Investigating ESL Learners’ Socioeconomic Environment on Their Writing Competence in Lagos, Nigeria: Implications for Pedagogy
Bibliographic record
Abstract
This study investigated the influence of Junior Secondary School (JSS) students’ socioeconomic environment on their competence in writing in English. Ten schools from randomly selected private and public schools in Lagos State, Nigeria were used. A total of 300 randomly selected students constituted the sample. Data were collected through structured questionnaire and adapted essay writing tests. Students’ tests were marked by considering content, organisation, expression, and mechanical accuracy (COEMA) as criteria and scored on 10 points: thus, 6-10 points was regarded as competent; while 1-5 points = incompetent. Information on students’ socioeconomic environment was collected through the questionnaire. Results revealed 66% of the respondents demonstrated writing incompetence and 34% demonstrated writing competence. Of the 66% of incompetence, 45% was from the public schools while 21% was from the private schools. Of all the socioeconomic factors examined, language of communication at home was established as a determining factor. All stake holders, especially, teachers must focus on grammar for the improvement of students’ writing skill. Key words : Socioeconomic environment; English Writing Competence; Private school; Public school
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".