Behind the Snapshot: Teachers’ Experiences of Preparing Students in Lower Socioeconomic Status Schools for the Ontario Secondary School Literacy Test
Bibliographic record
Abstract
The goal of standardized testing is purportedly to equalize the educational landscape for all students, regardless of background. However, the effects of imposing large-scale assessment on students, teachers, and the education system might not always be as positive as organizations such as Ontario’s Education Quality and Accountability Office have acknowledged. This study explored the experiences of teachers preparing students in schools with a high proportion of students from low socioeconomic backgrounds to write Ontario’s Secondary School Literacy Test (OSSLT). To determine the effects of high-stakes standardized tests in Ontario, interviews were conducted with grade ten English teachers preparing students to write the OSSLT from schools identified as having low scores on the OSSLT and Toronto District School Board’s Learning Opportunities Index. The data showed that teachers found the OSSLT to be an ineffective tool to measure literacy and implement changes in the classroom, and represented an increased emotional cost. Both teachers also acknowledged that students’ socioeconomic status and social position prevented them from being able to succeed on the OSSLT, no matter the academic interventions used by teachers and schools. These findings suggest that the increased emotional cost on teachers and low value placed on the OSSLT by teachers is leading to unethical practices in test preparation, which ultimately affects the data collected from the OSSLT, used to inform educational policy in Ontario.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".