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Record W2923596042 · doi:10.5539/ies.v12n4p217

Critical Thinking Skills in Elementary School Curricula in some Arab Countries—A Comparative Analysis

2019· article· en· W2923596042 on OpenAlexvenueno aff
Raja Omar Bahatheg

Bibliographic record

VenueInternational Education Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumCritical thinkingCredibilityMathematics educationArabicSemitic languagesPedagogyFocus groupPsychologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

This study aims to analyze and compare school subjects to determine the extent to which critical thinking skills are being engaged in school subjects’ questions and activities in public education. Five Arab countries are included in this paper; Saudi Arabia, Kuwait, The Hashemite Kingdom of Jordan, Arab Republic of Egypt, and The Tunisian Republic, in elementary school levels (first, second, and third grades.)The study found that all Arab countries focus on operating inductive reasoning skills in their subjects, followed by reasoning and observation, sequentially, while dismissing credibility and assumptions skills. Saudi Arabia focused on developing critical thinking skills in science textbooks for the past three academic years, while Kuwait had the same focus on their Arabic language classes. Both the Hashemite Kingdom of Jordan and Egypt have paid a measurable attention to engaging critical thinking skills in Mathematics and the Arabic language, as well as Tunisia in their science textbooks. The least effective subjects in operating critical thinking skills were the Arabic language in Saudi Arabia, science in Kuwait, Domestic Economics in Egypt, and Islamic education in Jordan and Tunisia.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.455
Teacher spread0.418 · 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 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

Citations10
Published2019
Admission routes1
Has abstractyes

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