ANALYSIS OF DISCOURSE FEATURES AND VERIFICATION OF SCORING LEVELS FOR INDEPENDENT AND INTEGRATED PROTOTYPE WRITTEN TASKS FOR THE NEW TOEFL®
Bibliographic record
Abstract
We assessed whether and how the discourse written for prototype integrated tasks (involving writing in response to print or audio source texts) field tested for the new TOEFL® differs from the discourse written for independent essays (i.e., the TOEFL essay). We selected 216 compositions written for 6 tasks by 36 examinees in a field test—representing Score Levels 3, 4, and 5 on the TOEFL essay—then coded the texts for lexical and syntactic complexity, grammatical accuracy, argument structure, orientations to evidence, and verbatim uses of source text. Analyses with nonparametric MANOVAs, following a 3-by-3 (task type by English proficiency level) within-subjects factorial design, showed that the discourse produced for the integrated writing tasks differed significantly at the lexical, syntactic, rhetorical, and pragmatic levels from the discourse produced in the independent essay on most of these variables. In certain analyses, these differences were also obtained across the 3 ESL proficiency levels.
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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 | 0.007 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".