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Record W2890033807 · doi:10.29173/iasl7444

Information literacy: Hong Kong primary teachers’ perceptions of the role of the teacher librarian

2021· article· en· W2890033807 on OpenAlexvenueno aff
Angel Leung Yuet Ha

Bibliographic record

VenueIASL Annual Conference Proceedings · 2021
Typearticle
Languageen
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsnot available
Fundersnot available
KeywordsInformation literacyMedical educationPerceptionGovernment (linguistics)LiteracyPsychologyPedagogySchool teachersMedicine

Abstract

fetched live from OpenAlex

This study aims at investigating Hong Kong primary teachers’ perceptions of the teacher librarian role in relation to information literacy. Primary teachers’ responsibility for equipping students with information literacy skills in cooperation with the teacher librarian is focused. A mixed-method of quantitative and qualitative approach was taken. The data were collected through questionnaires sent to every tenth primary schools listed in the Primary School Profiles 2011 published by the Committee on Home-School Co-operation, EDB, HKSAR and face to face interview with six questionnaire respondents. Questionnaires were sent to 146 schools. 75 teacher respondents answered and sent back. The results have identified teachers’ understanding of information literacy, the need to develop student such skills, professional development needs and teaching in terms of information literacy skills, government policies and school administration related to the teacher librarian role. Some suggestions were made regarding to teachers’ professional development needs in terms of information literacy.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.136

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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