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Record W7122630905 · doi:10.15575/atthulab.v10i1.49518

Multicultural Problem-Based Learning: Strategies for Improving Religious Moderation in Elementary Schools

2025· article· W7122630905 on OpenAlexaff
Apip Rudianto, Bunyamin Maftuh, Mubiar Agustin, Ernawulan Syaodih, Rosihon Anwar

Bibliographic record

VenueAtthulab Islamic Religion Teaching and Learning Journal · 2025
Typearticle
Language
FieldSocial Sciences
TopicMulticultural Education and Local Wisdom
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsMulticulturalismModerationReligious educationPerceptionRelevance (law)School teachersIslam

Abstract

fetched live from OpenAlex

This study examines teachers’ perceptions of the relevance and effectiveness of Multicultural Problem-Based Learning (MPBL) in strengthening religious moderation attitudes among Elementary School and Madrasah Ibtidaiyah students in Kuningan Regency, Indonesia. A quantitative survey approach was employed using a questionnaire developed from key dimensions of religious moderation, namely national commitment, religious tolerance, appreciation of religion-based local culture, and religion-based anti-violence, as well as indicators of the importance of MPBL in primary education. The results indicate that teachers overwhelmingly perceive MPBL as a highly relevant and effective learning approach. MPBL is considered capable of strengthening students’ character in appreciating diversity, reducing negative stereotypes and prejudice, and fostering critical, collaborative, and solution-oriented thinking skills. Teachers also agree that this approach supports the internalization of tolerance, respect for different religious beliefs, and appreciation of local cultural wisdom rooted in religious values. However, the findings reveal that students’ deeper understanding of the universal principle that all religions teach peace has not been fully internalized, indicating a gap between cognitive understanding and affective–behavioral development.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0060.000
Scholarly communication0.0030.001
Open science0.0000.000
Research integrity0.0000.006
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 head0.011
GPT teacher head0.317
Teacher spread0.306 · 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 designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

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