The effect of different bilingual experiences on attentional control ability
Bibliographic record
Abstract
Aims and objectives: Attentional control is an important cognitive ability, and it includes the abilities of attention and inhibitory control. It remains unclear whether a bilingual advantage in attentional control exists and whether different bilingual experiences exert distinct effects on this ability. This study aimed to address these questions. Research Questions: (1) Does bilingual experience enhance attentional control? (2) Do different bilingual experiences differentially influence attentional control? Methodology: Chinese-English bilinguals, Spanish-English bilinguals, and English monolinguals were recruited for the study. The participants underwent assessments of their English learning experiences, English proficiency, and attentional control abilities. Data and Analysis: Data analysis was performed by using SPSS 23. The group differences in the English learning experiences, English proficiency, Attentional Network Task (ANT) indicators for Chinese-English bilinguals, Spanish-English bilinguals, and English monolinguals were analyzed using analysis of variance (ANOVA). The correlations between ANT and English learning experiences, and English proficiency for three groups were analyzed using Pearson correlation. Conclusion: Compared with English monolinguals, both Chinese-English bilinguals and Spanish-English bilinguals did not show better attentional control ability. Further, we found that compared with Spanish-English bilinguals, Chinese-English bilinguals showed better inhibitory control, indicating that different bilingual experiences have different impacts on inhibitory control ability. However, no significant difference was found between Chinese-English bilinguals and Spanish-English bilinguals after controlling for age or AOA (age of acquisition), indicating age or AOA influenced the effect of different bilingual experiences on inhibitory control ability. The correlation results indicated the older the age, the better the attention ability for Chinese-English bilinguals; the older the age and AOA, the better the attention ability for Spanish-English bilinguals; the older the AOA, the poorer the inhibitory control ability for Spanish-English bilinguals. This study fills the gap in the effect of different bilingual experiences on attentional control ability.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".