched live from OpenAlex

This paper describes the development of two experimental school library information systems for Malaysian schools. The results of a user study, conducted using different sets of questionnaire for both types of schools indicated that students in general, borrowed books from the library by browsing the shelves. Students seldom used the catalogue card for searching and only a small percentage reported that they were able to find the books successfully using the catalogue card. Based on the findings, a conceptual model of the prototype automated catalogue was developed - Virtual Library for use in primary schools, and ELIS for secondary schools. Both systems are divided into two main modules, the Administrator and the User module. User acceptance test showed that the majority of students found the systems user friendly. Students were also successful in the search tasks given. A high majority described the graphical user interface to be attractive and simple. This indicates the feasibility of using the systems for school libraries in Malaysia.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.041
GPT teacher head0.314
Teacher spread0.273 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2021
Admission routes1
Has abstractyes

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