Bilinguals and Monolinguals' Performance in English Language Learning in Nigeria
Bibliographic record
Abstract
Some linguists argue that bilinguals’ knowledge and competence in their first language contribute to effective second language learning. On the contrary, other linguists who favour monolingualism hold that the first language stands as an obstacle for bilinguals. These opposing views motivated the present undertaking. Thus this study investigates the performance of both bilingual and monolingual learners’ of English Language in a second language situation in Nigeria. Terminal results in English Language tests of 108 Yoruba/English bilinguals and 108 Nigerian English monolinguals at the Senior Secondary School level were compared. Findings revealed that, on the one hand, more bilinguals are found in the pass region than monolinguals; on the other hand, more monolinguals were found in the fail region than bilinguals. These results confirm the position that bilingualism plays supportive role in second language learning, especially in second language situation. Consequently, stakeholders in second language learning might need to strengthen the learning and use of bilinguals’ first language in order to enhance effective second language learning.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".