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Record W2186190189 · doi:10.36510/learnland.v6i1.580

Nurturing Creativity and Professional Learning for 21st Century Education: ResponsiveDesign and the Cultural Landscapes Collaboratory

2012· article· en· W2186190189 on OpenAlexvenueno aff
Ralph A. Córdova, Kristiina Kumpulainen, Jeff Hudson

Bibliographic record

VenueLEARNing Landscapes · 2012
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityCollaboratoryPerspective (graphical)SociologySpace (punctuation)Complement (music)EthnographyPedagogyPsychologySocial psychologyComputer scienceAnthropology

Abstract

fetched live from OpenAlex

This study examines events within a CoLab1 3RDSpace: Summer Leadership Institute on Creativity & Innovation. The analyses are organized into two telling cases and reveal how participants develop a shared understanding of ResponsiveDesign, CoLab’s theory of inquiry and innovation. Drawing on an interactional ethnographic perspective, the analyses make visible the ways in which concepts of space, language, creativity, and innovation complement one another to form ResponsiveDesign as a powerful approach for educators in any setting to transform their ordinary places into extraordinary spaces for creatively confident learning.

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)0.009
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.011
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.027
Scholarly communication0.0110.009
Open science0.0010.017
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.363
Teacher spread0.337 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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