Living on both sides of the screen: An Ethnographic study of the impact of personal and professional identities on teacher candidates’ pedagogical practices
Bibliographic record
Abstract
The purpose of this ethnographic study is to trace the process of identity development of eight teacher candidates enrolled in the Bachelor of Education and Master of Arts in Teaching and Learning programs offered by a large English public university located in the Eastern part of Canada. In this study, the researcher aims to address how the personal and professional identities of teacher candidates impact their classroom practices during student teaching, using relevant conceptual and theoretical lenses to trace this process. Using the qualitative research methods of individual interview, reflective memo, and eportfolio, the researcher collected primary evidence from the selected teacher candidates. The findings of the study reveal that the ethos of becoming a teacher resides in various stages of teacher socialization. This process begins early within informal spaces such as family, schooling, and communities of sociocultural orientation and continues across formal spaces of Teacher Education and student teaching, including career-long professional development. This study provides insights into the ways teacher candidates make meaning of themselves while learning to teach vis-à-vis their personal histories, beliefs system, and prior learning experiences. The study findings also indicate that teacher candidates express a variety of positive and negative emotions triggered during coteaching with their assigned co-operating teachers. These emotional responses correspondingly affect their sense of teacher agency and their voices as individual teachers, and thus influence their emerging professional identities. The study suggests some implications for teacher training, teaching practice, and for teacher research at micro and macro levels. On a micro level, the study findings are useful for teacher educators and mentor-teachers in designing teaching processes that integrate the personal histories and prior experiences of individual teacher candidates. On a macro level, the findings inform future researchers about probable methodological approaches to conduct future research on identity development and teacher practice. Major findings are discussed, along with study limitations, and future directions
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".