Bibliographic record
Abstract
Internationally, the practicum is a cornerstone of initial teacher education in preparing pre-service teachers to enter the teaching profession. This edited collection expands theory and research in pedagogies of practicum by examining different ways teacher education programs across the globe experienced, modified, and innovated the practicum in response to the COVID-19 pandemic. What have we learned about the limitations of traditional in-school, brick-and-mortar practicum, and to what extent were these limitations challenged by pandemic shift s? Contributions from researchers, program chairs, teacher educators, field coordinators, and faculty supervisors address themes such as virtual practicum programming, emerging technologies that enhance the student teaching experience, and ways to support preservice teachers’ well-being during practicum sessions. Chapters in this unique volume invite teacher education programs to reimagine the field experience post-pandemic. "This thoughtfully constructed volume not only documents creative and responsive teacher education program designs and practices from around the world, but also gives insight into the principles, processes, and learnings of the teacher educators who collaborated to create coherent and meaningful practicum experiences in their contexts." —Dr. Kathy Broad, Associate Professor, Department of Curriculum, Teaching and Learning, Ontario Institute for Studies in Education, University of Toronto "Many innovative approaches in the teaching practicum during the pandemic have proven to carry further value and should be explored in-depth to enhance concepts and delivery. This book provides an excellent global overview of practicum stories and will inspire thoughtful reflection to enhance quality teacher education." —Charles Hopkins, UNESCO Chair in Reorienting Education Towards Sustainability, York University
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 | 0.005 | 0.010 |
| 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 | 0.019 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.027 | 0.011 |
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".