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Record W2474199844 · doi:10.5539/ies.v9n7p47

Instruments of Change: An Action Research Study of Studio Art Instruction in Teacher Education

2016· article· en· W2474199844 on OpenAlexvenueno aff
İsmail Özgür Soğancı

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsStudioCurriculumCasualAction researchPedagogyAction (physics)PsychologyClass (philosophy)Mathematics educationSociologyVisual artsComputer scienceArtPolitical science

Abstract

fetched live from OpenAlex

This article narrates a nine-month action research project conducted in order to improve studio art instruction in a preservice art education programme in Turkey. Setting out to determine the relevant problems through interpretation of conversations, anecdotes, essays and observations of 16 third-year BA students, the instructional atmosphere was rearranged with respect to three themes deduced in the action research process: “us and them,” “old-fashioned curriculum,” and “caring”. The principal results illustrate the concrete examples of “instruments of change” that integrate these themes in studio art teaching: Design of the studio, willing participation, guidance on demand, collegial environment, inclusive curriculum, language, social media and music, and casual interaction. The study presents articulations of participants on each one of these instruments through direct quotes along with links to the broader educational literature. The final concentration is on a discussion based on the changes in the instructional setting conveying the essential role of “caring” in the processes of forming “instruments of change” for art education professionals.

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)0.024
metaresearch head score (Gemma)0.028
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.028
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.017
Scholarly communication0.0070.004
Open science0.0030.006
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.001

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 head0.435
GPT teacher head0.500
Teacher spread0.065 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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