Sustaining the Integration of Local Wisdom into School Life: A Case Study and Bibliometric Approach
Bibliographic record
Abstract
The integration of local wisdom into school life has emerged as a vital strategy for fostering culturally responsive education that affirms students' identities and strengthens community ties.This study examines the sustainability of embedding local wisdom, particularly Sasak cultural values, into educational practices, using a combined bibliometric and case study approach.A bibliometric analysis was conducted to map global research trends on local wisdom in education, while a qualitative case study investigated the implementation of Sasak values in schools in East Lombok.Data were collected through interviews, observations, focus group discussions, and document analysis, and were analyzed thematically.Findings reveal that Sasak local wisdom, encompassing values such as honesty, discipline, hard work, tolerance, mutual cooperation, independence, responsibility, and religious integrity, plays a significant role in shaping student character and promoting holistic development.The bibliometric review highlights growing scholarly interest in themes such as indigenous knowledge, cultural heritage, and digital storytelling, reflecting a global shift toward contextualized pedagogy.However, challenges such as rigid curricula, limited teacher training, and inadequate institutional support hinder effective implementation.This study demonstrates that integrating local wisdom into school life not only enriches educational content but also fosters identity formation, resilience, and social cohesion.It contributes to the growing body of literature on culturally grounded education, calling for systemic reforms to support sustainable and inclusive learning environments rooted in local culture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.037 | 0.062 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".