The Impact of Personal and Professional Experiences: Holistic Exploration of Teacher Identity
Bibliographic record
Abstract
This paper investigates the impact of personal and professional experiences on the development of teacher identity. The holistic perspective in this article refers to the language teachers’ exploration of their personal and professional experiences with the use of both conscious/rational and intuitive/tacit thought processes. Three language teachers who participated in this study explored the beliefs, perceptions, and interpretations originating in their personal, educational, and professional experiences which also affected their teacher identity. Reflexive autobiographical journaling, a guided visualization activity, and three in-depth interviews were used in the research methodology. The results confirm that teacher identity is deeply embedded in one’s personal biography. The participants’ beliefs and interpretations rooted in their family environment influenced their early school experiences, career choice, instructional practice, teaching philosophy, and teacher identity. The results suggest that the analysis of teachers’ personal life experiences and their influence on professional practice can lead to a holistic understanding of the dominant influences on the development of teacher identity. The implications of this research are that a broader spectrum of the influences on teacher identity development needs more overt attention in professional development. This paper argues for the necessity of designing an integrated personal and professional development program for language teachers.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".