Unveiling Voices: Engaging Syrian Refugee Children and Educators Through Digital Storytelling Project
Bibliographic record
Abstract
While a child's primary sources of supportive relationships and learning experiences are at home, schools play a critical role as the first significant social environment for refugee children. In Ontario, thousands of young refugee children, including many from Syria, attend mainstream schools. However, many educators are not adequately prepared to address the specific needs of these children. This participatory visual research study seeks to bridge this gap in teacher education by exploring the pedagogical potential of digital storytelling to do the following: 1) enable Syrian refugee children to express their resettlement experiences through first-person digital, multimodal narratives; 2) provide educators with deeper insights into the perspectives of Syrian refugee children; and 3) foster social awareness among both educators and refugee students. The study aims to highlight Syrian refugee children’s resettlement experiences from their own viewpoints, enhance educators' understanding of these experiences, and investigate both the children's experience of creating digital stories and the educators' experience in facilitating digital storytelling workshops. Exploring the educational potential of digital storytelling with Syrian refugee children and educators may also support the resettlement needs of refugee children from other regions entering Canadian schools. Grounded in the new sociology of childhood, sociocultural theory, and critical pedagogy, this study employs participatory visual methodology and digital storytelling to challenge dominant narratives and promote a more inclusive understanding of knowledge. These approaches are aligned with the inquiry-based learning commonly used with marginalized communities. The findings demonstrate that digital storytelling offered refugee children a meaningful way to represent their experiences and foster social transformation, strengthening their sense of connection with others. For educators, facilitating the digital storytelling project challenged preconceptions about refugee children and positively impacted their approach to working with culturally diverse students.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.018 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".