Parent perspectives on digital play-based early literacy-learning in marginalized communities
Bibliographic record
Abstract
This study examined parent perspectives on digital play-based learning for early literacy development in non-formal educational settings in Pakistan and Bangladesh, where access to quality education remains limited for marginalized communities. Drawing on neo-ecological theory as a guiding framework, we conducted a qualitative focus group study in which we analysed discussions with 40 parents whose children participated in a three-month digital play-based literacy intervention implemented through community learning centres and refugee camps. The parents reported significant improvements in their children's English language capabilities and digital literacies, often describing instances that reversed traditional knowledge hierarchies within families, with children teaching their parents English pronunciation and digital navigation. However, the parents simultaneously expressed concerns about traditional writing skill development and future educational transitions. The intervention affected parent–child engagement in education, with many parents reporting increased school visits and children showing a newfound enthusiasm for attending classes. Notable variations emerged between communities with different levels of prior educational access, with refugee parents in Bangladesh showing greater enthusiasm for digital interventions than those with previous exposure to conventional education. The study demonstrated how parents in marginalized communities carefully evaluated digital play through contextual lenses, and challenged simplistic narratives about technology adoption in resource-constrained environments. The parents’ perspectives highlight both the transformative potential of digital play for early literacy and the importance of contextually responsive approaches to implementing interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".