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Record W2083727061 · doi:10.1080/08929092.2010.518907

Connecting With Their Inner Beings: An International Survey of Drama/ Theatre Teachers' Perceptions of Creative Teaching and Teaching for Creative Achievement

2010· article· en· W2083727061 on OpenAlexaffabout
Laura A. McCammon, Larry O’Farrell, Aud Berggraf Sæbø, Brian Heap

Bibliographic record

VenueYouth Theatre Journal · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsQueen's University
Fundersnot available
KeywordsDramaCreativityPsychologyMathematics educationPerceptionPedagogyCurriculumVariety (cybernetics)Teaching methodSociologyVisual artsArtComputer science

Abstract

fetched live from OpenAlex

As the first phase of a multinational exploration of the nature of creativity and its relationship to drama/theatre education, a mixed methods survey was given to 100 classroom teachers in four countries: Canada (Ontario), the United States (Arizona), Jamaica and Norway. Teachers were both elementary generalist and secondary specialists; most had some drama education. This article documents the following: a brief review of the related literature; survey results with an emphasis on the qualitative data; and a brief overview of the next phases of the research. Survey results suggest that teachers of drama/theatre believe in the importance of teaching for both creative achievement in their students and in themselves as creative teachers—especially when solving teaching problems. Examples of their practice indicate that teachers implement a variety of student-centered drama/theatre approaches in their classrooms. However, teachers do not perceive support for their creative work from their schools or the school system, nor do they have confidence in their capacity to assess student achievement in creativity.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.030
GPT teacher head0.287
Teacher spread0.257 · 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

Citations12
Published2010
Admission routes2
Has abstractyes

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