Indigenous Science Education and STEM-related Education
Bibliographic record
Abstract
Education broadly conceived includes the when, where, why, and how of teaching, learning, and maturation. From this perspective education takes shape and evolves across many contexts, including familial and kin relations; informal settings such as community-based organizations, museums, and libraries; and school settings from early childhood to post-secondary. Science, like education, is concerned with the how and why of things. Indigenous science education is grounded in the philosophical, intellectual, emotional, and spiritual traditions and practices of Indigenous knowledge systems (IKS). IKS is holistic, relational, and informed by experience in and with the natural world. Although IKS are tribally specific, there are commonalities and shared practices across communities. Indigenous knowledge systems ground much of Indigenous science education. While some principles of IKS and Indigenous science education that we discuss will apply to Indigenous peoples globally, there are also important differences to hold across geopolitical contexts. Rather than collapsing the vast heterogeneity of global indigeneity into a single category, we found it important to limit our scope. Furthermore, it may be inappropriate for the authors—Indigenous people from nations who largely reside within the borders of what is currently considered the United States and Canada—to reach beyond this scope. At the same time, we would be remiss if we did not acknowledge that there is important research within the field of comparative Indigenous education that speaks to connections between the local and the global. In addition, Indigenous peoples globally have traded, collaborated, and exchanged knowledge since time immemorial, and they continue to do so. IKS has taught us, the authors, to view reading and writing as activities that carry with them responsibilities for being in a relation with knowledge. Thus, this article is structured to provide relevant studies, reports, and resources on Indigenous science education and STEM-related education contextualized within what is currently known as the United States and Canada. And in this context, the authors use both Native and Indigenous interchangeably throughout this bibliography. The article is organized around four main sections: (1) Paradigms for Indigenous Science Education, (2) Indigenous Science Education across the Life-Span, (3) Curriculum and Assessments within Indigenous Science Education, and (4) Professional Organizations, Key Reports, and Books.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".