Metacognitive online reading strategy use: Readers' perceptions in L1 and L2
Bibliographic record
Abstract
This study aimed to explore whether first‐language (L1) readers of different language backgrounds would employ similar metacognitive online reading strategies and whether reading online in a second language (L2) could be influenced by L1 reading strategies. To this end, 52 Canadian college students as English L1 readers and 38 Iranian university students as both Farsi L1 and English L2 readers were selected. After completing three reading tasks on the Web, their perceptions about their use of strategies were assessed via a survey of reading strategies. Analyses of the data, using an analysis of variance and the Scheffé post hoc test, revealed certain differences. The Canadian readers perceived themselves to be high‐strategy users employing mostly a top‐down approach, whereas the Iranian readers in both Farsi and English appeared to be medium‐strategy users, favouring mostly a bottom‐up approach. Additionally, the correlation between readers' perceived use of strategies and their reading scores was statistically significant.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".