Associate-Candidate Relationships: A Study of Teacher Education Field Experiences
Bibliographic record
Abstract
Past research has identified the importance of the relationship between teacher candidates and their associate teachers during field experiences. Through the research questions that framed the study, I sought to contribute to a growing understanding of how the associate teacher-teacher candidate relationship develops from the perspective of teacher candidates. Using an interpretive lens, I explored the associate teacher-teacher candidate relationships of 5 teacher candidates at a mid-sized university in Southern Ontario. In this instrumental multicase study, the 5 participants described 13 pairs of relationships with associate teachers who modeled varying practices. The qualitative data surrounding these case relationships were collected through a focus group and semistructured interviews. Participants’ responses were analyzed using axial coding and constant comparative analysis. Participants identified feedback, guidance, support, genuine interactions, and relationship dynamics as central to successful field experiences. Participants also suggested that associate teachers might be better supported in their role if they were offered increased professional development from the faculties of education that organize the field experiences. The findings documented offer a fresh perspective of the role of the associate teacher in successful teacher education programs, particularly as experienced by the 5 participants.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".