Provoking Conversations on Inquiry in Teaching Education, (2012) by Darren E. Lund, E. Lisa Panayotidis, Hans Smits, and Jo Towers
Bibliographic record
Abstract
Lund and his colleagues have published a rather unusual book.It is unusual in a number of ways, starting with the point that much of its contents have been presented and published previously over a 10-year period (2003 to 2012).There are four main sections of the book, and the first three appeared as previous conference presentations and later as journal articles.This is not hidden by the authors-indeed, very little seems hidden in this volume even when the possibility exists that what is written may reflect negatively on the writers-but they have indulged in the luxury of revisiting and revising their earlier work in light of later experience and deeper perspective.This is, in short, a kind of post-mortem examination of a teacher training program that no longer runs.The result is an in-depth examination of the ontology of a teacher training program and the struggles, personal and professional, encountered by some of the faculty members who created it.This book challenges the reader throughout and asks more questions than it answers to provoke readers' responses to the problems of educating teachers in a higher education setting.It challenges the reader in two senses.First, it challenges the reader to keep up with and understand the philosophical explanation of their ideas, the basis of these ideas, and the rationale for choosing them.At times the small volume becomes quite a dense read.Second, and more to the point of the authors' intentions, it challenges the reader to examine his or her own practice and goals in teaching by posing the provocations as points of departure for selfreflection.There are several threads running throughout the book and one of these is to prod the reader into becoming more self-aware of her or his own teaching practices, the intellectual rationale for one's approach to teaching, and what the effects of those practices might be on the students being taught.The book is divided into four broad areas, and as mentioned earlier, each of the first three sections had been published before in slightly different form.The first area is about curriculum (published in 2003), the second is that of narratives (published in 2006), and the third is about embodying inquiry (published in 2008).The final section is about the faculty's responsibility to history and discusses the authors' reactions to the closure of their program, their feelings about their experiment of training prospective teachers much differently from other teacher preparation programs, and reflections on the long term impact of their practices upon themselves, the profession, and the students who participated in this program.Each chapter has a respondent, who, with one exception, comes from outside the immediate teaching staff of the Faculty of Education at the
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.020 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 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".