The Role of Writing Enablers on Writing Proficiency among Hispanic Students
Bibliographic record
Abstract
This study examined the contribution of three writing enabling skills (i.e., feedback perception, self-efficacy, and self-regulation) on writing performance among Hispanic students. Participants were 261 students in grades 3-5. Approximately 60% of students were Emerging Bilingual (EB) enrolled in dual language programming. Students completed writing enablers scales and three writing compositions. EB students were classified in proficiency levels based on state-mandated language assessment scores. Factor structure of the writing enablers scales deviated from the original measures. Using Exploratory Structural Equation Modeling, we found that, while feedback perception was not related to writing, self-efficacy and self-regulation significantly predicted writing outcomes, though in opposite directions. Students with different English proficiency showed significant differences in self-efficacy but not feedback perception and self-regulation. Results showed that students with higher writing self-efficacy exhibited better writing performance. Students more proficient in English had stronger self-efficacy, with highly advanced EB students reporting the highest scores.Impact StatementThis study examined the role of three writing enablers for successful writing performance among Hispanic students, with a majority of the sample classified as Emerging Bilingual. Findings showed that self-efficacy for writing emerged as a strong predictor of writing proficiency. This is particularly relevant for EB students, as they exhibited large differences in self-efficacy levels across varying levels of linguistic proficiency. Educators can leverage this information to effectively support student beliefs about their writing abilities, which in turn may lead to improved writing outcomes.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".