Digital Literacy Practices and Learning at Home for Children of First Generation Newcomers in Canada
Bibliographic record
Abstract
Contemporary childhood exists in a rapidly changing literacy context in the digital age, where digital devices and technology are increasingly used at home and in school. This qualitative study explored newcomer children’s digital practices, as reported by their parents, and parents’ perspectives of their children’s digital usage at home. The COVID-19 pandemic and shifts to online remote learning have also impacted children’s digital literacy practices, and this study also provides understanding of culturally and linguistically diverse children’s digital literacy practices at home during this pandemic era. Theoretically, this research is framed by contemporary literacy studies, specifically, multiliteracies and new literacy studies, which understand literacy as everyday multimodal and multilingual social practices, across multimedia. I drew on Kress’s (1997, 2005) concept of multimodality in the digital context and Green’s (1988, 2012) three-dimensional literacy model as my conceptual frameworks to help me understand and interpret my data on children’s digital practices and how parents understand their children’s digital literacy practices at home. My study is a qualitative case study using ethnographically informed approaches and small stories to present the findings. The data collection tools I used were an online survey and semistructured interviews with first-generation newcomer parents to answer my research questions. I received 39 responses to the online survey and interviewed 4 first-generation newcomer parents. In this dissertation, I focus on the interview data with 3 of the newcomer parents. The findings indicate that the three children’s digital practices at home are situated in a contemporary context where digital devices and digital environments are essential for their social networking, family relationship building, learning, entertainment, creation activities, and recording life moments through photos and videos. My research shows that children are not only consumers of digital texts but also active producers. The three children have been exposed to social media influencers, particularly on the YouTube platform. Today, children are not always the only literacy learners at home and the parents are not always the literacy knowledge holders, as was typical in literacy environments historically. Instead, within the digital multimodal literacy context, children may know more than their parents and assist their parents’ technology usage at home. In terms of parents’ perspectives towards their children’s digital practices at home, the three participating parents tended to focus on their children’s operational skills with digital devices in the interviews and sometimes provided examples of how their children engaged in digital activities by following conventions and rules. However, the three parents did not share much about how their children use critical thinking and analysis in their digital practices. In addition, the parents described the difficulties of balancing their children’s digital usage at home in this contemporary era. The insights gained from my study have the potential to provide valuable information for newcomer parents, educators, and policymakers to understand newcomer children’s home digital literacy experiences. As well, this information may ease the anxieties of newcomer parents about parental management of digital practices and digital literacy. Educators and policymakers will be able to use this study to recognize the ways that newcomer children use digital tools in their homes as they consider curriculum, pedagogy, and policy for newcomer children.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".