Bibliographic record
Abstract
Student achievement in Grade 9 has been linked to both secondary and post-secondary outcomes. Although Ontario has implemented significant curriculum and secondary school reforms, a significant subset of Ontario Grade 9 students consistently do not attain proficiency in mathematics. Students that take the applied mathematics course—on the pathway to college—are more likely to not reach the provincial standard on the provincial Grade 9 mathematics assessment than they are to reach it. This can have long-lasting consequences. The purpose of this qualitative study was to discern practices from the field that might contribute to better student outcomes in Grade 9 Applied Mathematics classrooms. Mathematics education experts from across the province were interviewed and visits were conducted at four of the province’s most successful schools on the Grade 9 provincial mathematics assessment. The findings from this study contribute to our understanding of the types of resources, professional development, departmental, leadership, and teaching practices that support student achievement in Grade 9 Applied Mathematics. The findings can be distilled into six central ideas. These are the importance of: reform-based teaching strategies and dispositions that foster intellectual engagement and investment in learning; instructional leadership by both the school administrator and mathematics department head; collaboration for both the teachers of and students in the Grade 9 Applied Mathematics course; valuing EQAO assessments at all levels of the system; mitigating the stigma around applied-level courses; and, careful attention to the placement of teachers in Grade 9 Applied classrooms. This study contributes to the Ontario literature on Grade 9 Applied Mathematics and the literature on implementing mathematics reform. The findings of this study are of relevance to policy-makers and practitioners, especially school leaders and teachers. The study concludes with recommendations for both research and practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".