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Record W199180689

Visual Culture in the Art Class: Case Studies

2007· article· en· W199180689 on OpenAlexaboutno aff
Jerome J. Hausman

Bibliographic record

VenueStudies in Art Education · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsVisual cultureVisual arts educationPaintingConventionInterpretation (philosophy)SociologyCurriculumSloganVisual artsPedagogyArtAestheticsLawPolitical scienceSocial scienceThe artsLinguistics
DOInot available

Abstract

fetched live from OpenAlex

Culture in the Art Class: Case Studies Paul Duncum, Editor (2006). Reston, VA: National Art Education Association. 194 pages. ISBN 1-890160-33-4Anyone attending the 2006 National Art Education Association Convention in Chicago could not help but be impressed by the frequency with which the term appeared in the convention program (Visual Culture in K-8 Classes for Critical Thinking, Body in Culture, Visual Culture Reform in Practice, Visual Culture and Curriculum Interpretation, Media Education Incorporated in Culture, Is it Public Art or Culture? etc.). There were about 30 such entries! It would seem that our field is one given to adopting (and adapting) particular terms or themes and then allowing them to run rampant in our literature and professional discourse.I chuckle when I think back to my own experience in describing differing emphases in the teaching of art: studio practice in artmaking (drawing, painting, sculpture, etc. with emphasis upon form-making techniques); visual forms as integral parts of celebrations (holidays, community events, etc.); experiencing and understanding the works of old masters (Rembrandt, Goya, Van Gogh, Monet, etc.); formalist delineations (line, color, form, composition, etc.), core curriculum (the American Revolution, Westward Expansion, the Civil War, the Industrial Revolution, etc.); and more recently, discipline-based art education and the development of standards as to students should know and be able to do as a result of art instruction. It is as if we have needed a more singular broadly based theme or persuasive slogan with which to attract attention and gain greater support for the teaching of art in our schools.Now the term being used is culture. At the onset, this book's editor, Paul Duncum, states his idea of what he intended by the term culture. As writers responded, he realized the differing meanings people held, but in general:Visual culture meant dealing with the popular culture of student experience and drawing upon both the history of imagery and cross-cultural comparisons to gain a perspective. The study of visual culture involved balancing the undeniable pleasures of popular culture with critiquing it for its often reactionary and anti-social values. It meant considering images as texts and beyond to consider their contexts (p. ix).Duncum and other serious adherents to the cause of are quick to disassociate themselves from simplistic slogans and bandwagon ideologies. They recognize that there's much that is being advocated that isn't new. In a recent article, Kevin Tavin (2005) made reference to critical antecedents of visual culture in art education(p. 6). He cited the work of Vincent Lanier, Jane McFee, Laura Chapman, and Brent and Marjorie Wilson as having focused on the realm of the everyday and helped posit popular cultural images as legitimate objects of study in art education (p. 16). Indeed, any thoughtful review of our field would find cross currents and connections to counter catch-all generalizations that purport to revolutionize art instruction. Thus, it is not a more singular, modernist idealogy that is being suggested in Culture in the Art Class: Studies. What we have is a series of brief narratives offered by teachers in the United States, Spain, Korea, and Canada that portray one or several units, rather than extended and more detailed descriptions of programs. It's a bit of a stretch to identify some of the narratives as case studies. They are much too brief. However, in varying ways, the chapters raise important issues for our field. …

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.376
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.078
GPT teacher head0.403
Teacher spread0.325 · 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 teacher head, 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

Citations0
Published2007
Admission routes1
Has abstractyes

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