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Record W7005812356

Školske knjižnice Istarske županije u „Školi za život“ : e-učenje kao usavršavanje i priprema za kurikularnu reformu

2019· dissertation· hr· W7005812356 on OpenAlexaboutno aff

Bibliographic record

VenueODRAZ (University of Zagreb Faculty of Humanities and SocialSciences) · 2019
Typedissertation
Languagehr
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsPeriod (music)Christian ministryQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Promjene koje su posljedica razvoja informacijskih i komunikacijskih tehnologija nužno se reflektiraju i u području obrazovanja, a time i na očekivanja od školskih knjižničara kao informacijskih stručnjaka. Da bi pripremili učenike za život i rad u današnjem, ali još i više u sutrašnjem svijetu, školski knjižničari s nastavnicima kreiraju poučavanje koje će učenike opskrbiti sposobnostima i kompetencijama za rješavanje izazova s kojima se susreću i istraživačko učenje. To je i cilj kurikularne reforme „Škola za život“. U radu se problematizira nepostojanje kurikuluma za školsku knjižnicu. Analizom kurikuluma međupredmetnih tema zaključuje se da je od sedam njih, školska knjižnica i suradnja sa školskim knjižničarem adekvatno zastupljena u dvama: „Uporaba informacijske i komunikacijske tehnologije“ i „Učiti kako učiti“. Rezultati istraživanja provedenog u školskim knjižnicama Istarske županije pokazuju da su se školski knjižničari Istarske županije u većem broju usavršavali u Loomenu (e-učenje) i pripremali za kurikularnu reformu iako su smatrali da je ta priprema besmislena bez donošenja kurikuluma koji bi pojasnio koja su očekivanja od školskih knjižničara.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0040.005
Scholarly communication0.0010.015
Open science0.0030.000
Research integrity0.0010.001
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 head0.035
GPT teacher head0.263
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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
Published2019
Admission routes1
Has abstractyes

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