The Rights and Responsibility of Test Takers when Large-Scale Testing Is Used for Classroom Assessment
Bibliographic record
Abstract
The purpose of this research was to identify conflicts in the rights and responsibility of Grade 9 test takers when some parts of a large-scale test are marked by teachers and used in the calculation of students’ class marks. Data from teachers’ questionnaires and students’ questionnaires from a 2009–10 administration of a large-scale test of Grade 9 mathematics were analyzed using descriptive statistics. Written comments by teachers were analyzed into themes. Results were interpreted using a framework comprised of a policy document and two theories that are relevant to large-scale testing: the rights and responsibility of test takers as documented in the Standards for Educational and Psychological Testing (AERA/APA/NCME/JCSEPT, 2014), expectancy-value theory of motivation, and theory regarding the developmental stage of students in Grade 9. Several conflicts were identified. Potential solutions to conflicts were presented.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".