INTERCULTURAL DIALOGUES IN COVID-19
Bibliographic record
Abstract
This paper explores how conversations about digital culture, innovation, and online pedagogy can inform practices accentuated during the pandemic. The immediatism adopted by universities around the world due to the urgency of lockdowns is problematic in many ways. Firstly, the little time to switch to an online environment, advance online delivery, and ensure assessment is undeniable. Second, the extent to which universities were at different levels of digitally ready infrastructure and related staff and students’ development, training, and readiness to learn and teach remotely is also challenging. However, research shows the important role of digital culture in pedagogical choices inside the classroom, as much as it considers how individuals cope with technological innovation in their daily online practices. From a Freirean perspective, pedagogy is reflective and transformative and online pedagogies can reconceptualize knowledge and practice, minimize physical and intangible spaces, and redefine time, constructing new ecologies of learning for an inclusive pedagogy. This paper addresses the above by presenting data from interviews with instructors, administrative staff, and students at three universities in Brazil, Canada, and the UK. This qualitative study uses intercultural concepts of pedagogical innovation, and how participants have adapted their practices in digital culture. We further explore the pedagogical implications of their attitudes towards online learning, the reconstruction of their self-awareness, and aim at corroborating future comprehensions on how COVID-19 will impact higher education. This paper is timely in problematizing concepts that are important to understanding and dealing with digital culture, innovation, and online pedagogies in learning contexts post-COVID.
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.
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 | 0.020 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.026 | 0.040 |
| Scholarly communication | 0.016 | 0.010 |
| Open science | 0.002 | 0.025 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".