Qualitative Exploration of Death Education in Mainland China: Generating Design Considerations for a Culturally Relevant Curriculum Framework
Bibliographic record
Abstract
Death education has garnered increasing global attention for its role in enhancing emotional resilience, ethical awareness, and psychological preparedness, particularly in health and social sciences. However, in mainland China, its development remains constrained by deep-rooted cultural taboos and limited institutional support. This qualitative study explores design considerations for a culturally relevant death education curriculum within Chinese higher education. Semi-structured interviews and focus group discussions were conducted with 58 participants—including faculty, administrators, and students—from four universities across China. Thematic analysis revealed four core domains essential for effective curriculum development: (1) underlying principles, (2) content design, (3) organization and delivery, and (4) assessment and feedback. Findings emphasize the importance of cultural sensitivity, interdisciplinary integration, and participatory curriculum co-construction. The study contributes empirical evidence and practical strategies for embedding death education in ways that align with Chinese cultural norms and evolving educational needs, offering a robust foundation for future curriculum reform in this emerging field.
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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 | 0.023 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".