Bibliographic record
Abstract
COVID-19 has created significant changes in the everyday lives of teachers, children and parents. Due to school lockdowns in the spring semester of 2020, teachers shifted from in-person classroom teaching into “emergent remote teaching” (Hodges et al. 2020, para. 5), where digital tools and software were used for instruction and teacher-student communications. Many children have also shifted their social lives from face-to-face to virtual interactions (Hutchins 2020); for example, engaging in online family story reading, social media participation, and joining after school activities digitally. This pandemic has highlighted the importance of being literate in digital environments for children. Digital literacy, that is, literacy practices undertaken across multi-media, involving “accessing, using and analysing digital texts and artefacts in addition to their production and dissemination” (Sefton-Green et al. 2016, p. 15). The importance of the digital world and digital tools for the post-COVID future where digital literacy could become more prominently featured for teachers, children, and parents must not be underemphasized.
 
 In this presentation, I reviewed the literature on young children’s digital literacy practices at home. Many studies have illustrated the benefits and various kinds of learning that children get from their digital play at home, including emergent literacy learning (Neumann 2016), digital citizenship (Bennett et al. 2016), etc. Moreover, I presented the complex trajectories of children playing with their digital devices and toys at home (Marsh 2017). In the 21st century children’s home play, the boundaries between the virtual and physical worlds are blurring (Marsh 2010; O’Mara and Laidlaw 2011; Carrington 2017).
 
 More importantly, this literature review suggests a gap and an opportunity for future researchers to explore home digital literacy of children, who are from minority backgrounds in Canada, as literacy practices are socially and culturally situated. This presentation illustrates the importance of my proposed doctoral research, as my research aims to explore Culturally and Linguistically Diverse (CLD) children’s digital home literacy practices in Canada.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".