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Record W2738971336 · doi:10.5539/jel.v6n4p239

Is There a Relationship between Creativity and Mathematical Creativity?

2017· article· en· W2738971336 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Leadership and Administration
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityFluencyOriginalityMathematics educationPsychologyTest (biology)Qualitative researchFlexibility (engineering)Content analysisQualitative propertyPedagogySocial psychologyMathematicsStatisticsSocial science

Abstract

fetched live from OpenAlex

The aim of this study is to examine the mathematical creativity of individuals who think they have creative thinking skills. Forty-four teachers who work in private schools participated in this study and they have their pedagogical formation training from a public university in order to be a public teacher. Also participants have at least one year of experience. Mixed method research is defined as combining qualitative and quantitative methods, approaches and concepts in successive studies (Creswell, 2003). This study was determined as a mixed method research since data first analyzed by content analysis (qualitative) and then relationship and comparison analysis (quantitative). In order to analyse problem situation of the study, two testing instruments one of which is ready to use were utilized. Problem solving and problem posing test as two items was developed by the researcher. On item was given to participants as a geometry problem in the testing instrument and they were asked to solve this problem by using as many different methods as they can. The other item was given to participants as a semi-structured geometry situation. They were asked to pose as many problems as they can by using this situation. Data obtained from solving draft were divided into categories in terms of flexibility, fluency and originality according to content analysis from qualitative data analyses for each participants.As a result of the study, according to the teachers’ creativity that they stated, we can talk about their mathematical creativity only if they can pose an authentic problem.

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.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.170
GPT teacher head0.447
Teacher spread0.277 · 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