Analyzing writing performance of L1, L2, and Generation 1.5 community college students through Coh-Metrix
Bibliographic record
Abstract
Abstract Proficient writing in English is a challenge for the linguistically diverse community college population. Writing research at the community college level is warranted in order to guide instruction and assist students in achieving higher levels of proficient writing. The current study examined the writing of three community college groups: native English Language students (L1, n = 146), English as a Second Language students primarily educated abroad (L2, n = 31), and English as a Second Language students who graduated from high school and lived in the United States for more than four years (Generation 1.5, n = 72). The writing samples were analyzed using Coh-Metrix to examine group differences in lexical, syntactic, and cohesion characteristics. Results indicated significant differences in syntactic and lexical measures among all groups, with small to large effect sizes. The majority of differences related to proficient writing characteristics were found between L1 and Generation 1.5 groups.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".