An Initial Development of an Analytic Rubric for Assessing Critical Thinking in English Argumentative Essays of EFL College Students
Bibliographic record
Abstract
This study aims to initially develop a Critical-Thinking-in-Argumentative-Essay Rubric (CTER) for EFL college students. Participants of this study were five experts and two groups of raters. Data sources included the experts’ validation survey for the CTER, interviews and writing samples. Three phases for developing the CTER were conducted, and the evaluative descriptors of the rubric were revised based on the experts’ comments. To complete the initial development of the rubric, the raters and the first researcher used the CTER to evaluate the writing samples. The scores obtained from the evaluation were analyzed to examine the inter-rater reliability of the rubric. The findings showed that the CTER contained six clear and valid domains for assessing critical thinking in argumentative essays of EFL students. The total scoring results from the six domains achieved a moderate inter-rater reliability with ICC of 0.70 and Kendall’s W of 0.5 (p < 0.05). The raters perceived that the CTER could be used to promote learning and critical thinking of EFL learners. Pedagogical implications were presented based on the findings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".