Raisins in the dough: Conversations on teacher identity and assessment practices
Bibliographic record
Abstract
We learn about teaching from each other, from our students, from our own experiences as students, teachers, and parents, and from our teaching and learning moments in non-academic settings.This study explores how teachers in higher education reconcile their ideas of professional identity with their professional obligations, particularly in terms of student assessment.Teachers in Quebec's Cgep system, like their colleagues in other post-secondary academic settings, often find themselves in the classroom with a wealth of knowledge in their field but very little conscious training in pedagogy.Through a series of interactive interviews, I gathered the stories and insights of nine fellow teachers.I used these interviews as a source for a constructed narrative in which the nine participants and I gather around a dinner table to discuss our individual, personal journeys in becoming teachers, and the many shared experiences, challenges, and epiphanies that represent a teacher's development.Woven into this narrative are recollections from my personal and professional experiences.These memories, and how I remember them, serve to enrich the discussion.Ultimately, four main themes emerge: the familiar 'accidentally a teacher' career path; the tension between teachers' philosophies of formative learning and institutional demands for accountability; the importance of introspection and deliberate practice in our ongoing development; and the value of peer mentoring moments and communities of practice in supporting that development.The aim of this exploration is not to generate definitive concepts of how to teach in Cgep, nor to determine who is or is not suited to the task.Rather, the goal is to shed light on our shared journey, to see that we are not the first or only teachers to face challenges, to learn on the job, or to realize, suddenly, that we are not who we teach-and they are not us.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".