Applying modified participatory video and popular education to improve environmental science learning in northern Manitoba
Bibliographic record
Abstract
Northern Indigenous communities are confronted by many social and economic barriers as well as declines in the sustainability of freshwater which has emerged as a crucial issue in these regions. Responses to challenges are compromised by an education system that is still imported from the South and fails to reflect the rich cultural traditions of the North. It is in these remote locales that freshwater maintainability and insightful caring are felt directly, and it is within these same communities that alternative place-based learning will accomplish the most. The University College of the North has recently developed an approach that is cross-cultural in nature and grounded both in western science and the traditions of nearby Oji-Cree communities. Although culturally appropriate, the continued absence of diversity in lesson delivery and entry-level assessment of adult student performance inadvertently enforces a uni-dimensional Euro-dominant model of education. This study explores the implications of different approaches to environmental education on academic performance and experience in northern Manitoba. In addition to conventional lesson delivery, the value of non-conventional approaches using participatory video and situated education were explored. Experiences and learning outcomes of 97 incoming students from seven different academic programs centered on an exercise that calculated stream flow. Outcomes were assessed using competency-based field skills tests and ‘unsolicited’ student interview responses. Non-conventional approaches were characterized by improved academic performance, raised environmental consciousness, and overt acts of engagement creating global context at a personal level concerning freshwater supply. Situated in-stream opportunities and participatory video not only stimulated transformative moments, but significantly increased (p=0.003) mean test scores by 26%, raised Indigenous student technical skillset scores by 12% (p = 0.05), and significantly improved (p=0.07) conceptual understanding. Increases in performance were exhibited by students who were Indigenous, female, and those registered in the natural resource program, supporting the importance of participatory video and experiential learning in postsecondary education. The results of this study show implementation of ‘alternative’ non-conventional lesson deliveries will increase student awareness and ‘individual advocacy’ regarding freshwater conservation while also helping improve the success and retention of postsecondary students across northern Manitoba, and for that matter Canada.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".