The role of self efficacy in constraints negotiation : rural Nova Scotia physical education teachers ability to implement outdoor education
Bibliographic record
Abstract
Previous research has highlighted a noticeable shift from humans, especially \nchildren and youth, engaging in activities in natural environments to an increasing \ntendency to participate in sedentary activities in front of a screen. Nova Scotia has taken \nsteps to reduce the disconnect from the natural environment many youth are \nexperiencing through implementation of a Grade 10 Outdoor Pursuits module into the \npublic education system. However, even with the support of the province of Nova Scotia \nand school boards, research indicates that experience and attitudinal barriers of teachers \nimplementing outdoor education are as compelling as economic and logistical barriers. \nThe purpose of this study was to increase understanding of outdoor education in two \nNova Scotia school boards through analysis of teachers? experiences on the ground. In \nparticular, understanding the constraints teachers face implementing and delivering the \nOutdoor Pursuits module and the relationship between physical education teachers? \nmotivation and perceived self-efficacy, and how they negotiated the constraints they do \nface. Overall, teachers? implementing the module identified with the importance of \ngetting students outside in their own backyards in the hope of promoting lifelong learning \nand physically active lifestyles. However, the findings illustrated that although a strong \nfocus of the province and school boards has been on acquiring the physical supports \nneeded, such as equipment and resources, developing self-efficacy of teachers and \nbuilding social networks was more influential to participation levels. Key amongst the \nmajor influences in developing teachers? self-efficacy with Outdoor Pursuits were being \ncomfortable with and exhibiting a mastery of activities, experiencing the pursuits under \nthe guidance of someone else who could successfully model it, and receiving peer \nsupport, feedback and discussion to stimulate excitement and the acquisition of \nknowledge. The evidence from this study indicates that training, the provision of \nmentors, and creating a structure of peer support are vital to raising teachers? confidence, \nthereby enabling them to successfully negotiate future constraints.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".