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Record W2116942817 · doi:10.5539/ies.v4n1p127

Exploring the Impact of Handcraft Activities on the Creativity of Female Students at the Elementary Schools

2011· article· en· W2116942817 on OpenAlexvenueno aff
Amir Rezaei, Manijeh Zakariaie

Bibliographic record

VenueInternational Education Studies · 2011
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityFluencyPsychologyMathematics educationOriginalityTest (biology)Flexibility (engineering)Descriptive statisticsElaborationPrimary educationData collectionStatistical analysisSubject (documents)PedagogySocial psychologyStatisticsMathematicsComputer scienceHumanities

Abstract

fetched live from OpenAlex

Creativity has been one of the interesting issues in the field of education and has been subject of some studies. But studying the effect of using handcraft on the enhancing learners’ creativity at early stages of education has not been focused on in many studies. Therefore, in this study an effort was made to explore the effect of using handcrafts on the enhancement of the creativity among the learners at elementary schools. The participants in this study were 64 female students who were selected randomly from elementary school learners at grade five in Tehran. For data collection Torrens Creativity Test was used and data gathering was done through pre-test and post-test. Data was analyzed by using descriptive statistics and ANOVA analysis. The data analysis revealed that using handcraft as an instrument was significantly effective in enhancing students’ score in originality, flexibility and elaboration at the elementary grades, whereas; there was not any significant difference between their scores in fluency. The findings and their implications are discussed more in detail.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.477
GPT teacher head0.533
Teacher spread0.056 · 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 designObservational
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

Citations5
Published2011
Admission routes1
Has abstractyes

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