Bibliographic record
Abstract
Many of the activities discussed in this book may be unfamiliar to teachers or require some degree of planning if they are to be successfully implemented. In our experience, a workshop is often the best way of exploring what a particular professional activity, such as action research, consists of, what its pros and cons are, andwhether it might be of interest to teachers.Workshops, however, are often hit-or-miss affairs and are sometimes thrown together without a great deal of preliminary thought or planning. In view of the important role workshops can have in preparing teachers for different kinds of professional development initiatives, in this chapter we will examine the nature of workshops and suggest ways in which they can be used to support some of the activities we discuss throughout the book. What are workshops? A workshop is an intensive, short-term learning activity that is designed to provide an opportunity to acquire specific knowledge and skills. In a workshop, participants are expected to learn something that they can later apply in the classroom and to get hands-on experience with the topic, such as developing procedures for classroom observation or conducting action research. Workshops can also provide opportunities for participants to examine their beliefs or perspectives on teaching and learning, and use this process to reflect on their own teaching practices. Workshops can address issues related to both institutional improvement and individual development and they are led by a person who is considered an expert and who has relevant experience in the workshop topic. In our experience, workshop-based learning is particularly suitable for teachers because workshops can be scheduled outside of class time (e.g., on a Saturday).
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.302 | 0.160 |
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".