Bibliographic record
Abstract
Since its inception in 1996, the GrassRoots Program has been instrumental in facilitating the integration of information and communication technologies (ICT) into the classrooms of Canadian schools. By linking the GrassRoots Program to the school curriculum and providing incentives for teachers to engage students in the process of co-creating electronic curriculum resources for the Internet, it has been influential in transforming classrooms into authentic centres of learning. There is overwhelming evidence supporting the concept that the GrassRoots Program is a powerful connector between ICT and new teaching theories. This paper provides an overview of innovation, a background to some of the challenges associated with large-scale innovation in the Canadian K-12 school system and the findings from a collection of 16 case studies conducted in innovative schools in Canada. An analysis of the data contained in the case studies indicates that the GrassRoots Program is having a positive impact on the diffusion of ICT in the classrooms of schools that are members of the Network of Innovation (NIS), and it is making a significant contribution to the development of a culture of innovation. The existence of GrassRoots projects has also increased the capacity for innovation by empowering and enabling the schools and teachers to work on multiple innovations simultaneously. Also, there is sufficient evidence to show that GrassRoots has had a major impact on: teacher professional learning; teacher technology skill development; student technology skill development, student employability skill development; access to teaching resources; leadership opportunities; and school growth and development.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.049 | 0.020 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".