Digital Literacies: a comparative analysis of in-service teacher education in Brazil and 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
In the constant flux of global migratory patterns, shifting borders, transliteracies and cross-cultural changes, digital technologies add certain complexities to an increasingly intricate and evolving educational landscape. In-service teachers grapple with digital literacy challenges in their appreciation of technology, changing teacher-student paradigms, and their own personal pedagogical philosophies. Within the context of the Brazil-Canada Knowledge Exchange Project and using a case study approach, this paper focuses on a comparative analysis of digital literacies amongst Canadian in-service teachers and their Brazilian counterparts. It further elaborates digital literacy concepts and considerations for mutually inclusive collaborations in multi-spherical global/local contexts. Supported by a bibliographic research and empirical data from two different case studies in Brazil and Canada, the paper examines in-service teacher professional development with a specific focus on technology education. The main findings suggest that pre-service and in-service teacher education should include digital literacies as part of their programs. They also suggest that these programs could take place through a critical framework, which can aid such practices so that technology education can be viewed as part of evolving social practices.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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