Pedagogical Disruption then Construction
Bibliographic record
Abstract
Traditional approaches to education are evolving in order to improve student engagement in course content and enhance learning outcomes. The image of students passively absorbing information from an educator who is lecturing from behind a podium does not reflect the current scope and dimensions of higher education. In many post-secondary institutions, students are encouraged to participate, engage, and collaborate with educators and peers in the design, development, and delivery of educational content for blended environments. The use and integration of exciting new technology enable educators to disrupt traditional learning experiences by breaking down the status quo that characterizes many teaching and learning spaces and then recreating or (re)constructing teaching approaches that meet the learning needs of today’s students. Although this article includes the description of a research project that was conducted in a blended environment as a disruptive strategy, the article is primarily an expository piece around the need for disruptive pedagogies in post-secondary institutions and for construction of new philosophies and practices of teaching from theory, policy, and innovation.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.050 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".