Developing Social Skills for Cohabiting in a Multicultural Society Through the Board Game Religio
Bibliographic record
Abstract
This study aimed to evaluate the effectiveness of the Religio board game in developing the social skills necessary for cohabitation in a multicultural society among grade 9 students, with a particular focus on communication, respect for rights, and acceptance of diversity. Additionally, it examined changes in these dimensions before and after gameplay to develop strategies for enhancing learning in multicultural environments. A quasi-experimental research design was employed, involving a sample of 25 students selected through voluntary sampling. The findings indicated that the Religio board game was highly effective in fostering social skills, as expert evaluations yielded an average score of 4.88, reflecting a high level of effectiveness. Significant improvements were observed in acceptance of diversity (pre-test mean = 2.64, post-test mean = 4.00, p < 0.001). However, no significant changes were found in respect for rights (pre-test mean = 4.64, post-test mean = 4.76, p = 0.600), likely because of the school’s strong emphasis on this aspect. This study highlights the potential of game-based learning as an innovative tool to enhance social skills in multicultural settings. Qualitative findings further revealed improvements in peaceful communication, empathy, and respect for cultural diversity, demonstrating the game’s capacity to foster intercultural understanding. Additionally, students applied non-violent communication (NVC) strategies, including attentive listening, avoiding competitive arguments, and seeking fact-based solutions. Significant improvements were also observed in students’ knowledge of world religions (pre-test mean = 3.72, post-test mean = 4.44, p = 0.002).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".