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Enregistrement W307975350 · doi:10.1080/00393541.2009.11518785

Mel Alexenberg’s<i>Educating Artists for the Future</i>

2009· article· en· W307975350 sur OpenAlexaffabout
Rita L. Irwin

Notice bibliographique

RevueStudies in Art Education · 2009
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueArt Education and Development
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésIntellectThe artsAgency (philosophy)CreativitySociologyVisual artsPraxisMedia studiesPedagogyArtSocial sciencePolitical scienceLaw

Résumé

récupéré en direct d'OpenAlex

Mel Alexenberg's Educating Artists for the Future Mel Alexenberg (Ed.). (2008). Educating Artists for the Future: Learning at the Intersections of Art, Science, Technology and Culture. Bristol, UK: Intellect Books/ Chicago: University of Chicago Press. 344 pages. ISBN 978-1-84150-191-8 (hard cover)Educating Artists for the Future: Learning at the Intersections of Art, Science, Technology and Culture is a rare find. Editor Mel Alexenberg has done a remarkable job of bringing together outstanding artist/educators who are grappling with issues related to technology, ecology, creativity, agency, identity, and community. Each individual author provides rich written descriptions of projects they have undertaken, the conceptual underpinnings that frame their work, and the implications of their practices for art education in informal and formal learning contexts. I am certain that readers reviewing this book will feel a profound sense of collectivity knowing we are at the edge of transforming the world in which we live.The volume is divided into the following five sections, book-ended with an introduction and epilogue by the editor: Beyond the Digital, Networked Times, Polycultural Perspectives, Reflective Inquiry, and Emergent Praxis. Each section has four chapters making this 22-chapter book an extensive array of ideas from authors representing Brazil, Canada, China, Czech Republic, Finland, Germany, India, Israel, South Korea, Switzerland, Turkey, the United Kingdom, and the United States. Its international character alone makes this book a must read for educators wanting to understand the arts and education at a global level.One of the most prominent threads running throughout the book (for me) is its references to complexity theory. A number of authors refer to complexity theory being an influential theory coming from the mathematical sciences, while other authors may not refer to complexity theory but rather, the language of the chapter reiterates the characteristics of the theory. One of my colleagues, who coincidentally is a mathematics educator, has joined forces with two curriculum scholars to write several books on complexity theory in education (e.g., Davis, Sumara & Luce-Kapler, 2007). I was delighted to see how artists, scientists, and educators have taken up this theory in such strong yet innovative ways and can hardly wait to introduce this book to the many complexity theorists I know working in education, and particularly art education. It is on this basis that I would highly recommend the book to undergraduate and graduate students as well as to instructors who want to re-imagine how we perceive and understand education, art, science, technology, and culture now and in the future.Why complexity theory? Everywhere we look today, we are networked in decentralized (and centralized) structures and through a variety of interactions (with lots of feedback loops) taking place within these structures, creating selforganizing communities or projects. Complexity theory, as developed by several authors in this book, discusses four characteristics of complex systems: differentiation, interaction, self-organization, and emergent behavior. For artists and art educators, differentiation is about how we use materials in a variety of ways and how our connections with people can be accessed differently from what may have been expected. Interaction refers to the direct relationships viewers and authences have with people and processes that, in turn, provide opportunities for participants to alter the artworks or what is learned. Selforganization applied to the arts would suggest that while artists may start an artistic project, others would also participate in the development of the process and/or product, and as such, the project would be attributed to all of the creators. Emergent behavior is very exciting for artists and educators. Here is where a complex system naturally evolves and adapts into a number of possible structures, perhaps even simultaneously, knowing that the end product may look incredibly different from the original proposition. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,809
Score d'incertitude au seuil0,536

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,050
Tête enseignante GPT0,347
Écart entre enseignants0,296 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2009
Routes d'admission2
Résumé présentoui

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