An Argument-Based Approach to the Validity of Interpretation and Use of Chinese High School Students' Grades across Educational Contexts
Bibliographic record
Abstract
Driven by the recent trend towards globalization and internationalization, grades are not only used locally where they are constructed, but also internationally for high-stakes admission decision-making into tertiary institutions. This dissertation investigates the validity of the interpretation and use of Chinese high school students’ grades for admission into Canadian universities. Inspired by the argument-based approaches to validity (e.g., Kane, 2006, 2013), the structure of validity argument is adopted as a means to systematically collect evidence, coherently analyze evidence, and present an evaluative judgment. \n \nTheoretically guided by grading frameworks from McMillan (2003) and Kunnath (2017), I propose a validity framework for grade interpretation and use to guide the research design of this dissertation. Three interrelated studies on Chinese high school grades are designed to collect various validity evidence, and these studies are written as individual manuscripts. The first study uses document analysis to explore the embedded values in documents that potentially influence Chinese high school teachers’ grading practices. The second study adopts a questionnaire to examine how local stakeholders, including teachers, students, and parents, interpret and use Chinese high school students’ grades. The third study adopts semi-structured interviews to understand Canadian university admission decision-makers’ interpretation and use of Chinese high school students’ grades. \n \nAfter a synthesis of the validity evidence collected in the three studies, I believe that overall, the interpretation and use of Chinese high school students’ grades for admission into Canadian universities seems reasonable and appropriate. The conceptualizations of Chinese high school students’ grades by both local stakeholders in China and admission decision-makers in Canada are largely aligned. Admission decision-makers employ various strategies in their use of grades to compensate for the misalignment of interpretation and improve the validity of grade interpretation and use. This dissertation responds to Brookhart’s (2013a) call for theoretically grounded grading research on the meaning and usefulness of grades and extends the validity argument for grade interpretation and use to a cross-cultural level. The research also contributes to the improvement of Chinese high school teachers’ grading practices and helps admission decision-makers in Canadian universities better understand Chinese high school students’ grades.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".