Indigenous Knowledges and Perspectives in Engineering Education: Team Reflections on a Series of Faculty Workshops
Bibliographic record
Abstract
Indigenous Peoples, and their languages, cultures, Knowledges, beliefs, and values have been historically silenced through systematic colonial suppression in Canada for centuries.Since 2008, the country has been engaged in a national effort to learn these truths and practice reconciliation, called for by the Truth and Reconciliation (TRC) of Canada.Education, used as a tool to eradicate Indigenous Peoples in Canada, is one mechanism by which Canadians can right these historical wrongs.As such, four engineering faculty members in a large research university in Western Canada in a year-long internally funded project designed a series of engineering-specific faculty workshops/events to bring Indigenous Knowledges and perspectives into engineering education. GOALS AND PURPOSEThe project goals were for faculty members to experience a shift in perspective by seeing engineering education through Indigenous worldviews, and to support faculty in integrating Indigenous Knowledges, perspectives, and design principles into engineering curricula.The purpose of this paper is to explore the impact of this work from team members' perspectives. METHODSTeam members' Reflections After Events are inductively analysed for overarching themes. OUTCOMESThree themes emerged from team members' individual critical reflections: challenges, culture, and change.There were differences in team members' responses to the themes and in the tones of their reflections.It is anticipated that this paper will stimulate both intertextual and interpersonal conversations with Indigenous Peoples and allies working to make space in engineering education for Indigenous Peoples and their ways of being, knowing, and doing. CONCLUSIONSOverall, 1.This work requires many people; 2. mistakes are made; 3. students are vital in forwarding this work; 4. faculty are in different places; and 5. a paradigmatic shift is required.Through team members' critical reflections we have stimulated deeper understandings on the impact of this work and how paradigmatic change was observed and can be encouraged.
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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 | 0.019 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.035 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 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".