Understanding How the Student Success Strategy Has Developed and Contributed to Student Outcomes in One Ontario District
Bibliographic record
Abstract
In 2003 the Ontario Ministry of Education launched the Student Success Strategy, a game changing initiative of whole system reform. Since that time Ontario’s graduation rate has risen from 68% to 85.5% by 2015, but surprisingly few studies have examined the strategy. The purpose of this study was to better understand how the Student Success Strategy developed and contributed to student outcomes in one school district. A qualitative research approach was used for the study, which was also complemented by administrative data. Schools which would be considered were identified using a purposeful sampling technique. Qualitative data was derived from interviewing educators who were members of their schools’ Student Success Team. Interview questions were focused on four key pillars of the strategy: efforts at connecting with students, providing programs that enable achievement, improving teaching and learning, and connecting with the community. Administrative data originated from Ontario’s Education Quality and Accountability Office test scores, as well as district and Ministry reports. Six key findings from the study emerged. The first revealed that fostering positive connections with secondary students takes time, requiring a multi-tiered differentiated approach involving layers of interventions and support. The second finding demonstrated that improving the range of programs, notably the Specialist High Skills Major, led to an enrolment surge and improved academic performances. The third main finding confirmed on-going efforts at improving teaching and learning, and the critical role administrators play as instructional leaders driving improvements. The fourth finding noted mixed results in connecting with the community, with no gains in engaging parents, however gains were made in accessing community supports for students as well as through dual-credit opportunities with positive post-secondary outcomes. The fifth finding revealed strong commonalities on how the Student Success Strategy had developed over time. The sixth key finding exposed the challenges connected to the strategy, notably replacing key staff, and the desire to retain greater school autonomy. What clearly was unquestionable was the impact policy, programs, and people – both within the school and community - could have in connecting with students, meeting their varied and individual needs, including pathways for their future success.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".