Multilinguals’ and monolinguals’ use of awareness-raising activities
Bibliographic record
Abstract
Research findings have confirmed that multilingual acquisition differs essentially from second language acquisition, and that multilingual learners have advantages over monolingual learners when learning a new language. These advantages are attributed to metalinguistic awareness, highly developed learning strategies and communicative sensitivity. This paper reports on research examining the extent to which multilingual and monolingual participants benefit from awareness-raising activities on listening skills, based on 252 female participants. Additionally, participants with two different learning styles – reflective/impulsive – are compared. For data analysis, a three-way ANOVA analysis with post hoc test was conducted. Results showed that being multilingual has significant effects on the use of awareness-raising activities. Similarly, it was revealed that being reflective/impulsive has a significant effect on multilingual speakers’ listening enhancement. Results also indicated that the interaction between being multilingual/monolingual and being reflective/impulsive is statistically significant. The results obtained give some insights on the effect of individual factors, especially cognitive styles, on the language development of multilinguals, and shed some light on models developed for multilingualism, especially the Dynamic Multilingual Model. The theoretical and practical implications of the study are discussed in detail.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".