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Record W4254807030 · doi:10.3402/edui.v6.23403

Associating creativity, context, and experiential learning

2015· article· en· W4254807030 on OpenAlexaff
Catharine Dishke Hondzel, Ron Hansen

Bibliographic record

VenueEducation Inquiry · 2015
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsWestern University
Fundersnot available
KeywordsCreativityExperiential learningSituatedContext (archaeology)PsychologyEpistemologyProcess (computing)Creativity techniqueCognitive scienceSociologyPedagogySocial psychologyComputer science

Abstract

fetched live from OpenAlex

One of the difficult aspects of defining creativity is that the term means many things to each of us, and reflects our unique perspectives and experiences. Our situatedness within a unique, personal context means that the concept of individual creativity defies formal scientific definition. This paper is an attempt to conceptualise creativity differently. It tries to break new ground by defining it through the process of being creative within a dynamic environment. We consider how individuals think about creativity, especially outside the confines of our institutionalised learning, and through the lens of experience. The context is a rising public and scholarly interest in the topic but using the complimentary frameworks of situated cognition and experiential learning. This conceptual paper takes a critical look at formal learning and human creativity, and the role teachers, educators and policymakers play in the process.

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)0.005
metaresearch head score (Gemma)0.015
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 score0.010
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.023
Scholarly communication0.0100.008
Open science0.0010.011
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.120
GPT teacher head0.436
Teacher spread0.316 · 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

Citations22
Published2015
Admission routes1
Has abstractyes

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