Reading Online in Foreign Languages: A Study of Strategy Use
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p class="3">Scores of studies have established that when learning online, students must be equipped with different sets of strategies and skills than in a physical classroom setting (Anderson, 2003; Broadbent &amp; Poon, 2015; Coiro, 2007; Leu et al., 2007; Michinov, Brunot, Le Bohec, Juhel, &amp; Delaval, 2011; Salmon, 2013). The present study, by virtue of exploring foreign language learners’ online reading experience, aimed to identify the reading strategies that learners would use when engaged in online reading activities in the target foreign languages. Thirty-two foreign language learners whose native language was English participated in the study. The Online Survey of Reading Strategies (OSORS) designed by Anderson (2003) was administered to investigate the following four research questions: (1) What are the strategies that language learners would or would not use when reading online in foreign languages? (2) Would foreign language learners use some of the online reading strategies more frequently than other strategies? (3) Would different levels of foreign language proficiencies influence language learners’ use of the strategies? (4) What could foreign language teachers do in their instruction to help students acquire and broaden their repertoire of online reading strategies? Data analysis demonstrated the most and least frequently used strategies of the foreign language learners and uncovered a significant difference in the frequency of use among the strategies. However, there was no significant difference found between the use of online reading strategies and learners’ foreign language proficiencies. Implications and suggestions for future research and practice were proposed accordingly. </p>
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 it