Asian adolescents’ out-of-school encounters with English and Korean literacy
Bibliographic record
Abstract
The acquisition of second language (L2) academic literacy has attracted increasing interest among L2 literacy researchers as the number of English Language Learners (ELLs) studying in schools in Anglophone countries like Australia, the United Kingdom, Canada, and the United States continues to grow. However, this emphasis on academic literacy has led L2 researchers to overlook the importance of exploring other types of literacy, especially out-of-school literacy. In particular, few studies have examined the impact of out-of-school literacy activities on overall literacy acquisition, as well as on the development of academic literacy skills. This article describes a study that examined the nature of three Asian adolescent ELLs’ out-of-school literacy practices and their implications for school-based literacy growth. These Asian adolescent ELLs engaged in various types of reading and forms of writing in both their native language (L1), Korean, and their L2, English, within both print and computer-based contexts. The findings suggest some often overlooked connections, direct or indirect, between in and out-of-school literacy. The article discusses the implications of these findings for pedagogy and future research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".