Investigation into the Role of Mother Tongue on the Acquisition of French as a Foreign Language (FFL) in the South African Education System
Bibliographic record
Abstract
This paper focuses on the impact of mother tongue on students learning French as a foreign language (FFL) in South Africa.While identifying well defined advantages and challenges, this study is aimed at explicating how native language backgrounds impact students' acquisition of French as a foreign language.The study made use of the qualitative research method with a diverse sample of 50 students from educational institutions within the Gauteng and Kwazulu Natal provinces.A Qualitative analysis of the study revealed that there is a significant correlation between students' mother tongues and their levels of proficiency in French.Findings of this research show that learners whose first languages present structural similarities to French tend to excel in language acquisition unlike students hailing from linguistic backgrounds that diverge significantly from French who tend to encounter enormous difficulties, particularly in areas such as grammar and pronunciation.These findings highlight the urgency for developing tailored teaching strategies for linguistic diversity, thereby suggesting important implications for pedagogy and curriculum design in a multilingual context like South Africa.Further research that will explore the long-term effects of mother tongue influence on language acquisition and proficiency in FFL should be carried out, as well as the larger implications for language learning strategies in similar educational settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".