The componential model of reading in bilingual learners.
Bibliographic record
Abstract
According to the Componential Model of Reading (CMR; Aaron, Joshi, Gooden, & Bentum, 2008), reading comprehension can be explained by 3 domains—cognitive, psychological, and ecological domains. We examined the direct and indirect contributions of these 3 domains to reading comprehension in bilingual learners. Participants included 124 bilingual children in Grades 4 through 6 who spoke Chinese as their first language. They were administered a battery of language and literacy measures, and motivation and acculturation questionnaires. Additionally, the participants’ parents completed a home literacy environment questionnaire in Chinese. Using structural equation modeling, we found direct effects of the cognitive and psychological domains on reading comprehension. The ecological domain only had an indirect influence on reading comprehension via the cognitive and psychological domains. The findings support and extend the CMR model and advance our understanding of the nature of the relationships among the different components of the model among bilingual learners. (PsycInfo Database Record (c) 2020 APA, all rights reserved)
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".