Exploring the roles of L1 reading, L2 proficiency, strategy use and anxiety in L2 Reading comprehension
Bibliographic record
Abstract
Background Second language (L2) reading is a complex process in which two languages constantly interact. L1 reading and L2 proficiency are two well‐acknowledged factors contributing to L2 reading comprehension. Other factors, such as strategy use and anxiety, might also predict L2 reading comprehension, but their roles have not been examined in the presence of L1 reading and L2 proficiency. Method Participants were 147 high school Chinese English as a foreign language (EFL) learners (mean age = 17.8, SD = 0.48). They were assessed on their L2 reading comprehension, L1 reading comprehension, L2 proficiency (L2 vocabulary and L2 syntactic knowledge), strategy use and reading anxiety. Results Hierarchical regression model analyses showed that L1 reading significantly contributed to L2 reading comprehension in the presence of L2 proficiency. Strategy use and anxiety were significant predictors of L2 reading comprehension in the presence of L1 reading and L2 proficiency. Together, they accounted for 53% of the variance in L2 reading comprehension. L2 proficiency moderated the relations between L1 and L2 reading comprehension and strategy use and L2 reading comprehension but not the relation between anxiety and L2 reading comprehension. Conclusions Besides the well‐acknowledged L1 reading and L2 proficiency, strategy use and anxiety were also significant predictors of L2 reading comprehension, stressing the importance of these cognitive and affective factors in L2 reading. By revealing the moderating role of L2 proficiency, these findings deepen our understanding of the nature of the relations between L1 and L2 reading comprehension, strategy use and L2 reading comprehension.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".