Exploring the Experiences of High School Syrian Refugee Students with Interrupted Formal Education and their Teachers in ELD Classrooms
Bibliographic record
Abstract
Exploring the experiences of Syrian refugee Students with Interrupted Formal Education (SIFE) and their teachers in English and Literacy Development (ELD) classrooms is an emergent topic of interest in the field of education in Canada. There is a need to understand the ways in which ELD teachers respond to the cultural, linguistic, and ethnic diversity of Syrian refugee SIFEs and create learning opportunities for those students while supporting them emotionally, socially, and academically. Thus, the aim of this research was to explore the nature of the experiences of high school Syrian refugee SIFEs and their teachers in ELD classrooms in Ontario. The research focused on exploring classroom practices and supportive pedagogies, specifically caring and Culturally Responsive Teaching (CRT) pedagogies enacted in ELD classrooms in two secondary schools in Ontario. Social structures and power relationships reflected in ELD classrooms, in addition to resources and constraints to the implementation of caring and CRT, were also examined. The major research question was What is the nature of the experiences of high school Syrian refugee students with interrupted formal education and their teachers in ELD classrooms in Ontario? The theoretical framework adopted in this exploratory case study drew on critical theory, CRT, and Ethics of Care (EoC). The methods used included semi-structured interviews, documentation, and the researcher’s reflective notes. The analysis revealed the complexity of the nature of Syrian refugee SIFEs’ and their teachers’ experiences in ELD classrooms and the nuances these experiences entail. There was evidence of caring and CRT practices enacted in ELD classrooms. That said, some of the ELD teachers’ instructions still need to reflect their students’ ages, academic levels, and core culture. Power and privileging such as power and hierarchical teacher-student relationships and the dominance of a Western curriculum canon were reflected in ELD classrooms. Resources and constraints to the implementation of caring and CRT were also signaled. Key recommendations included embedding equality and diversity in the ELD curriculum and putting more emphasis on caring and CRT pedagogies. The practical and theoretical recommendations aim to disrupt deficient institutional and classroom practices and emphasize supportive pedagogies in ELD classrooms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.018 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".