“Everything’s technology now”: the role of technology in home- and school-based summer learning activities in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Though summer learning loss has been widely documented across both the United States and Canada, there is little knowledge on how parents and teachers view the use of technology in the context of summer vacation, and what the role of digital tools are in potentially alleviating achievement gaps due to summer learning loss. Drawing on 71 parent and 37 teacher interviews from a large-scale Canadian study examining summer learning loss in Ontario through summer literacy and numeracy programs for students (grades 1–3), this study highlights the complexities associated with using digital tool in both home and school life in the summer. Through extensions of Bourdieu’s theory of cultural capital, we suggest that digital tools are becoming a new type of valued skillset that parents and educators are acknowledging. In specific, our main findings center around three interrelated themes: i) comfort with technology; ii) home-school connections; and iii) perception of children as digital natives. Results may be fruitful for parents, educators, and policymakers to understand the larger role that digital technology plays amongst Canadian families and teachers during the summer months and school year. Capturing these discussions can maximize both school and home use of digital tools.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 |
| 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 it