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Record W7007636845

An action research study of negotiating the visual arts curriculum with Grade 8 students

2018· dissertation· en· W7007636845 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2018
Typedissertation
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumNegotiationThe artsAction researchDisengagement theoryAction (physics)Visual arts education
DOInot available

Abstract

fetched live from OpenAlex

The focus of this thesis is negotiating a visual arts curriculum with Grade 8 students. The action research study offered me a way to transform and revitalize my classroom practice to counteract the disengagement experienced by many students at this age level. I aimed to provide an example of curriculum negotiation with middle years art students in a western Canadian context. The study was guided by five research questions dealing with implementation, meeting curricular outcomes, increasing student engagement, valuing the artistic experience, and empowering students. Data collection took many forms: questionnaires, interviews, field notes, and a survey. During the study, I implemented three pedagogical action strategies that gradually transferred responsibility and ownership for visual arts learning to the students. The students’ artwork provided evidence that curriculum negotiation positively impacts students’ valuing of the artistic experience, sustains students’ levels of engagement, increases students’ sense of empowerment, and positively impacts students’ artistry.

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)0.014
metaresearch head score (Gemma)0.019
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 score0.054
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0130.008
Scholarly communication0.0100.004
Open science0.0040.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.074
GPT teacher head0.347
Teacher spread0.273 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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