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Record W2112955200 · doi:10.5539/res.v6n1p1

Creative Teaching in Art: Content Analysis and Evaluation of Training Manuals Formed by Students

2014· article· en· W2112955200 on OpenAlexvenueno aff
Kampouropoulou Maria, Persa Fokiali, Ioanna Efstathiou, Efstathios Stefos

Bibliographic record

VenueReview of European Studies · 2014
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityPresentation (obstetrics)Cultural heritageContent analysisTraining (meteorology)PsychologyMathematics educationPedagogyVisual artsSociologyArtSocial scienceHistoryArchaeologyGeographyMedicine

Abstract

fetched live from OpenAlex

The goal of this study is to investigate and evaluate training manuals created by students, like exploration of their views on how promoting children’s cultural heritage in Primary schools. The study concerns the degree of completeness of the training manuals according to their content and functionality within aesthetic presentation, creativity, responsiveness to pedagogical objectives, etc. They were created by students studying in the Department of Primary Education of the University of the Aegean (fourth year of training) and they completed their work for the course “Artistic Education and Creations of Artistic forms”. The issue was: The Palace of the Grand Master, history and environment of the medieval city of Rhodes. In order to extract the research results, we used statistical software SPSS v.17 offered by the School of Humanities of the University of the Aegean.

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)0.008
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.280
GPT teacher head0.513
Teacher spread0.233 · 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 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

Citations1
Published2014
Admission routes1
Has abstractyes

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