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Record W4323075080 · doi:10.5539/ass.v19n2p40

The Effectiveness of Extracurricular Educational Games on the Achievement Level of Third-Grade Students in Islamic Education

2023· article· en· W4323075080 on OpenAlexvenueno aff
Ahmad Kh Yousef, Mamduh Menazel Ashraah, Manal Hendawi, Maha Salama Ghuwairi

Bibliographic record

VenueAsian Social Science · 2023
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsnot available
Fundersnot available
KeywordsEtiquetteMathematics educationTest (biology)PsychologyIslamEducational gameControl (management)Academic achievementStudent achievementComputer sciencePolitical scienceTheology

Abstract

fetched live from OpenAlex

The goal of this study is to determine whether playing extracurricular educational games increases third-grade primary children's academic achievement levels in Jordan. The study sample includes 56 male and female students (28 male and 28 female) from Madaba Governorate's Al-Khansaa Secondary Comprehensive School for Girls. A two-group quasi-experimental design is used, with an experimental group and a control group. An achievement test, three educational games, and resources relating to three topics of supplication, travel etiquette, and playing etiquette, are produced and used by the researcher. The experimental group is taught these concepts through educational games in the schoolyard, while the control group receives traditional classroom instruction. SPSS software is used to conduct a statistical analysis. The achievement test results for the control and experimental groups do not indicate any statistically significant (α≤0.05) differences. The results reveal no statistically significant (α≤0.05) gender-related variations in the experimental group's level of success. The researchers suggest that Islamic education sessions might be designed to avoid the characteristic inertia, using extracurricular educational games.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.404
Teacher spread0.358 · 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
Published2023
Admission routes1
Has abstractyes

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