Public knowledge and perceptions of large-scale assessments
Bibliographic record
Abstract
Large-scale assessment has been used as an effective tool for government organizations to justify the well-being of educational systems in terms of accountability, gatekeeping, instructional diagnosis, and monitoring student achievement. The purpose of this study was to examine public knowledge and perceptions about large-scale assessments and thereby explore the accountability function of large-scale assessments. An online questionnaire combined with a paper and pencil questionnaire was distributed to residents in a small Canadian province using a nonprobability purposive sampling technique combined with convenience sampling. A total of 515 questionnaires were completed. The overall findings revealed that public was knowledgeable about students’ most recent performance on the Programme for International Student Assessment but not the most recent performance on the Pan-Canadian Assessment Program. The public’s perceptions towards large-scale assessments were in the middle of the scale and there was no statistically significant differences based on parental status, educational attainment, or cultural affiliations.\nKey words: large-scale assessment, common assessment, accountability, stakeholders, Prince Edward Island
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".