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Record W2586623750 · doi:10.5539/elt.v10n3p82

The Effect of English Language Learning on Creative Thinking Skills: A Mixed Methods Case Study

2017· article· en· W2586623750 on OpenAlexvenueno aff
Sandro Sehic

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsnot available
Fundersnot available
KeywordsOriginalityFluencyPsychologyElaborationFlexibility (engineering)CreativityMathematics educationTest (biology)Qualitative propertyData collectionCognitive psychologySocial psychologyComputer science

Abstract

fetched live from OpenAlex

The purpose of this sequential explanatory mixed-methods case study was to investigate the effects of English language learning on creative thinking skills in the domains of fluency, flexibility, originality, and elaboration as measured with the Alternate Uses Test. Unlike the previous research studies that investigated the links between English language learning and cognitive skills and had large numbers of participants, this research study relied on small group of participants to provide detailed information about the effects of English language learning on their creative thinking skills in the domains of fluency, flexibility, originality, and elaboration as measured with the Alternate Uses Test. This study involved the collection of quantitative data at the pretest and posttest stages and the explanation of the quantitative data using qualitative data. The quantitative findings of this sequential explanatory mixed-method case study indicated that there were no statistically significant differences between the pretest and posttest results in the domains of fluency, flexibility, originality, and elaboration as measured with the Alternate Uses Test.

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)0.008
metaresearch head score (Gemma)0.050
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.050
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.424
Teacher spread0.408 · 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 teacher head, not a consensus.

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

Citations13
Published2017
Admission routes1
Has abstractyes

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