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Record W2942587821 · doi:10.5539/ass.v15n5p83

Level of Metacognitive Skills of a Sample of Talented Students in Jordan

2019· article· en· W2942587821 on OpenAlexvenueno aff
Esam Abdullah Al Jaddou

Bibliographic record

VenueAsian Social Science · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsMetacognitionPsychologyExcellenceSample (material)Scale (ratio)Significant differenceMathematics educationStratified samplingReliability (semiconductor)StatisticsCognitionMathematicsGeographyChemistryPolitical science

Abstract

fetched live from OpenAlex

This study aimed at identifying the metacognitive skill level of a sample of talented students in Jordan, and whether the level is affected by the difference of a number of variables. The sample consisted of (256) male and female students who were chosen by the random stratified method. Out of them were (101) male and female students from the Jubilee School, and (155) from King Abdullah II School for Excellence, during the academic year 2018-2019. To achieve the study objective, the metacognitive thinking scale was applied after verifying its validity and reliability. The results showed that the total degree of the metacognitive skill level of a sample of talented students in Jordan was high. The results did not show statistically significant differences in the metacognitive skill level attributable to the gender variable. Meanwhile, there were statistically significant differences at (α≤0.05) level attributed to the grade level variable.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.397
Teacher spread0.349 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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