Journeys toward becoming teachers : subtitle charting the course of professional development
Bibliographic record
Abstract
The purpose of this study was threefold: 1) to illustrate how preservice teachers undergo identity transformations toward becoming teachers, 2) to understand the challenges these preservice teachers face as they navigate their B.Ed, program and 3) to identify potential impacts of prior perspectives on their journeys and challenges. Twenty-three secondary preservice teachers completed the Teaching Perspectives Inventory (TPI) twice and were interviewed twice over the course of their one-year B.Ed, program. TPI data were analyzed using a pre/post design along with comparisons of dominant teaching perspectives held at the beginning and end of the program. Analyses of the TPI data revealed an increase in participants' grouped mean scores on the Developmental perspective. The comparison of dominant perspectives showed that by the end of the program two shifts were evident: seven of twenty-three participants held no dominant teaching perspective and ten moved away from their initial dominant perspective to another dominant one. The multidimensional nature of these movements was reinforced by the analysis of interview data. Relying on a constant comparative method the interview analysis revealed the importance of participants' perceptions of their teaching identity and their commitment to the profession. These two dimensions were used to 'profile' participants in terms of their position at the beginning of the program and the changes (journeys) participants made over the course of their teacher education. The analysis of participants' journeys reinforced the notion of multidimensionality. Participants began with various levels of a teacher identity and a variety of reasons for why they began teacher education. Similarly, participants ended the program with different perceptions of themselves as teachers and wanted to engage in a variety of different teaching careers options (i.e., full time contract, teacher-on-call). The final analysis focused on what challenges participants experienced over the course of their teacher education program. Three themes emerged from the analysis: structural, professional, and role challenges. Initial perceptions of teacher identity strongly differentiated how participants experienced the challenges.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".