Rethinking the Engineering Design Process: Advantages of Incorporating Indigenous Knowledges, Perspectives, and Methodologies
Bibliographic record
Abstract
A recent increase in interest in the inclusion of Indigenous Ways of Knowing in engineering education has led to the discussion on how to bridge the worldviews of Indigenous Peoples and modern engineers. A literature review was performed to identify issues in current engineering practice, explore the value of perspective in the process of problem solving, distinguish the differences between engineering and Indigenous worldviews, analyze how these worldviews are compatible and incompatible, and formulate a general approach and value system for engineers going forward. Findings show that there is a need to revise how engineers approach problems, and that the consideration of alternative perspectives can provide new avenues for solving problems. There were indications of potential for symbiosis between Indigenous cultures and engineering, as the inclusion of Indigenous knowledges in engineering and engineering education would not only preserve Indigenous cultures, but alsoimprove the quality of engineering design solutions.
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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 | 0.059 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".