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Record W2540482751

Elementary Artists as Scientists: Educational Technology as a Catalyst

2016· article· en· W2540482751 on OpenAlexaff
David Cloutier, Norman Vaughan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsMount Royal University
Fundersnot available
KeywordsAffordanceEducational technologyMathematics educationThe artsPerceptionPedagogyLearning sciencesPsychologyComputer scienceVisual artsHuman–computer interactionArt
DOInot available

Abstract

fetched live from OpenAlex

What happens when you use educational technology with young artists? In this research study, we endeavoured to discover “ How do elementary students perceive learning through the arts with educational technology? ” This action research project focused on student perceptions of learning in a grade 6 arts-centered learning school using educational technology to disrupt and to scaffold learning. We found that students can appreciate and maintain their inner artist while benefitting from the affordances of educational technology. Specifically, we discovered that educational technology can help elementary students to see through multiple lenses of learning as researchers and explorers that enable them to embrace their creative capacities. Students felt better about their learning when they were able to choose their own mechanisms of learning, and rely on the teacher and their peers for support in discovering those mechanisms. By nature of the study’s design, it is also model for investigative analysis into students as researchers, in parallel with the instructor as a learner (“Teacher as co-Learner”).

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.1190.016

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 head0.014
GPT teacher head0.264
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2016
Admission routes1
Has abstractyes

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