Teacher Opinions on the Problems Faced in Reading and Writing by Syrian Migrant Children in Their First Class at Primary School
Bibliographic record
Abstract
The objective of this study is to evaluate, according to the opinions of teachers, the problems faced by the children of Syrian families who have taken refuge in Turkey since 2011 with regard to their linguistic and communication skills, as well as their reading and writing process in Turkish as a foreign language. The research group is composed of seven teachers working in the first class of public primary schools attended by Syrian children. The study, which is based on the statements and perceptions of teachers, has been designed with the descriptive approach in the qualitative research method. Linguistic problems faced by Syrian immigrant children during their reading and writing process in Turkish as a foreign language, as well as the opinions of teachers on solution recommendations, are treated in detail in the study. The opinions of teachers are assessed under four main theme: Opinions on preparatory processes of instructing Turkish as a foreign language; opinions on communication approaches and the program implemented during the instruction of reading and writing; the importance of cooperation in the solving of problems; and opinions on instructing Turkish to Syrian children in a more effective manner. The study found that class teachers experience many problems in teaching Turkish reading and writing as a foreign language to Syrian students, as well as developing their linguistic and communication skills. The findings also reveal that teachers tend to look for support from their colleagues and other students in their classes, rather than from the families of children.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".