Blended learning and Syrian refugees' empowerment through a capability approach lens
Bibliographic record
Abstract
This study analyses the learning experiences of three Syrian refugee youth who enrolled in and completed blended learning (BL) programmes in Jordan, in order to explicate how BL has/or has not empowered those refugees. To achieve this objective, the following research questions framed this study: Does blended learning empower Syrian refugee youth living in Jordan? 1. Is blended learning, in the case of Syrian refugee youth, an empowering capability? 2. Does blended learning help Syrian refugee youth to overcome their restrictive ‘rules of the game’? 3. Does blended learning improve Syrian refugee youth’s resource portfolio? This study followed a case study approach. Three Syrian youth, each of whom attended a different BL programme, were interviewed between December 2018 and March 2019. While all three cases expressed aspirations that are education-bound, this study shows some difference in the aspirations of males and females and of urban refugees versus those residing in the camps. BL has been for all three cases a feasible learning opportunity. Programme providers designed the courses in a manner that accommodated to refugees’ locations, time, and economic status. Social media disseminated information about educational opportunities and possessing smartphones made following up with lectures and assignments possible and easy. The investigated BL programmes proved also to be enjoyable due to their constructive, learner-centred and collaborative approach, and competent facilitators. However, this finding does not indicate that those programmes were “empowering”. Restrictive legislations that constrain refugees’ work, movement, and lives, as well as patriarchal traditions that hampered females’ choices of education, were “rules of the game” that hindered students’ ability to fully benefit from the provided programmes. Despite the development of oral and public speaking, employability, and English language skills and despite the enhancement of self-esteem, confidence, and respect towards others, those programmes did not lead to refugees’ full empowerment.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".